D.C. Duives
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
26 records found
1
Using Crowd Simulation to Support Experience-Driven Police Decision-Making during Large-Scale Events
Designing and evaluating a decision framework in the Rotterdam Police context
Crowd simulation is a well-developed research field, but its outputs are not structurally used in police event preparation. Police decision-making during large-scale events is strongly experience-driven. Professionals rely on practical knowledge, prior experience, local context, and coordination with other actors to assess risks and prepare measures. This is necessary in practice, but it can also make assumptions about crowd movement, bottlenecks, emergency accessibility, and possible measures difficult to test or explain.
The main challenge is therefore not the absence of simulation models, but the absence of a method that translates simulation outputs into usable decision-support information. This paper presents the Crowd Simulation Decision Framework, developed using Design Science Research at the Rotterdam Police. The framework is a method-type artefact that structures when and how crowd simulation can be used in the risk analysis and advisory phase. It links police risks, simulation questions, scenarios, outputs, interpretation, and possible measures to decision points in the event process.
The framework was demonstrated in the Meent case during a large-scale running event in Rotterdam and evaluated with police professionals. The evaluation focused on interpretability, usefulness, and usability. The findings suggest that the framework can support risk analysis by making assumptions explicit, comparing scenarios, and helping to substantiate police advice. At the same time, simulation outputs require clear explanation, transparent assumptions, a model check with practitioners, feedback loops, and a simulation expert who can translate between police practice and technical modelling. Without these conditions, outputs may be misinterpreted or may suggest more certainty than the model can provide.
The paper contributes design knowledge on how existing crowd simulation outputs can be integrated into experience-driven police decision-making. Simulation-based decision support should start with the decision-making problem, not with the model. The framework should therefore be seen as structured support for professional judgement, not as proof that simulation automatically improves decision-making. ...
The main challenge is therefore not the absence of simulation models, but the absence of a method that translates simulation outputs into usable decision-support information. This paper presents the Crowd Simulation Decision Framework, developed using Design Science Research at the Rotterdam Police. The framework is a method-type artefact that structures when and how crowd simulation can be used in the risk analysis and advisory phase. It links police risks, simulation questions, scenarios, outputs, interpretation, and possible measures to decision points in the event process.
The framework was demonstrated in the Meent case during a large-scale running event in Rotterdam and evaluated with police professionals. The evaluation focused on interpretability, usefulness, and usability. The findings suggest that the framework can support risk analysis by making assumptions explicit, comparing scenarios, and helping to substantiate police advice. At the same time, simulation outputs require clear explanation, transparent assumptions, a model check with practitioners, feedback loops, and a simulation expert who can translate between police practice and technical modelling. Without these conditions, outputs may be misinterpreted or may suggest more certainty than the model can provide.
The paper contributes design knowledge on how existing crowd simulation outputs can be integrated into experience-driven police decision-making. Simulation-based decision support should start with the decision-making problem, not with the model. The framework should therefore be seen as structured support for professional judgement, not as proof that simulation automatically improves decision-making. ...
Crowd simulation is a well-developed research field, but its outputs are not structurally used in police event preparation. Police decision-making during large-scale events is strongly experience-driven. Professionals rely on practical knowledge, prior experience, local context, and coordination with other actors to assess risks and prepare measures. This is necessary in practice, but it can also make assumptions about crowd movement, bottlenecks, emergency accessibility, and possible measures difficult to test or explain.
The main challenge is therefore not the absence of simulation models, but the absence of a method that translates simulation outputs into usable decision-support information. This paper presents the Crowd Simulation Decision Framework, developed using Design Science Research at the Rotterdam Police. The framework is a method-type artefact that structures when and how crowd simulation can be used in the risk analysis and advisory phase. It links police risks, simulation questions, scenarios, outputs, interpretation, and possible measures to decision points in the event process.
The framework was demonstrated in the Meent case during a large-scale running event in Rotterdam and evaluated with police professionals. The evaluation focused on interpretability, usefulness, and usability. The findings suggest that the framework can support risk analysis by making assumptions explicit, comparing scenarios, and helping to substantiate police advice. At the same time, simulation outputs require clear explanation, transparent assumptions, a model check with practitioners, feedback loops, and a simulation expert who can translate between police practice and technical modelling. Without these conditions, outputs may be misinterpreted or may suggest more certainty than the model can provide.
The paper contributes design knowledge on how existing crowd simulation outputs can be integrated into experience-driven police decision-making. Simulation-based decision support should start with the decision-making problem, not with the model. The framework should therefore be seen as structured support for professional judgement, not as proof that simulation automatically improves decision-making.
The main challenge is therefore not the absence of simulation models, but the absence of a method that translates simulation outputs into usable decision-support information. This paper presents the Crowd Simulation Decision Framework, developed using Design Science Research at the Rotterdam Police. The framework is a method-type artefact that structures when and how crowd simulation can be used in the risk analysis and advisory phase. It links police risks, simulation questions, scenarios, outputs, interpretation, and possible measures to decision points in the event process.
The framework was demonstrated in the Meent case during a large-scale running event in Rotterdam and evaluated with police professionals. The evaluation focused on interpretability, usefulness, and usability. The findings suggest that the framework can support risk analysis by making assumptions explicit, comparing scenarios, and helping to substantiate police advice. At the same time, simulation outputs require clear explanation, transparent assumptions, a model check with practitioners, feedback loops, and a simulation expert who can translate between police practice and technical modelling. Without these conditions, outputs may be misinterpreted or may suggest more certainty than the model can provide.
The paper contributes design knowledge on how existing crowd simulation outputs can be integrated into experience-driven police decision-making. Simulation-based decision support should start with the decision-making problem, not with the model. The framework should therefore be seen as structured support for professional judgement, not as proof that simulation automatically improves decision-making.
Beyond the Average Pedestrian
A Qualitative Analysis of Route Choice in the Netherlands
Across Europe, walking is promoted as a healthy and sustainable mode of transport, and in the Netherlands it accounts for a substantial share of daily trips. Planning models and walkability tools typically represent pedestrians as a single, homogeneous group, while the implicit “average pedestrian” largely reflects the male experience. International research shows that women value and navigate public space differently, placing greater importance on factors such as lighting, surveillance, and enclosure, particularly with respect to perceived safety. In the Netherlands, the high quality of pedestrian infrastructure has resulted in statistical gender neutrality in mode choice, leading to the assumption that walking experiences are also gender neutral. Whether this assumption holds for route choice has remained largely unexplored. This study therefore examines how gender shapes pedestrian route-choice decisions among young adults (18–25 years) in Dutch urban environments.
A qualitative research approach was adopted, consisting of sixteen go-along walking interviews conducted in Amsterdam, Delft, and Rotterdam, complemented by a night-time scenario and a map-pointing task. The interviews were analysed using thematic coding based on the Four Pillars of Pedestrian Route Choice, a framework developed for this study that synthesises international and Dutch literature into four dimensions: social safety, traffic safety, aesthetic experience, and efficiency. Fourteen of the fifteen indicators identified in the literature emerged in participants’ accounts. Only physical exertion was absent, consistent with the flat and well-maintained Dutch environment. Two additional themes, visual variety and cognitive ease, emerged inductively, while familiarity influenced the interpretation of multiple other factors.
The central finding is that gender influences route choice not through differences in which environmental cues are noticed, but through differences in how those cues are interpreted and whether they lead to behavioural change. Male and female participants generally recognised the same environmental characteristics but differed in the meaning they assigned to them and in the decisions that followed. All female participants reported changing their routes in response to social-safety cues, whereas none of the male participants did, although two indicated they might do so hypothetically. While based on a small exploratory sample, this pattern was consistent across participants. Female participants interpreted cues from all four pillars through the lens of personal safety and evaluated them differently during the day and at night. Male participants considered the four dimensions more independently and rarely regarded social-safety cues as sufficient reason to deviate from the shortest route. Participants also described route choice as an overall interpretation of the streetscape rather than the result of weighing isolated factors, and most were unable to identify the precise point at which they decided to alter their route.
These findings suggest that the apparent gender neutrality reported in Dutch aggregate travel statistics may result from analysing behaviour at the mode-choice level rather than the route-choice level. Differences in route choice can therefore remain hidden despite similar overall walking rates. Spatially, these differences manifested themselves in recurring avoidance of parks, alleys, and poorly lit streets after dark by female participants, reducing their effective accessibility to urban space. Because route choice depends on how pedestrians interpret environmental cues rather than simply on the presence of those cues, the study also indicates that quantitative walkability indices may overlook important aspects of pedestrian decision-making.
This research contributes empirical evidence of gendered pedestrian behaviour at the route-choice level in the Netherlands, a country widely regarded as a benchmark for pedestrian-friendly infrastructure. The findings suggest that even high-quality infrastructure alone is insufficient to ensure an equitable walking experience for women and men. ...
A qualitative research approach was adopted, consisting of sixteen go-along walking interviews conducted in Amsterdam, Delft, and Rotterdam, complemented by a night-time scenario and a map-pointing task. The interviews were analysed using thematic coding based on the Four Pillars of Pedestrian Route Choice, a framework developed for this study that synthesises international and Dutch literature into four dimensions: social safety, traffic safety, aesthetic experience, and efficiency. Fourteen of the fifteen indicators identified in the literature emerged in participants’ accounts. Only physical exertion was absent, consistent with the flat and well-maintained Dutch environment. Two additional themes, visual variety and cognitive ease, emerged inductively, while familiarity influenced the interpretation of multiple other factors.
The central finding is that gender influences route choice not through differences in which environmental cues are noticed, but through differences in how those cues are interpreted and whether they lead to behavioural change. Male and female participants generally recognised the same environmental characteristics but differed in the meaning they assigned to them and in the decisions that followed. All female participants reported changing their routes in response to social-safety cues, whereas none of the male participants did, although two indicated they might do so hypothetically. While based on a small exploratory sample, this pattern was consistent across participants. Female participants interpreted cues from all four pillars through the lens of personal safety and evaluated them differently during the day and at night. Male participants considered the four dimensions more independently and rarely regarded social-safety cues as sufficient reason to deviate from the shortest route. Participants also described route choice as an overall interpretation of the streetscape rather than the result of weighing isolated factors, and most were unable to identify the precise point at which they decided to alter their route.
