This research explores how shared bicycles can enhance the modal shift from cars to public transport for commuter trips in suburban areas, focusing on South Holland. The study combines a literature review with a survey, comprising revealed and stated preference components, to assess travel behaviour and quantify the effects of shared bicycle attributes. A multinomial logit model is applied to estimate behavioural responses, with 105 respondents commuting to Drechtsteden and Leiden as case studies.

Results underline the critical role of competitive public transport travel times in fostering shared bicycle adoption. In areas where public transport significantly lags behind cars in travel time, the potential for shared bicycles is diminished. Shared bicycles are most effective for last-mile distances between 500 and 3,000 metres, but availability issues and reliance on private bicycles limit their adoption. Cost measures, including employer subsidies and reduced shared bicycle fees, significantly encourage uptake, while car parking charges predominantly shift commuters to public transport. A combination of free shared bicycles and paid parking achieves a potential modal shift of 10 percentage points, though inclusivity remains essential.

The stated preference model reveals that shared bicycle costs are perceived as three times more negative than travel time, particularly among younger and low-income travellers. Women and lower-educated individuals are more sensitive to public transport travel times, while frequent car users show less aversion to longer car journeys. Furthermore, hybrid systems such as Donkey Republic meet the needs of frequent commuters, while e-bikes provide limited added value in suburban areas due to car dominance over longer distances.

This study concludes that optimising public transport competitiveness, improving shared bicycle availability, and introducing cost incentives are vital for achieving a sustainable modal shift. Recommendations include integrating shared bicycles into public transport cards, reallocating bicycle parking, and enhancing hub locations to strengthen the synergy between shared bicycles and public transport.

The Netherlands is confronted with challenges such as traffic congestion, overburdened public transportation, and obesity. These issues could potentially be mitigated by elevating the cycling modal share. To attain this objective, the Dutch central government has introduced a range of strategies aimed at fostering commuter cycling. This study examines one of these strategies, namely financial schemes encompassing the kilometre allowance, lease bike, and 'Fietsplan'. The financial schemes are analysed by creating an extensive conceptual model which is thereafter used to make a comprehensive Social Cost-Benefit Analysis (SCBA). Using both methods contributes to improving the SCBA technique for cycling policies by presenting a well-rounded and extensive assessment of the associated costs and benefits. The results of the SCBA show that the lease bike scheme is the most socio-economically favourable financial scheme. The validity and reliability of the results could be improved by researching the elasticity of the kilometre allowance in relation to the number of additional cycling kilometres, the percentage switcher by different heights of the kilometre allowance and to determine the willingness to pay of individuals for a bicycle to better determine the consumer surplus of the 'Fietsplan'.

COVID-19 has had a great impact worldwide. One of its many effects was that offices had to be closed, which negatively affects the economy and people’s mental health. It is important that a safe way to keep offices open is found. Non-Pharmaceutical Interventions (NPIs) are an important way to do this. However, to pick the right NPIs for one’s office, knowledge is needed of the effects of the different NPIs within the given context. As of now, there are not many models that can provide a detailed estimation of COVID-19 spread and quantify the impact of NPIs in office spaces.
Therefore the existing model of the PedestrianDynamics - Virus Spread (PeDViS) of Duives et al. (2022) is chosen as the base model to be extended into a model that allows the comparison of the effects of NPIs in an office space.
The NPIs of which the effects are explored in this research are:
• All employees wear a mask while walking
• Increasing the rate of cleaning
• Increasing the ventilation rate from standard rate to the rate advised by government officials
• Allowing only 50 % of the employees to come into the office
• Allowing a maximum number of people in the meeting rooms, equal to 50 % of the capacity of the meeting rooms

A sensitivity analysis has been performed to learn more about the impact of some of the variables related to the meetings held in the office. Both the size and frequency of meetings were found to have some influence on the number of infections.
Next, policy analysis has been performed to learn more about the effectiveness of the NPIs, both individually and combined into policies. This led to conclusions on how large and consistent the effect of each of the NPIs was in reducing the number of infections in office contexts. The results also provided information on under what circumstances NPI could best be implemented and what NPI policies are recommended to be implemented to adhere to different levels of safety. Also, various limitations of this research were identified and recommendations for future work were given for part of them. The most important recommendations for future work are:
• Extending the model to include shared workspaces and the activity of having lunch.
•Testing the impact of more aspects relating to activity scheduling
•Gather data on people’s behaviour when the number of days they can come to the office is limited, to learn more about the inconsistent effect of this NPI.
•Test the impact of the NPIs in a context in which the initial infection risk is low.

The rapid development of Dutch DC’s near airports pressures the environment. VGS are considered a promising measure toward a more nature-inclusive development of Dutch distribution centers. However, an integral quantitative impact assessment model is needed to retrieve funding and facilitate an evidence-based decision-making process for the implementation of VGS. This research therefore aims to develop a multi-criteria decision model to assess the impact of VGS in Dutch DC’s near airports to enhance the decision-making process for the implementation of VGS. The main research question was formulated as follows: ‘How can a MCDM tool on the quantitative performance of VGS in delivering ecosystem services be developed and applied, in order to facilitate the impact assessment and evidence-