These findings suggest that the apparent gender neutrality reported in Dutch aggregate travel statistics may result from analysing behaviour at the mode-choice level rather than the route-choice level. Differences in route choice can therefore remain hidden despite similar overall walking rates. Spatially, these differences manifested themselves in recurring avoidance of parks, alleys, and poorly lit streets after dark by female participants, reducing their effective accessibility to urban space. Because route choice depends on how pedestrians interpret environmental cues rather than simply on the presence of those cues, the study also indicates that quantitative walkability indices may overlook important aspects of pedestrian decision-making.
This research contributes empirical evidence of gendered pedestrian behaviour at the route-choice level in the Netherlands, a country widely regarded as a benchmark for pedestrian-friendly infrastructure. The findings suggest that even high-quality infrastructure alone is insufficient to ensure an equitable walking experience for women and men. ...
Across Europe, walking is promoted as a healthy and sustainable mode of transport, and in the Netherlands it accounts for a substantial share of daily trips. Planning models and walkability tools typically represent pedestrians as a single, homogeneous group, while the implicit “average pedestrian” largely reflects the male experience. International research shows that women value and navigate public space differently, placing greater importance on factors such as lighting, surveillance, and enclosure, particularly with respect to perceived safety. In the Netherlands, the high quality of pedestrian infrastructure has resulted in statistical gender neutrality in mode choice, leading to the assumption that walking experiences are also gender neutral. Whether this assumption holds for route choice has remained largely unexplored. This study therefore examines how gender shapes pedestrian route-choice decisions among young adults (18–25 years) in Dutch urban environments.
A qualitative research approach was adopted, consisting of sixteen go-along walking interviews conducted in Amsterdam, Delft, and Rotterdam, complemented by a night-time scenario and a map-pointing task. The interviews were analysed using thematic coding based on the Four Pillars of Pedestrian Route Choice, a framework developed for this study that synthesises international and Dutch literature into four dimensions: social safety, traffic safety, aesthetic experience, and efficiency. Fourteen of the fifteen indicators identified in the literature emerged in participants’ accounts. Only physical exertion was absent, consistent with the flat and well-maintained Dutch environment. Two additional themes, visual variety and cognitive ease, emerged inductively, while familiarity influenced the interpretation of multiple other factors.
The central finding is that gender influences route choice not through differences in which environmental cues are noticed, but through differences in how those cues are interpreted and whether they lead to behavioural change. Male and female participants generally recognised the same environmental characteristics but differed in the meaning they assigned to them and in the decisions that followed. All female participants reported changing their routes in response to social-safety cues, whereas none of the male participants did, although two indicated they might do so hypothetically. While based on a small exploratory sample, this pattern was consistent across participants. Female participants interpreted cues from all four pillars through the lens of personal safety and evaluated them differently during the day and at night. Male participants considered the four dimensions more independently and rarely regarded social-safety cues as sufficient reason to deviate from the shortest route. Participants also described route choice as an overall interpretation of the streetscape rather than the result of weighing isolated factors, and most were unable to identify the precise point at which they decided to alter their route.
These findings suggest that the apparent gender neutrality reported in Dutch aggregate travel statistics may result from analysing behaviour at the mode-choice level rather than the route-choice level. Differences in route choice can therefore remain hidden despite similar overall walking rates. Spatially, these differences manifested themselves in recurring avoidance of parks, alleys, and poorly lit streets after dark by female participants, reducing their effective accessibility to urban space. Because route choice depends on how pedestrians interpret environmental cues rather than simply on the presence of those cues, the study also indicates that quantitative walkability indices may overlook important aspects of pedestrian decision-making.
This research contributes empirical evidence of gendered pedestrian behaviour at the route-choice level in the Netherlands, a country widely regarded as a benchmark for pedestrian-friendly infrastructure. The findings suggest that even high-quality infrastructure alone is insufficient to ensure an equitable walking experience for women and men.
A qualitative research approach was adopted, consisting of sixteen go-along walking interviews conducted in Amsterdam, Delft, and Rotterdam, complemented by a night-time scenario and a map-pointing task. The interviews were analysed using thematic coding based on the Four Pillars of Pedestrian Route Choice, a framework developed for this study that synthesises international and Dutch literature into four dimensions: social safety, traffic safety, aesthetic experience, and efficiency. Fourteen of the fifteen indicators identified in the literature emerged in participants’ accounts. Only physical exertion was absent, consistent with the flat and well-maintained Dutch environment. Two additional themes, visual variety and cognitive ease, emerged inductively, while familiarity influenced the interpretation of multiple other factors.
The central finding is that gender influences route choice not through differences in which environmental cues are noticed, but through differences in how those cues are interpreted and whether they lead to behavioural change. Male and female participants generally recognised the same environmental characteristics but differed in the meaning they assigned to them and in the decisions that followed. All female participants reported changing their routes in response to social-safety cues, whereas none of the male participants did, although two indicated they might do so hypothetically. While based on a small exploratory sample, this pattern was consistent across participants. Female participants interpreted cues from all four pillars through the lens of personal safety and evaluated them differently during the day and at night. Male participants considered the four dimensions more independently and rarely regarded social-safety cues as sufficient reason to deviate from the shortest route. Participants also described route choice as an overall interpretation of the streetscape rather than the result of weighing isolated factors, and most were unable to identify the precise point at which they decided to alter their route.
These findings suggest that the apparent gender neutrality reported in Dutch aggregate travel statistics may result from analysing behaviour at the mode-choice level rather than the route-choice level. Differences in route choice can therefore remain hidden despite similar overall walking rates. Spatially, these differences manifested themselves in recurring avoidance of parks, alleys, and poorly lit streets after dark by female participants, reducing their effective accessibility to urban space. Because route choice depends on how pedestrians interpret environmental cues rather than simply on the presence of those cues, the study also indicates that quantitative walkability indices may overlook important aspects of pedestrian decision-making.
This research contributes empirical evidence of gendered pedestrian behaviour at the route-choice level in the Netherlands, a country widely regarded as a benchmark for pedestrian-friendly infrastructure. The findings suggest that even high-quality infrastructure alone is insufficient to ensure an equitable walking experience for women and men.
Right to The City
Drawing on Urban Experiences in The Pursuit of Gender Inclusivity in Amsterdam’s Built Environment
This thesis examines how experiences of safety, comfort, and accessibility in Amsterdam’s outdoor public space can be translated into a quantitative Urban Experience Index (UEI) that supports more gender-inclusive urban design and policymaking. The research addresses a practical gap: although gendered differences in public space are recognised, Amsterdam still lacks a spatially applicable tool that makes these differences visible in planning and design. The study therefore develops and tests a reproducible UEI for selected routes and places in Amsterdam.
The thesis first develops a conceptual framework that links built-environment elements to experience through affordances, temporal context, and positionality. Based on this framework, selected survey findings were translated into a demonstration model for Amsterdam through a limited set of measurable spatial indicators and scenario-specific weights. The resulting UEI was then applied to selected routes and places and validated against lived experience.
The findings show that translating urban experience into a spatial index is possible, but only in a selective and transparent way. The clearest patterns concern the safety side of experience. Discomfort increases sharply after dark, especially where poor lighting, weak visibility, low social presence, and desolate atmospheres coincide. Route-level outcomes are more sensitive to scenario changes than place-level outcomes, and the strongest shifts appear between day and night rather than between women and men within the same light condition. Women responded more negatively than men to dark and empty conditions, and in the model results, men scored higher than women on every selected route in the night scenario and on all selected places in both day and night scenarios.
The validation interviews broadly support the direction of the model, while also showing that the UEI captures some dimensions of experience better than others. It identifies patterned conditions of discomfort well, but cannot fully represent the social meaning of presence, behaviour, belonging, or anticipation. The thesis concludes that the UEI is most useful as a screening and conversation tool rather than as a definitive measure of inclusivity. Its main value lies in making uneven urban conditions more visible and in helping planners identify where gender-sensitive and time-sensitive interventions are most needed. ...
The thesis first develops a conceptual framework that links built-environment elements to experience through affordances, temporal context, and positionality. Based on this framework, selected survey findings were translated into a demonstration model for Amsterdam through a limited set of measurable spatial indicators and scenario-specific weights. The resulting UEI was then applied to selected routes and places and validated against lived experience.
The findings show that translating urban experience into a spatial index is possible, but only in a selective and transparent way. The clearest patterns concern the safety side of experience. Discomfort increases sharply after dark, especially where poor lighting, weak visibility, low social presence, and desolate atmospheres coincide. Route-level outcomes are more sensitive to scenario changes than place-level outcomes, and the strongest shifts appear between day and night rather than between women and men within the same light condition. Women responded more negatively than men to dark and empty conditions, and in the model results, men scored higher than women on every selected route in the night scenario and on all selected places in both day and night scenarios.
The validation interviews broadly support the direction of the model, while also showing that the UEI captures some dimensions of experience better than others. It identifies patterned conditions of discomfort well, but cannot fully represent the social meaning of presence, behaviour, belonging, or anticipation. The thesis concludes that the UEI is most useful as a screening and conversation tool rather than as a definitive measure of inclusivity. Its main value lies in making uneven urban conditions more visible and in helping planners identify where gender-sensitive and time-sensitive interventions are most needed. ...
This thesis examines how experiences of safety, comfort, and accessibility in Amsterdam’s outdoor public space can be translated into a quantitative Urban Experience Index (UEI) that supports more gender-inclusive urban design and policymaking. The research addresses a practical gap: although gendered differences in public space are recognised, Amsterdam still lacks a spatially applicable tool that makes these differences visible in planning and design. The study therefore develops and tests a reproducible UEI for selected routes and places in Amsterdam.
The thesis first develops a conceptual framework that links built-environment elements to experience through affordances, temporal context, and positionality. Based on this framework, selected survey findings were translated into a demonstration model for Amsterdam through a limited set of measurable spatial indicators and scenario-specific weights. The resulting UEI was then applied to selected routes and places and validated against lived experience.
The findings show that translating urban experience into a spatial index is possible, but only in a selective and transparent way. The clearest patterns concern the safety side of experience. Discomfort increases sharply after dark, especially where poor lighting, weak visibility, low social presence, and desolate atmospheres coincide. Route-level outcomes are more sensitive to scenario changes than place-level outcomes, and the strongest shifts appear between day and night rather than between women and men within the same light condition. Women responded more negatively than men to dark and empty conditions, and in the model results, men scored higher than women on every selected route in the night scenario and on all selected places in both day and night scenarios.
The validation interviews broadly support the direction of the model, while also showing that the UEI captures some dimensions of experience better than others. It identifies patterned conditions of discomfort well, but cannot fully represent the social meaning of presence, behaviour, belonging, or anticipation. The thesis concludes that the UEI is most useful as a screening and conversation tool rather than as a definitive measure of inclusivity. Its main value lies in making uneven urban conditions more visible and in helping planners identify where gender-sensitive and time-sensitive interventions are most needed.
The thesis first develops a conceptual framework that links built-environment elements to experience through affordances, temporal context, and positionality. Based on this framework, selected survey findings were translated into a demonstration model for Amsterdam through a limited set of measurable spatial indicators and scenario-specific weights. The resulting UEI was then applied to selected routes and places and validated against lived experience.
The findings show that translating urban experience into a spatial index is possible, but only in a selective and transparent way. The clearest patterns concern the safety side of experience. Discomfort increases sharply after dark, especially where poor lighting, weak visibility, low social presence, and desolate atmospheres coincide. Route-level outcomes are more sensitive to scenario changes than place-level outcomes, and the strongest shifts appear between day and night rather than between women and men within the same light condition. Women responded more negatively than men to dark and empty conditions, and in the model results, men scored higher than women on every selected route in the night scenario and on all selected places in both day and night scenarios.
The validation interviews broadly support the direction of the model, while also showing that the UEI captures some dimensions of experience better than others. It identifies patterned conditions of discomfort well, but cannot fully represent the social meaning of presence, behaviour, belonging, or anticipation. The thesis concludes that the UEI is most useful as a screening and conversation tool rather than as a definitive measure of inclusivity. Its main value lies in making uneven urban conditions more visible and in helping planners identify where gender-sensitive and time-sensitive interventions are most needed.
Building-level pedestrian trip generation
For Dutch urban areas using open data
Cities are increasingly pressured by rapid urbanisation, climate change, and congested transport networks, intensifying the need for sustainable mobility solutions that prioritise walking and cycling. Designing effective pedestrian-friendly interventions requires reliable, city-scale models of pedestrian activity. However, most existing transport models remain car-oriented or focus on microscopic pedestrian dynamics. Macroscopic pedestrian models are often highly data-intensive, rely on household surveys or extensive pedestrian counts, and are poorly suited to the Dutch context, where such data are limited. This creates a clear gap: the need for a practical, open-data-based, building-level pedestrian trip-generation model for Dutch cities.
To address this gap, this study develops a building-level pedestrian trip-generation model with fine spatial and temporal resolution, tailored to Dutch conditions and relying exclusively on widely available open data. The central research question is: To what extent can an existing pedestrian trip-generation model be adapted to reflect pedestrian trip-generation dynamics in the Dutch urban context?
The study adapts Sevtsuk’s Urban Network Analysis (UNA) framework into a Dutch-specific, building-level model referred to as BPT-Gen (Building-level Pedestrian Trip Generation). The UNA framework was selected because it offers a practical balance between spatial detail and data requirements while remaining transparent and reproducible. Several key adaptations are introduced to ensure applicability to Dutch cities.
First, buildings are identified and classified using the Dutch BAG dataset, supplemented with OpenStreetMap (OSM) data to capture land use, amenities, and public transport facilities. This enables a detailed and consistent representation of pedestrian trip origins and destinations at the building level.
Second, the derivation of building activity weights is modified. These weights represent the estimated number of unique daily users per building. Where detailed local data are available, weights are calculated directly; otherwise, Dutch building and occupancy standards or carefully selected proxy indicators are applied. This approach allows the model to remain operational across data-limited contexts while explicitly acknowledging uncertainty.
Building on the UNA framework, the model incorporates accessibility-adjusted activity weights. Each building is connected to the pedestrian network, and destination-specific Reach indices are calculated using a walking radius relevant to Dutch conditions. These indices adjust baseline activity weights to account for behavioural tendencies and destination attractiveness. Sensitivity analyses examine how assumptions regarding walking radius and normalisation methods influence model outcomes.
A major extension beyond the original UNA framework is the integration of temporal dynamics through hourly walking trip rates. Trip purposes derived from the Dutch ODiN travel survey are mapped to building types, and corresponding hourly origin–destination trip rates are applied. Combining these rates with accessibility-adjusted weights yields hourly, building-level pedestrian trip-generation estimates for the study area.
Model performance is assessed through face validation using observed pedestrian counts. Results show that the adapted model reproduces realistic spatial and temporal patterns for building types supported by reliable activity data, particularly housing and major train stations. Underprediction is observed for offices and leisure facilities, where activity weights rely on proxy indicators and where walking trips are likely underreported in ODiN. Sensitivity analyses confirm that trip-generation outcomes depend strongly on proxy selection and accessibility assumptions, revealing structural uncertainties.
Despite these limitations, the BPT-Gen model provides clear practical value. It identifies key generators of walking trips, peak periods, and accessibility-driven hotspots using only open data. By linking trip purposes to building types at hourly resolution, the framework fills an important gap in Dutch pedestrian modelling and offers a transparent foundation for future extensions. The findings demonstrate that open-data pedestrian models can provide meaningful planning insights while highlighting the need for improved activity indicators and further validation using street-level pedestrian flow data.
...
To address this gap, this study develops a building-level pedestrian trip-generation model with fine spatial and temporal resolution, tailored to Dutch conditions and relying exclusively on widely available open data. The central research question is: To what extent can an existing pedestrian trip-generation model be adapted to reflect pedestrian trip-generation dynamics in the Dutch urban context?
The study adapts Sevtsuk’s Urban Network Analysis (UNA) framework into a Dutch-specific, building-level model referred to as BPT-Gen (Building-level Pedestrian Trip Generation). The UNA framework was selected because it offers a practical balance between spatial detail and data requirements while remaining transparent and reproducible. Several key adaptations are introduced to ensure applicability to Dutch cities.
First, buildings are identified and classified using the Dutch BAG dataset, supplemented with OpenStreetMap (OSM) data to capture land use, amenities, and public transport facilities. This enables a detailed and consistent representation of pedestrian trip origins and destinations at the building level.
Second, the derivation of building activity weights is modified. These weights represent the estimated number of unique daily users per building. Where detailed local data are available, weights are calculated directly; otherwise, Dutch building and occupancy standards or carefully selected proxy indicators are applied. This approach allows the model to remain operational across data-limited contexts while explicitly acknowledging uncertainty.
Building on the UNA framework, the model incorporates accessibility-adjusted activity weights. Each building is connected to the pedestrian network, and destination-specific Reach indices are calculated using a walking radius relevant to Dutch conditions. These indices adjust baseline activity weights to account for behavioural tendencies and destination attractiveness. Sensitivity analyses examine how assumptions regarding walking radius and normalisation methods influence model outcomes.
A major extension beyond the original UNA framework is the integration of temporal dynamics through hourly walking trip rates. Trip purposes derived from the Dutch ODiN travel survey are mapped to building types, and corresponding hourly origin–destination trip rates are applied. Combining these rates with accessibility-adjusted weights yields hourly, building-level pedestrian trip-generation estimates for the study area.
Model performance is assessed through face validation using observed pedestrian counts. Results show that the adapted model reproduces realistic spatial and temporal patterns for building types supported by reliable activity data, particularly housing and major train stations. Underprediction is observed for offices and leisure facilities, where activity weights rely on proxy indicators and where walking trips are likely underreported in ODiN. Sensitivity analyses confirm that trip-generation outcomes depend strongly on proxy selection and accessibility assumptions, revealing structural uncertainties.
Despite these limitations, the BPT-Gen model provides clear practical value. It identifies key generators of walking trips, peak periods, and accessibility-driven hotspots using only open data. By linking trip purposes to building types at hourly resolution, the framework fills an important gap in Dutch pedestrian modelling and offers a transparent foundation for future extensions. The findings demonstrate that open-data pedestrian models can provide meaningful planning insights while highlighting the need for improved activity indicators and further validation using street-level pedestrian flow data.
...
Cities are increasingly pressured by rapid urbanisation, climate change, and congested transport networks, intensifying the need for sustainable mobility solutions that prioritise walking and cycling. Designing effective pedestrian-friendly interventions requires reliable, city-scale models of pedestrian activity. However, most existing transport models remain car-oriented or focus on microscopic pedestrian dynamics. Macroscopic pedestrian models are often highly data-intensive, rely on household surveys or extensive pedestrian counts, and are poorly suited to the Dutch context, where such data are limited. This creates a clear gap: the need for a practical, open-data-based, building-level pedestrian trip-generation model for Dutch cities.
To address this gap, this study develops a building-level pedestrian trip-generation model with fine spatial and temporal resolution, tailored to Dutch conditions and relying exclusively on widely available open data. The central research question is: To what extent can an existing pedestrian trip-generation model be adapted to reflect pedestrian trip-generation dynamics in the Dutch urban context?
The study adapts Sevtsuk’s Urban Network Analysis (UNA) framework into a Dutch-specific, building-level model referred to as BPT-Gen (Building-level Pedestrian Trip Generation). The UNA framework was selected because it offers a practical balance between spatial detail and data requirements while remaining transparent and reproducible. Several key adaptations are introduced to ensure applicability to Dutch cities.
First, buildings are identified and classified using the Dutch BAG dataset, supplemented with OpenStreetMap (OSM) data to capture land use, amenities, and public transport facilities. This enables a detailed and consistent representation of pedestrian trip origins and destinations at the building level.
Second, the derivation of building activity weights is modified. These weights represent the estimated number of unique daily users per building. Where detailed local data are available, weights are calculated directly; otherwise, Dutch building and occupancy standards or carefully selected proxy indicators are applied. This approach allows the model to remain operational across data-limited contexts while explicitly acknowledging uncertainty.
Building on the UNA framework, the model incorporates accessibility-adjusted activity weights. Each building is connected to the pedestrian network, and destination-specific Reach indices are calculated using a walking radius relevant to Dutch conditions. These indices adjust baseline activity weights to account for behavioural tendencies and destination attractiveness. Sensitivity analyses examine how assumptions regarding walking radius and normalisation methods influence model outcomes.
A major extension beyond the original UNA framework is the integration of temporal dynamics through hourly walking trip rates. Trip purposes derived from the Dutch ODiN travel survey are mapped to building types, and corresponding hourly origin–destination trip rates are applied. Combining these rates with accessibility-adjusted weights yields hourly, building-level pedestrian trip-generation estimates for the study area.
Model performance is assessed through face validation using observed pedestrian counts. Results show that the adapted model reproduces realistic spatial and temporal patterns for building types supported by reliable activity data, particularly housing and major train stations. Underprediction is observed for offices and leisure facilities, where activity weights rely on proxy indicators and where walking trips are likely underreported in ODiN. Sensitivity analyses confirm that trip-generation outcomes depend strongly on proxy selection and accessibility assumptions, revealing structural uncertainties.
Despite these limitations, the BPT-Gen model provides clear practical value. It identifies key generators of walking trips, peak periods, and accessibility-driven hotspots using only open data. By linking trip purposes to building types at hourly resolution, the framework fills an important gap in Dutch pedestrian modelling and offers a transparent foundation for future extensions. The findings demonstrate that open-data pedestrian models can provide meaningful planning insights while highlighting the need for improved activity indicators and further validation using street-level pedestrian flow data.
To address this gap, this study develops a building-level pedestrian trip-generation model with fine spatial and temporal resolution, tailored to Dutch conditions and relying exclusively on widely available open data. The central research question is: To what extent can an existing pedestrian trip-generation model be adapted to reflect pedestrian trip-generation dynamics in the Dutch urban context?
The study adapts Sevtsuk’s Urban Network Analysis (UNA) framework into a Dutch-specific, building-level model referred to as BPT-Gen (Building-level Pedestrian Trip Generation). The UNA framework was selected because it offers a practical balance between spatial detail and data requirements while remaining transparent and reproducible. Several key adaptations are introduced to ensure applicability to Dutch cities.
First, buildings are identified and classified using the Dutch BAG dataset, supplemented with OpenStreetMap (OSM) data to capture land use, amenities, and public transport facilities. This enables a detailed and consistent representation of pedestrian trip origins and destinations at the building level.
Second, the derivation of building activity weights is modified. These weights represent the estimated number of unique daily users per building. Where detailed local data are available, weights are calculated directly; otherwise, Dutch building and occupancy standards or carefully selected proxy indicators are applied. This approach allows the model to remain operational across data-limited contexts while explicitly acknowledging uncertainty.
Building on the UNA framework, the model incorporates accessibility-adjusted activity weights. Each building is connected to the pedestrian network, and destination-specific Reach indices are calculated using a walking radius relevant to Dutch conditions. These indices adjust baseline activity weights to account for behavioural tendencies and destination attractiveness. Sensitivity analyses examine how assumptions regarding walking radius and normalisation methods influence model outcomes.
A major extension beyond the original UNA framework is the integration of temporal dynamics through hourly walking trip rates. Trip purposes derived from the Dutch ODiN travel survey are mapped to building types, and corresponding hourly origin–destination trip rates are applied. Combining these rates with accessibility-adjusted weights yields hourly, building-level pedestrian trip-generation estimates for the study area.
Model performance is assessed through face validation using observed pedestrian counts. Results show that the adapted model reproduces realistic spatial and temporal patterns for building types supported by reliable activity data, particularly housing and major train stations. Underprediction is observed for offices and leisure facilities, where activity weights rely on proxy indicators and where walking trips are likely underreported in ODiN. Sensitivity analyses confirm that trip-generation outcomes depend strongly on proxy selection and accessibility assumptions, revealing structural uncertainties.
Despite these limitations, the BPT-Gen model provides clear practical value. It identifies key generators of walking trips, peak periods, and accessibility-driven hotspots using only open data. By linking trip purposes to building types at hourly resolution, the framework fills an important gap in Dutch pedestrian modelling and offers a transparent foundation for future extensions. The findings demonstrate that open-data pedestrian models can provide meaningful planning insights while highlighting the need for improved activity indicators and further validation using street-level pedestrian flow data.
With increasing awareness of the environmental impacts of motorized trans-port. low-carbon mobility modes such as cycling are gaining importance. This dissertation investigates bicycle traffic dynamics and develops data-driven spatial-temporal prediction models under varying environmental and operational conditions. The findings aim to support policymakers, mobility providers, and system developers in making more efficient and evidence-based decisions for bicycle transportation systems.
...
...
With increasing awareness of the environmental impacts of motorized trans-port. low-carbon mobility modes such as cycling are gaining importance. This dissertation investigates bicycle traffic dynamics and develops data-driven spatial-temporal prediction models under varying environmental and operational conditions. The findings aim to support policymakers, mobility providers, and system developers in making more efficient and evidence-based decisions for bicycle transportation systems.
The rapid increase of e-bike use in the Netherlands has intensified speed heterogeneity on cycling infrastructure. Although this trend contributes positively to sustainable mobility, it may negatively influence cyclists’ perceived safety, which in turn affects their route choices and willingness to cycle. Existing literature recognizes the role of infrastructural, environmental, traffic-related, and individual factors in shaping perceived safety, yet the specific influence of speed differences in bicycle-only environments remains insufficiently studied. This research investigates the extent to which speed heterogeneity affects perceived cycling safety and how this effect interacts with other contextual attributes. A video-based stated preference experiment was designed in which respondents evaluated overtaking events filmed in real urban locations, manipulated across lane design, lane width, cycling density, and speed differences. A panel Mixed Logit model was estimated, supplemented with scenario ranking tasks. Results show that greater speed differences consistently reduce perceived safety, especially under congested conditions. Two-way lanes are perceived as less safe than one-way lanes, though wider lanes mitigate this effect and experienced cyclists express higher comfort levels. Findings underline the importance of managing speed heterogeneity through infrastructural design and policy interventions, including multi-paced cycling lanes, speed awareness campaigns, and targeted safety reporting mechanisms. The study demonstrates the value of video-based stated preference methods for analyzing subjective safety and contributes to policy debates on designing cycling infrastructure for increasingly diverse urban cyclists.
...
The rapid increase of e-bike use in the Netherlands has intensified speed heterogeneity on cycling infrastructure. Although this trend contributes positively to sustainable mobility, it may negatively influence cyclists’ perceived safety, which in turn affects their route choices and willingness to cycle. Existing literature recognizes the role of infrastructural, environmental, traffic-related, and individual factors in shaping perceived safety, yet the specific influence of speed differences in bicycle-only environments remains insufficiently studied. This research investigates the extent to which speed heterogeneity affects perceived cycling safety and how this effect interacts with other contextual attributes. A video-based stated preference experiment was designed in which respondents evaluated overtaking events filmed in real urban locations, manipulated across lane design, lane width, cycling density, and speed differences. A panel Mixed Logit model was estimated, supplemented with scenario ranking tasks. Results show that greater speed differences consistently reduce perceived safety, especially under congested conditions. Two-way lanes are perceived as less safe than one-way lanes, though wider lanes mitigate this effect and experienced cyclists express higher comfort levels. Findings underline the importance of managing speed heterogeneity through infrastructural design and policy interventions, including multi-paced cycling lanes, speed awareness campaigns, and targeted safety reporting mechanisms. The study demonstrates the value of video-based stated preference methods for analyzing subjective safety and contributes to policy debates on designing cycling infrastructure for increasingly diverse urban cyclists.
Safer Together
How do Parents Assess Street Safety when Biking with their Children?
The Netherlands has experienced a decline in active school travel over the last decade. This is concerning, considering that active school travel is essential to support children’s health and independence. Parents’ perceived traffic safety is often linked to children’s mobility choices, but there is little knowledge on what factors inform parents’ perceived safety in a bike-oriented context. This research employed a combination of literature reviews and interviews with mental maps, to understand what factors influenced parents’ perceived traffic safety in a bike-oriented context, like the Netherlands. Overall, this research established a multitude of factors that informed parents’ perceived traffic safety. These factors included, but were not limited to, complex crossings, high speed, high traffic volume, type of bike path, type of crossing, and accidents along the route. This research also highlighted that children’s characteristics and parents’ approach to risk mitigated parents’ perception of traffic safety. The results further showed that parents’ perception of traffic safety did not solely depend on the factors found along the route, but also on the interplay between factors at any specific location. These findings largely overlapped with the literature, with some important additions, which can be attributed to the bike-oriented context and use of interviews in this study. A key supposition from the study was that parents focused on minimizing the uncertainty along their travel route to feel safe. Hence, they preferred routes where their expectations matched the resulting behavior and where infrastructure elements minimized the consequences of any mistakes their children made. The conclusions in this research should be reconfirmed with a larger sample.
...
The Netherlands has experienced a decline in active school travel over the last decade. This is concerning, considering that active school travel is essential to support children’s health and independence. Parents’ perceived traffic safety is often linked to children’s mobility choices, but there is little knowledge on what factors inform parents’ perceived safety in a bike-oriented context. This research employed a combination of literature reviews and interviews with mental maps, to understand what factors influenced parents’ perceived traffic safety in a bike-oriented context, like the Netherlands. Overall, this research established a multitude of factors that informed parents’ perceived traffic safety. These factors included, but were not limited to, complex crossings, high speed, high traffic volume, type of bike path, type of crossing, and accidents along the route. This research also highlighted that children’s characteristics and parents’ approach to risk mitigated parents’ perception of traffic safety. The results further showed that parents’ perception of traffic safety did not solely depend on the factors found along the route, but also on the interplay between factors at any specific location. These findings largely overlapped with the literature, with some important additions, which can be attributed to the bike-oriented context and use of interviews in this study. A key supposition from the study was that parents focused on minimizing the uncertainty along their travel route to feel safe. Hence, they preferred routes where their expectations matched the resulting behavior and where infrastructure elements minimized the consequences of any mistakes their children made. The conclusions in this research should be reconfirmed with a larger sample.
Cyclist route choice can lead to uncomfortable and dangerous situations. Therefore, it is important to research ways to influence this. This study explores how infrastructural nudging can be used to influence cyclist route choice. Using virtual reality and a bicycle simulator the impact of visual road hierarchy, visual obstruction and herding through street art is studied. A virtual urban environment was designed with 11 T-intersections. In 9 of the 11 intersection these methods were applied in three different ways, to see whether the nudge impacted cyclist route choice. The gathered data was then analysed with descriptive data analysis and discrete choice modelling. This study shows that cyclists follow nudges using visual road hierarchy and herding. However, they do not follow nudges with visual obstruction. This effect is the same for people of all ages, genders, heights etc. Though less experienced cyclists seem to react more heavily to obstruction methods. The results also indicate that cyclists have a significant right-handed tendency. This effect is not influenced by eye or hand dominance. The effect becomes slightly weaker when nudging is applied but does not go away. Future research should validate these results in a physical environment before this is used in practice.
...
Cyclist route choice can lead to uncomfortable and dangerous situations. Therefore, it is important to research ways to influence this. This study explores how infrastructural nudging can be used to influence cyclist route choice. Using virtual reality and a bicycle simulator the impact of visual road hierarchy, visual obstruction and herding through street art is studied. A virtual urban environment was designed with 11 T-intersections. In 9 of the 11 intersection these methods were applied in three different ways, to see whether the nudge impacted cyclist route choice. The gathered data was then analysed with descriptive data analysis and discrete choice modelling. This study shows that cyclists follow nudges using visual road hierarchy and herding. However, they do not follow nudges with visual obstruction. This effect is the same for people of all ages, genders, heights etc. Though less experienced cyclists seem to react more heavily to obstruction methods. The results also indicate that cyclists have a significant right-handed tendency. This effect is not influenced by eye or hand dominance. The effect becomes slightly weaker when nudging is applied but does not go away. Future research should validate these results in a physical environment before this is used in practice.
Examining the Societal Costs and Benefits of Integrating Bike Sharing Systems and Public Transport
A Case Study of the OV-fiets in the Netherlands
Integrating bike-sharing programs with public transport enhances car-independent mobility, yet a comprehensive societal cost-benefit analysis of this integration remains scarce. This study addresses this gap by conducting an ex-post analysis of the OV-fiets program in the Netherlands, a station-based round-trip bike-sharing system designed to improve last-mile connectivity for train commuters. Spanning from 2004 to 2023, the analysis identifies 19 critical factors through an exhaustive literature review and expert consultations, with 14 factors subsequently quantified and monetized. The findings reveal a positive net present value (NPV) for the OV-fiets scheme, with benefit-cost ratios (BCRs) ranging from 1.1:1 to 2.4:1 and a median ratio of 1.5:1. Primary benefits include enhanced accessibility, reduced road congestion, and improved health outcomes, while significant costs are associated with initial investments and road safety impacts. This research underscores the considerable societal value of the OV-fiets program, warranting continued investment in the program and emphasizing the need for ongoing safety measures and infrastructure improvements. Additionally, it provides a robust framework for future assessments and improvements in similar urban contexts.
...
Integrating bike-sharing programs with public transport enhances car-independent mobility, yet a comprehensive societal cost-benefit analysis of this integration remains scarce. This study addresses this gap by conducting an ex-post analysis of the OV-fiets program in the Netherlands, a station-based round-trip bike-sharing system designed to improve last-mile connectivity for train commuters. Spanning from 2004 to 2023, the analysis identifies 19 critical factors through an exhaustive literature review and expert consultations, with 14 factors subsequently quantified and monetized. The findings reveal a positive net present value (NPV) for the OV-fiets scheme, with benefit-cost ratios (BCRs) ranging from 1.1:1 to 2.4:1 and a median ratio of 1.5:1. Primary benefits include enhanced accessibility, reduced road congestion, and improved health outcomes, while significant costs are associated with initial investments and road safety impacts. This research underscores the considerable societal value of the OV-fiets program, warranting continued investment in the program and emphasizing the need for ongoing safety measures and infrastructure improvements. Additionally, it provides a robust framework for future assessments and improvements in similar urban contexts.
The car-centric transportation systems of cities nowadays induce many complications ranging from environmental impact, land-use inefficiency and personal health issues. The governmental bodies of numerous cities within the Netherlands started to envision car-free cities and want to promote the use of transport modes that improve the city’s liveability and reduce the environmental impact. Walking as a transport modality fits this description perfectly and a modal shift towards more trips on foot can be achieved through effective policies and investments. To support the implementation of effective policies and investments, practical tools are required that measure, monitor and forecast (changes in) the network scale pedestrian behaviour but these are currently not in existence. This research aims to overcome this gap by developing an urban network pedestrian flow model.
Several modelling frameworks for the measuring, monitoring and forecasting of motorized, and in some instances bicycle, traffic are already in existence and are broadly used in the practical field. The direct application of these frameworks to pedestrian traffic is, however, not possible due to the absence of the required input data at the proper (spatial) resolution or on pedestrians at all. Nevertheless, for several elements of these frameworks, the application to pedestrian traffic is possible given the data available and so a new framework could be developed that takes inspiration from the existing transport modelling frameworks.
The core of the developed modelling framework consists of an optimisation model in which local pedestrian counts are related to potential route flows over the network, or in other words, that derives the global route flows from observed segment flows for a subset of network segments. The creation of the potential routes is done beforehand in two distinct modelling steps: the OD-pair selection and the route set generation. In the first model step, a subset of the network graph nodes is selected to represent the origin and destination locations of walking trips. Next, for each combination of OD-pairs, several potential walking routes are generated. Here, the k-least-cost paths are computed with a weighted sum of several route and environmental attributes as the cost. Moreover, the optimisation model is extended by incorporating information on real pedestrian behaviour in Dutch urban contexts. Hereby, the model's optimal solution is ensured to represent these mobility patterns and hence improve the result’s validity by combining various data sources on pedestrian behaviour.
The modelling framework's performance was tested by applying a case study on the city centre district of The Hague, The Netherlands for the year 2019. The model returns a modest set of route flows, providing a flow over 22.06% of the network segments. In reality, however, more network segments have pedestrians traversing and the performance of a cross-validation experiment on the observed segment flow vector was poor. This indicates that the developed modelling framework does not model pedestrian flow accurately and improvements to the framework and input data are necessary.
Although the developed framework showed not to be ready for practical applications, this study did provide a good starting point for the development of a practical tool for modelling pedestrian flows and steps for further improvement of the model could be derived. For instance, the model can advance from introducing the logit formula for the distribution of OD-flows over routes, improving the route set, and incorporating pedestrian link counts as sequential data sets. Additionally, the pedestrian count data can improve in quality through a better network coverage of the observation locations, or by measuring the directionality of the passers-by and on a higher temporal resolution. ...
Several modelling frameworks for the measuring, monitoring and forecasting of motorized, and in some instances bicycle, traffic are already in existence and are broadly used in the practical field. The direct application of these frameworks to pedestrian traffic is, however, not possible due to the absence of the required input data at the proper (spatial) resolution or on pedestrians at all. Nevertheless, for several elements of these frameworks, the application to pedestrian traffic is possible given the data available and so a new framework could be developed that takes inspiration from the existing transport modelling frameworks.
The core of the developed modelling framework consists of an optimisation model in which local pedestrian counts are related to potential route flows over the network, or in other words, that derives the global route flows from observed segment flows for a subset of network segments. The creation of the potential routes is done beforehand in two distinct modelling steps: the OD-pair selection and the route set generation. In the first model step, a subset of the network graph nodes is selected to represent the origin and destination locations of walking trips. Next, for each combination of OD-pairs, several potential walking routes are generated. Here, the k-least-cost paths are computed with a weighted sum of several route and environmental attributes as the cost. Moreover, the optimisation model is extended by incorporating information on real pedestrian behaviour in Dutch urban contexts. Hereby, the model's optimal solution is ensured to represent these mobility patterns and hence improve the result’s validity by combining various data sources on pedestrian behaviour.
The modelling framework's performance was tested by applying a case study on the city centre district of The Hague, The Netherlands for the year 2019. The model returns a modest set of route flows, providing a flow over 22.06% of the network segments. In reality, however, more network segments have pedestrians traversing and the performance of a cross-validation experiment on the observed segment flow vector was poor. This indicates that the developed modelling framework does not model pedestrian flow accurately and improvements to the framework and input data are necessary.
Although the developed framework showed not to be ready for practical applications, this study did provide a good starting point for the development of a practical tool for modelling pedestrian flows and steps for further improvement of the model could be derived. For instance, the model can advance from introducing the logit formula for the distribution of OD-flows over routes, improving the route set, and incorporating pedestrian link counts as sequential data sets. Additionally, the pedestrian count data can improve in quality through a better network coverage of the observation locations, or by measuring the directionality of the passers-by and on a higher temporal resolution. ...
The car-centric transportation systems of cities nowadays induce many complications ranging from environmental impact, land-use inefficiency and personal health issues. The governmental bodies of numerous cities within the Netherlands started to envision car-free cities and want to promote the use of transport modes that improve the city’s liveability and reduce the environmental impact. Walking as a transport modality fits this description perfectly and a modal shift towards more trips on foot can be achieved through effective policies and investments. To support the implementation of effective policies and investments, practical tools are required that measure, monitor and forecast (changes in) the network scale pedestrian behaviour but these are currently not in existence. This research aims to overcome this gap by developing an urban network pedestrian flow model.
Several modelling frameworks for the measuring, monitoring and forecasting of motorized, and in some instances bicycle, traffic are already in existence and are broadly used in the practical field. The direct application of these frameworks to pedestrian traffic is, however, not possible due to the absence of the required input data at the proper (spatial) resolution or on pedestrians at all. Nevertheless, for several elements of these frameworks, the application to pedestrian traffic is possible given the data available and so a new framework could be developed that takes inspiration from the existing transport modelling frameworks.
The core of the developed modelling framework consists of an optimisation model in which local pedestrian counts are related to potential route flows over the network, or in other words, that derives the global route flows from observed segment flows for a subset of network segments. The creation of the potential routes is done beforehand in two distinct modelling steps: the OD-pair selection and the route set generation. In the first model step, a subset of the network graph nodes is selected to represent the origin and destination locations of walking trips. Next, for each combination of OD-pairs, several potential walking routes are generated. Here, the k-least-cost paths are computed with a weighted sum of several route and environmental attributes as the cost. Moreover, the optimisation model is extended by incorporating information on real pedestrian behaviour in Dutch urban contexts. Hereby, the model's optimal solution is ensured to represent these mobility patterns and hence improve the result’s validity by combining various data sources on pedestrian behaviour.
The modelling framework's performance was tested by applying a case study on the city centre district of The Hague, The Netherlands for the year 2019. The model returns a modest set of route flows, providing a flow over 22.06% of the network segments. In reality, however, more network segments have pedestrians traversing and the performance of a cross-validation experiment on the observed segment flow vector was poor. This indicates that the developed modelling framework does not model pedestrian flow accurately and improvements to the framework and input data are necessary.
Although the developed framework showed not to be ready for practical applications, this study did provide a good starting point for the development of a practical tool for modelling pedestrian flows and steps for further improvement of the model could be derived. For instance, the model can advance from introducing the logit formula for the distribution of OD-flows over routes, improving the route set, and incorporating pedestrian link counts as sequential data sets. Additionally, the pedestrian count data can improve in quality through a better network coverage of the observation locations, or by measuring the directionality of the passers-by and on a higher temporal resolution.
Several modelling frameworks for the measuring, monitoring and forecasting of motorized, and in some instances bicycle, traffic are already in existence and are broadly used in the practical field. The direct application of these frameworks to pedestrian traffic is, however, not possible due to the absence of the required input data at the proper (spatial) resolution or on pedestrians at all. Nevertheless, for several elements of these frameworks, the application to pedestrian traffic is possible given the data available and so a new framework could be developed that takes inspiration from the existing transport modelling frameworks.
The core of the developed modelling framework consists of an optimisation model in which local pedestrian counts are related to potential route flows over the network, or in other words, that derives the global route flows from observed segment flows for a subset of network segments. The creation of the potential routes is done beforehand in two distinct modelling steps: the OD-pair selection and the route set generation. In the first model step, a subset of the network graph nodes is selected to represent the origin and destination locations of walking trips. Next, for each combination of OD-pairs, several potential walking routes are generated. Here, the k-least-cost paths are computed with a weighted sum of several route and environmental attributes as the cost. Moreover, the optimisation model is extended by incorporating information on real pedestrian behaviour in Dutch urban contexts. Hereby, the model's optimal solution is ensured to represent these mobility patterns and hence improve the result’s validity by combining various data sources on pedestrian behaviour.
The modelling framework's performance was tested by applying a case study on the city centre district of The Hague, The Netherlands for the year 2019. The model returns a modest set of route flows, providing a flow over 22.06% of the network segments. In reality, however, more network segments have pedestrians traversing and the performance of a cross-validation experiment on the observed segment flow vector was poor. This indicates that the developed modelling framework does not model pedestrian flow accurately and improvements to the framework and input data are necessary.
Although the developed framework showed not to be ready for practical applications, this study did provide a good starting point for the development of a practical tool for modelling pedestrian flows and steps for further improvement of the model could be derived. For instance, the model can advance from introducing the logit formula for the distribution of OD-flows over routes, improving the route set, and incorporating pedestrian link counts as sequential data sets. Additionally, the pedestrian count data can improve in quality through a better network coverage of the observation locations, or by measuring the directionality of the passers-by and on a higher temporal resolution.
Exploring bicycle parking potential near public transport stops
A case study in The Hague
Urban areas such as The Hague face traffic congestion and environmental issues due to frequent car usage, especially for short trips up to 5 kilometres. To address these challenges, combining cycling with public transportation (PT) offers a promising alternative. This study examines the potential of bicycle parking facilities at public transport stops in The Hague, aiming to encourage multimodal travel and discourage short car trips.
The qualitative part of the research involved structured interviews with residents of The Hague. The results showed that people are open to considering the bicycle-PT combination but have not yet adopted it. The main barriers are the lack of safe, accessible, and well-maintained bicycle parking at public transport stops. Respondents emphasized the need for more bike parking and cited bad weather and convenience as common reasons for choosing the car.
The quantitative analysis, based on a stated preference survey and a multinomial logit model, confirmed the interview findings. Residents are more likely to opt for the bicycle-PT combination if certain bicycle parking facilities, such as bike racks or lockers, are available. These specific facilities could shift up to 2 percentage points of trips toward the bicycle-PT combination and reduce short car trips by up to 3 percentage points.
Additionally, the results indicate that cost and travel time are important factors in transport choice. Increasing car-related costs and reducing public transport fares were tested and could further contribute to a modal shift from car to bicycle-PT. Tested scenarios showed a potential increase of up to 5 percentage points in bike-transit usage and a reduction of up to 6.5 percentage points in car trips.
Based on these findings, it is recommended to invest in user-friendly and more abundant bicycle parking at transit stops, particularly bike racks, which are cost- and space-efficient. Policymakers are also advised to explore pricing policies that make public transport more financially attractive compared to car use.
These findings are not only relevant for The Hague but also offer insights for similar cities striving to create a more sustainable mobility system by better integrating cycling with public transport. ...
The qualitative part of the research involved structured interviews with residents of The Hague. The results showed that people are open to considering the bicycle-PT combination but have not yet adopted it. The main barriers are the lack of safe, accessible, and well-maintained bicycle parking at public transport stops. Respondents emphasized the need for more bike parking and cited bad weather and convenience as common reasons for choosing the car.
The quantitative analysis, based on a stated preference survey and a multinomial logit model, confirmed the interview findings. Residents are more likely to opt for the bicycle-PT combination if certain bicycle parking facilities, such as bike racks or lockers, are available. These specific facilities could shift up to 2 percentage points of trips toward the bicycle-PT combination and reduce short car trips by up to 3 percentage points.
Additionally, the results indicate that cost and travel time are important factors in transport choice. Increasing car-related costs and reducing public transport fares were tested and could further contribute to a modal shift from car to bicycle-PT. Tested scenarios showed a potential increase of up to 5 percentage points in bike-transit usage and a reduction of up to 6.5 percentage points in car trips.
Based on these findings, it is recommended to invest in user-friendly and more abundant bicycle parking at transit stops, particularly bike racks, which are cost- and space-efficient. Policymakers are also advised to explore pricing policies that make public transport more financially attractive compared to car use.
These findings are not only relevant for The Hague but also offer insights for similar cities striving to create a more sustainable mobility system by better integrating cycling with public transport. ...
Urban areas such as The Hague face traffic congestion and environmental issues due to frequent car usage, especially for short trips up to 5 kilometres. To address these challenges, combining cycling with public transportation (PT) offers a promising alternative. This study examines the potential of bicycle parking facilities at public transport stops in The Hague, aiming to encourage multimodal travel and discourage short car trips.
The qualitative part of the research involved structured interviews with residents of The Hague. The results showed that people are open to considering the bicycle-PT combination but have not yet adopted it. The main barriers are the lack of safe, accessible, and well-maintained bicycle parking at public transport stops. Respondents emphasized the need for more bike parking and cited bad weather and convenience as common reasons for choosing the car.
The quantitative analysis, based on a stated preference survey and a multinomial logit model, confirmed the interview findings. Residents are more likely to opt for the bicycle-PT combination if certain bicycle parking facilities, such as bike racks or lockers, are available. These specific facilities could shift up to 2 percentage points of trips toward the bicycle-PT combination and reduce short car trips by up to 3 percentage points.
Additionally, the results indicate that cost and travel time are important factors in transport choice. Increasing car-related costs and reducing public transport fares were tested and could further contribute to a modal shift from car to bicycle-PT. Tested scenarios showed a potential increase of up to 5 percentage points in bike-transit usage and a reduction of up to 6.5 percentage points in car trips.
Based on these findings, it is recommended to invest in user-friendly and more abundant bicycle parking at transit stops, particularly bike racks, which are cost- and space-efficient. Policymakers are also advised to explore pricing policies that make public transport more financially attractive compared to car use.
These findings are not only relevant for The Hague but also offer insights for similar cities striving to create a more sustainable mobility system by better integrating cycling with public transport.
The qualitative part of the research involved structured interviews with residents of The Hague. The results showed that people are open to considering the bicycle-PT combination but have not yet adopted it. The main barriers are the lack of safe, accessible, and well-maintained bicycle parking at public transport stops. Respondents emphasized the need for more bike parking and cited bad weather and convenience as common reasons for choosing the car.
The quantitative analysis, based on a stated preference survey and a multinomial logit model, confirmed the interview findings. Residents are more likely to opt for the bicycle-PT combination if certain bicycle parking facilities, such as bike racks or lockers, are available. These specific facilities could shift up to 2 percentage points of trips toward the bicycle-PT combination and reduce short car trips by up to 3 percentage points.
Additionally, the results indicate that cost and travel time are important factors in transport choice. Increasing car-related costs and reducing public transport fares were tested and could further contribute to a modal shift from car to bicycle-PT. Tested scenarios showed a potential increase of up to 5 percentage points in bike-transit usage and a reduction of up to 6.5 percentage points in car trips.
Based on these findings, it is recommended to invest in user-friendly and more abundant bicycle parking at transit stops, particularly bike racks, which are cost- and space-efficient. Policymakers are also advised to explore pricing policies that make public transport more financially attractive compared to car use.
These findings are not only relevant for The Hague but also offer insights for similar cities striving to create a more sustainable mobility system by better integrating cycling with public transport.
Preferences of visitors of mass events towards travel information messages
Identifying visitor profiles using Latent Class Cluster Analysis
During the influx to mass events in the past, situations have regularly arisen that people experienced as unpleasant or even unsafe. Nowadays, many researchers focus on regulating this influx by influencing travel choices, where only little attention is paid to travellers’ preferences. This research identifies the preferences of different type of visitors towards receiving information, and the extent to which visitors with different information profiles act on the information messages they receive. A survey was distributed (N=378), and the number of variables was reduced by performing an Exploratory Factor Analysis. The Latent Class Cluster Analysis distinguished three clusters based on their information message preferences. The results show that people are most interested in receiving information via email a few days before departure and that it is challenging to inform them at a later time. The most impressionable cluster mainly consists of young people, unfamiliar with the event area. Event organisations can apply the results by better-aligning communication with the preferences of their visitors. The differences in behavioural intentions between the clusters turned out to be limited. This must be further investigated since it is not in line with expectations.
...
During the influx to mass events in the past, situations have regularly arisen that people experienced as unpleasant or even unsafe. Nowadays, many researchers focus on regulating this influx by influencing travel choices, where only little attention is paid to travellers’ preferences. This research identifies the preferences of different type of visitors towards receiving information, and the extent to which visitors with different information profiles act on the information messages they receive. A survey was distributed (N=378), and the number of variables was reduced by performing an Exploratory Factor Analysis. The Latent Class Cluster Analysis distinguished three clusters based on their information message preferences. The results show that people are most interested in receiving information via email a few days before departure and that it is challenging to inform them at a later time. The most impressionable cluster mainly consists of young people, unfamiliar with the event area. Event organisations can apply the results by better-aligning communication with the preferences of their visitors. The differences in behavioural intentions between the clusters turned out to be limited. This must be further investigated since it is not in line with expectations.
Shared Micromobility, Shared by Everyone?
A Qualitative Study of Non-Users' Perspectives to Explore The Challenges of Achieving Inclusivity in Shared Micromobility Systems
Impact of leader-follower behavior on evacuation performance
An exploratory modeling approach
Different leader-follower behavior may be observed in models, such as group gathering, backtracking, and flexibility of the group. However, a comparison of these behaviors resulting in possible substantially different estimates of optimal evacuation procedures is lacking. Hence, we developed an Agent-based model in combination with exploratory modeling to compare backtracking, group gathering, and the possibility to change to another leader and investigate their influence on the evacuation and response time to receive a robust result. The results showed that backtracking and flexibility of the group increased the evacuation time. Whereby group gathering impacts the response time. In addition, the combination of behaviors increases the influence on evacuation and response time. Further research needs to test these results with empirical studies. Furthermore, the impact of other leader-follower behavior needs to be investigated.
...
Different leader-follower behavior may be observed in models, such as group gathering, backtracking, and flexibility of the group. However, a comparison of these behaviors resulting in possible substantially different estimates of optimal evacuation procedures is lacking. Hence, we developed an Agent-based model in combination with exploratory modeling to compare backtracking, group gathering, and the possibility to change to another leader and investigate their influence on the evacuation and response time to receive a robust result. The results showed that backtracking and flexibility of the group increased the evacuation time. Whereby group gathering impacts the response time. In addition, the combination of behaviors increases the influence on evacuation and response time. Further research needs to test these results with empirical studies. Furthermore, the impact of other leader-follower behavior needs to be investigated.
Ecology in Urban Development
The potential of systems thinking to make ecology a more prominent concept in urban development
Changes to ecosystems due to human activity have occurred more quickly in the previous 65 years than at any other period in history, this has resulted in an irreversible loss in biodiversity worldwide. A direct consequence is a decrease in ecosystem services - the benefits for humans that are provided by ecology - which are needed to keep especially cities liveable places. It is therefore crucial that cities are going to be developed more sustainably. Several theories acknowledge that for sustainable urban development, a shift is needed from a fragmented approach to a systematic approach to development. Therefore, this thesis has studied the potential of systems thinking to make ecology more important in the process of urban development. This has been done through document analysis and semi-structured interviews, which clarified how ecology is approached in the current process. It emphasized the current socio-technical landscape we are in, where ecology is still something that is controlled by humans and where urban ecology is not acknowledged as a distinct urban system. The interviews have been used to indicate the challenges and opportunities for systems thinking to change this landscape. This has formed the foundation of preliminary recommendations that have been validated through a workshop. Challenges like other interests, soft concept and no value can be overcome by various niche developments, tools that help in quantifying or monetising ecology so a value can be created that is interesting for developers, or help can be given to municipalities to set requirements on ecology. Using these tools, the context and its systems should always be considered for ecology not to be reduced to technical features, and no optimal ecological change can be created. Tools should also be used in a pre-initiative phase, where core challenges in an area, main drivers of developers and common goals of stakeholders can be established. Involving a wide range of stakeholders influences people to think more broadly and deeply about themes. Especially involving ecologists and maintenance departments in the design phase can create flexible designs that are future-proof and implemented successfully. Besides, ecologists, who know how to use language and create more chances in ecology instead of burdens and relate ecology to other themes, should be involved throughout the different phases of urban development as they often can make it more interesting for other disciplines. This eventually benefits the desired transition towards a landscape where the paradigm around urban ecology is entirely accepted, which results in the perception of ecology as something that is equal to humans and is therefore always on an equal level or even more important as the social and economic system ultimately benefitting the loss of biodiversity.
...
Changes to ecosystems due to human activity have occurred more quickly in the previous 65 years than at any other period in history, this has resulted in an irreversible loss in biodiversity worldwide. A direct consequence is a decrease in ecosystem services - the benefits for humans that are provided by ecology - which are needed to keep especially cities liveable places. It is therefore crucial that cities are going to be developed more sustainably. Several theories acknowledge that for sustainable urban development, a shift is needed from a fragmented approach to a systematic approach to development. Therefore, this thesis has studied the potential of systems thinking to make ecology more important in the process of urban development. This has been done through document analysis and semi-structured interviews, which clarified how ecology is approached in the current process. It emphasized the current socio-technical landscape we are in, where ecology is still something that is controlled by humans and where urban ecology is not acknowledged as a distinct urban system. The interviews have been used to indicate the challenges and opportunities for systems thinking to change this landscape. This has formed the foundation of preliminary recommendations that have been validated through a workshop. Challenges like other interests, soft concept and no value can be overcome by various niche developments, tools that help in quantifying or monetising ecology so a value can be created that is interesting for developers, or help can be given to municipalities to set requirements on ecology. Using these tools, the context and its systems should always be considered for ecology not to be reduced to technical features, and no optimal ecological change can be created. Tools should also be used in a pre-initiative phase, where core challenges in an area, main drivers of developers and common goals of stakeholders can be established. Involving a wide range of stakeholders influences people to think more broadly and deeply about themes. Especially involving ecologists and maintenance departments in the design phase can create flexible designs that are future-proof and implemented successfully. Besides, ecologists, who know how to use language and create more chances in ecology instead of burdens and relate ecology to other themes, should be involved throughout the different phases of urban development as they often can make it more interesting for other disciplines. This eventually benefits the desired transition towards a landscape where the paradigm around urban ecology is entirely accepted, which results in the perception of ecology as something that is equal to humans and is therefore always on an equal level or even more important as the social and economic system ultimately benefitting the loss of biodiversity.
The search for cycling routes
Analysing the influence of spatial characteristics on cycling route choices in Amsterdam
In recent years, cycling has attracted increasing attention as a sustainable alternative to private car use. In cities across the world, strategies are put in place to improve existing cycling infrastructure. This raises the question of how cyclists move through a city and what part of the road network attracts the most cyclists. Prior studies on cycling behaviour have revealed that cyclists prefer routes that require less turns, over separated bicycle paths, smoother street surface materials like asphalt or concrete. Furthermore, dense and mixed-use neighbourhoods seem to attract more active travel. This research will analyse correlations between spatial characteristics and cycling route choices in Amsterdam.
Space Syntax is an analysis method that studies the urban morphology of a city. Until recently, the implementation of Space Syntax has mainly focused on the analysis of pedestrian flows, with a limited number of studies applying the methodology to cyclist behaviour. This master thesis presents exploratory research into the application of Space Syntax – in combination with other built environment characteristics – to study cyclist route choice. GPS data from the 2016 Bicycle Counting Week shows the cycling counts of every street segment.
A linear regression analysis found that “through-movement potential” represented by Normalised Angular Choice (NACH) explained more than 22% of variance in cycling activity. The results indicate that Space Syntax is an interesting indicator to locate which street segments could potentially see large numbers of cyclists. More research encompassing multiple cities in a variety of different contexts is recommended, as Amsterdam is a city with a rich cycling culture that spans multiple decades, making it difficult to generalize any conclusions.
...
Space Syntax is an analysis method that studies the urban morphology of a city. Until recently, the implementation of Space Syntax has mainly focused on the analysis of pedestrian flows, with a limited number of studies applying the methodology to cyclist behaviour. This master thesis presents exploratory research into the application of Space Syntax – in combination with other built environment characteristics – to study cyclist route choice. GPS data from the 2016 Bicycle Counting Week shows the cycling counts of every street segment.
A linear regression analysis found that “through-movement potential” represented by Normalised Angular Choice (NACH) explained more than 22% of variance in cycling activity. The results indicate that Space Syntax is an interesting indicator to locate which street segments could potentially see large numbers of cyclists. More research encompassing multiple cities in a variety of different contexts is recommended, as Amsterdam is a city with a rich cycling culture that spans multiple decades, making it difficult to generalize any conclusions.
...
In recent years, cycling has attracted increasing attention as a sustainable alternative to private car use. In cities across the world, strategies are put in place to improve existing cycling infrastructure. This raises the question of how cyclists move through a city and what part of the road network attracts the most cyclists. Prior studies on cycling behaviour have revealed that cyclists prefer routes that require less turns, over separated bicycle paths, smoother street surface materials like asphalt or concrete. Furthermore, dense and mixed-use neighbourhoods seem to attract more active travel. This research will analyse correlations between spatial characteristics and cycling route choices in Amsterdam.
Space Syntax is an analysis method that studies the urban morphology of a city. Until recently, the implementation of Space Syntax has mainly focused on the analysis of pedestrian flows, with a limited number of studies applying the methodology to cyclist behaviour. This master thesis presents exploratory research into the application of Space Syntax – in combination with other built environment characteristics – to study cyclist route choice. GPS data from the 2016 Bicycle Counting Week shows the cycling counts of every street segment.
A linear regression analysis found that “through-movement potential” represented by Normalised Angular Choice (NACH) explained more than 22% of variance in cycling activity. The results indicate that Space Syntax is an interesting indicator to locate which street segments could potentially see large numbers of cyclists. More research encompassing multiple cities in a variety of different contexts is recommended, as Amsterdam is a city with a rich cycling culture that spans multiple decades, making it difficult to generalize any conclusions.
Space Syntax is an analysis method that studies the urban morphology of a city. Until recently, the implementation of Space Syntax has mainly focused on the analysis of pedestrian flows, with a limited number of studies applying the methodology to cyclist behaviour. This master thesis presents exploratory research into the application of Space Syntax – in combination with other built environment characteristics – to study cyclist route choice. GPS data from the 2016 Bicycle Counting Week shows the cycling counts of every street segment.
A linear regression analysis found that “through-movement potential” represented by Normalised Angular Choice (NACH) explained more than 22% of variance in cycling activity. The results indicate that Space Syntax is an interesting indicator to locate which street segments could potentially see large numbers of cyclists. More research encompassing multiple cities in a variety of different contexts is recommended, as Amsterdam is a city with a rich cycling culture that spans multiple decades, making it difficult to generalize any conclusions.
Master thesis
(2022)
-
Roberto Villena Gonzales, W. Daamen, D.C. Duives, S.C. Calvert, Nienke Valkhoff
The COVID-19 pandemic has changed people's lives in greater or lesser degree since the outbreak back in December 2019 in Wuhan, China. Due to the high transmissibility of the virus and with the aim of preventing the virus from continue spreading, several measures have been applied during the last two years, which now have become part of people's daily life. One of these measures is physical distancing, which has been proven to be an effective way to reduce the transmission risk. The objective of this research is to understand how the walking behaviour of pedestrians has changed during COVID-19 because of physical distancing at bidirectional flows in locations where people might encounter difficulties for complying with this measure, and conduct a calibration of the pedestrian simulation model Pedestrian Dynamics (PD) to improve its accuracy for reproducing such behaviour. As a result, this research aims at determining the capability of the model to reproduce the walking behaviour during the pandemic. The results show that the walking behaviour has changed over the course of the pandemic, since in 2020 and 2021 pedestrians kept respectively larger and shorter distances than in 2019. Moreover, a larger variability in velocity and higher effort to traverse the measurement area suggest changes in the awareness of their surroundings during the pandemic. The calibration results show that the relaxation time is the most relevant parameter as the accuracy of the model significantly changes when values lower than its default are used, which in turn indicates a faster reaction of pedestrians. In conclusion, a calibrated model considering one parameter would not yield accurate predictions if a general usage for all COVID-19 scenarios is intended. Finally, different types of behaviour are recommended to be analysed to obtain insight into the capability of the model to reproduce them and moreover, the behavioural assessment at strategic and tactical level are adviced, since this research focused on the impact of physical distancing on the behaviour at operational level.
...
The COVID-19 pandemic has changed people's lives in greater or lesser degree since the outbreak back in December 2019 in Wuhan, China. Due to the high transmissibility of the virus and with the aim of preventing the virus from continue spreading, several measures have been applied during the last two years, which now have become part of people's daily life. One of these measures is physical distancing, which has been proven to be an effective way to reduce the transmission risk. The objective of this research is to understand how the walking behaviour of pedestrians has changed during COVID-19 because of physical distancing at bidirectional flows in locations where people might encounter difficulties for complying with this measure, and conduct a calibration of the pedestrian simulation model Pedestrian Dynamics (PD) to improve its accuracy for reproducing such behaviour. As a result, this research aims at determining the capability of the model to reproduce the walking behaviour during the pandemic. The results show that the walking behaviour has changed over the course of the pandemic, since in 2020 and 2021 pedestrians kept respectively larger and shorter distances than in 2019. Moreover, a larger variability in velocity and higher effort to traverse the measurement area suggest changes in the awareness of their surroundings during the pandemic. The calibration results show that the relaxation time is the most relevant parameter as the accuracy of the model significantly changes when values lower than its default are used, which in turn indicates a faster reaction of pedestrians. In conclusion, a calibrated model considering one parameter would not yield accurate predictions if a general usage for all COVID-19 scenarios is intended. Finally, different types of behaviour are recommended to be analysed to obtain insight into the capability of the model to reproduce them and moreover, the behavioural assessment at strategic and tactical level are adviced, since this research focused on the impact of physical distancing on the behaviour at operational level.
Master thesis
(2022)
-
J.K. Krom, D.C. Duives, W. Daamen, J.A. Annema, Elise Zuurbier, Laurens Versluis
This study has investigated the effect of the urban environment on pedestrian route choice behaviour, for walking routes to and from train stations in the Netherlands. To the best knowledge of the author, this is the first pedestrian route choice study which is performed at country-level scope. This was made possible by applying an innovative quasi-revealed preference approach. Respondents self-reported their route preferences through an online GIS survey. Outputs were subsequently analysed by overlaying route data with a range of open geodata sources and searching for statistical similarities between certain urban features and (in)frequently taken routes. Results from statistical testing are verified by testing these against a qualitative text-coding analysis. The study finds that pedestrians in the Netherlands have a strong preference for the route which they perceive to be fastest, especially when they are en-route to a train station. Pedestrians dislike features which they perceive as ’slowing’ them down such as traffic lights. Detours are found somewhat more often on from-station routes, with such detours leading via environments which are attractive for social reseasons such as shops or busy streets. The method was found to work fairly well and should now be tested on a larger population sample with more variables.
...
This study has investigated the effect of the urban environment on pedestrian route choice behaviour, for walking routes to and from train stations in the Netherlands. To the best knowledge of the author, this is the first pedestrian route choice study which is performed at country-level scope. This was made possible by applying an innovative quasi-revealed preference approach. Respondents self-reported their route preferences through an online GIS survey. Outputs were subsequently analysed by overlaying route data with a range of open geodata sources and searching for statistical similarities between certain urban features and (in)frequently taken routes. Results from statistical testing are verified by testing these against a qualitative text-coding analysis. The study finds that pedestrians in the Netherlands have a strong preference for the route which they perceive to be fastest, especially when they are en-route to a train station. Pedestrians dislike features which they perceive as ’slowing’ them down such as traffic lights. Detours are found somewhat more often on from-station routes, with such detours leading via environments which are attractive for social reseasons such as shops or busy streets. The method was found to work fairly well and should now be tested on a larger population sample with more variables.
The COVID-19 global pandemic has a great negative influence on the event industry. Decreasing number of festivals poses threats to cultural and economical development. This research aims to close this research gap by developing a SARS-CoV-2 transmission risk analysis method for large events by modelling crowd interactions at different types of event spaces and quantifying the SARS-CoV-2 transmission risks in the process. A method is proposed to connect activity scheduling, pedestrian route choice and movement modeling, virus spread modeling, and infection risk identification to determine the transmission risks throughout the events by probability method.
A case study applies the proposed method in a pre-pandemic music festival and shows its capability of revealing the general infection risk and the relation of influence factors to the transmission scale, and it also identifies risk-prone areas in an event. Comparing the different scenarios at each activity space, the general trend is identified that the transmission of SARS-CoV-2 is limited when the facility is located outdoor, the queue distance is increased, the density is lowered, and the respiratory activities are calmer. Compared to the real-life experimental events, the simulated results tend to be underestimating the risks due to assumptions of the event scale, infrastructure, compliance to measures, heterogeneity in the emission rate, activity schedules, group behavior, number of infectious individuals, and such factors that directly influence the amount of virus transmitted in the event. Nevertheless, this research has shown when and where major risks can occur during an event. It also gives indications on crowd management measures and interventions that can help reduce the virus transmission scale.
The proposed method allows future exploration and comparison of the transmission scales of large events, without posing ethical controversy of exposing people in infection risks. Yet, it has its limitations of not considering group behavior at the event, which is commonly observed at large events and may potentially increase the transmission scale. Another major limitation is its heavy dependency on detailed virus transmission parameters and activity patterns. The former needs to be validated under different scenarios, and the latter needs to be identified from the data collected at the same type of event in future research. ...
A case study applies the proposed method in a pre-pandemic music festival and shows its capability of revealing the general infection risk and the relation of influence factors to the transmission scale, and it also identifies risk-prone areas in an event. Comparing the different scenarios at each activity space, the general trend is identified that the transmission of SARS-CoV-2 is limited when the facility is located outdoor, the queue distance is increased, the density is lowered, and the respiratory activities are calmer. Compared to the real-life experimental events, the simulated results tend to be underestimating the risks due to assumptions of the event scale, infrastructure, compliance to measures, heterogeneity in the emission rate, activity schedules, group behavior, number of infectious individuals, and such factors that directly influence the amount of virus transmitted in the event. Nevertheless, this research has shown when and where major risks can occur during an event. It also gives indications on crowd management measures and interventions that can help reduce the virus transmission scale.
The proposed method allows future exploration and comparison of the transmission scales of large events, without posing ethical controversy of exposing people in infection risks. Yet, it has its limitations of not considering group behavior at the event, which is commonly observed at large events and may potentially increase the transmission scale. Another major limitation is its heavy dependency on detailed virus transmission parameters and activity patterns. The former needs to be validated under different scenarios, and the latter needs to be identified from the data collected at the same type of event in future research. ...
The COVID-19 global pandemic has a great negative influence on the event industry. Decreasing number of festivals poses threats to cultural and economical development. This research aims to close this research gap by developing a SARS-CoV-2 transmission risk analysis method for large events by modelling crowd interactions at different types of event spaces and quantifying the SARS-CoV-2 transmission risks in the process. A method is proposed to connect activity scheduling, pedestrian route choice and movement modeling, virus spread modeling, and infection risk identification to determine the transmission risks throughout the events by probability method.
A case study applies the proposed method in a pre-pandemic music festival and shows its capability of revealing the general infection risk and the relation of influence factors to the transmission scale, and it also identifies risk-prone areas in an event. Comparing the different scenarios at each activity space, the general trend is identified that the transmission of SARS-CoV-2 is limited when the facility is located outdoor, the queue distance is increased, the density is lowered, and the respiratory activities are calmer. Compared to the real-life experimental events, the simulated results tend to be underestimating the risks due to assumptions of the event scale, infrastructure, compliance to measures, heterogeneity in the emission rate, activity schedules, group behavior, number of infectious individuals, and such factors that directly influence the amount of virus transmitted in the event. Nevertheless, this research has shown when and where major risks can occur during an event. It also gives indications on crowd management measures and interventions that can help reduce the virus transmission scale.
The proposed method allows future exploration and comparison of the transmission scales of large events, without posing ethical controversy of exposing people in infection risks. Yet, it has its limitations of not considering group behavior at the event, which is commonly observed at large events and may potentially increase the transmission scale. Another major limitation is its heavy dependency on detailed virus transmission parameters and activity patterns. The former needs to be validated under different scenarios, and the latter needs to be identified from the data collected at the same type of event in future research.
A case study applies the proposed method in a pre-pandemic music festival and shows its capability of revealing the general infection risk and the relation of influence factors to the transmission scale, and it also identifies risk-prone areas in an event. Comparing the different scenarios at each activity space, the general trend is identified that the transmission of SARS-CoV-2 is limited when the facility is located outdoor, the queue distance is increased, the density is lowered, and the respiratory activities are calmer. Compared to the real-life experimental events, the simulated results tend to be underestimating the risks due to assumptions of the event scale, infrastructure, compliance to measures, heterogeneity in the emission rate, activity schedules, group behavior, number of infectious individuals, and such factors that directly influence the amount of virus transmitted in the event. Nevertheless, this research has shown when and where major risks can occur during an event. It also gives indications on crowd management measures and interventions that can help reduce the virus transmission scale.
The proposed method allows future exploration and comparison of the transmission scales of large events, without posing ethical controversy of exposing people in infection risks. Yet, it has its limitations of not considering group behavior at the event, which is commonly observed at large events and may potentially increase the transmission scale. Another major limitation is its heavy dependency on detailed virus transmission parameters and activity patterns. The former needs to be validated under different scenarios, and the latter needs to be identified from the data collected at the same type of event in future research.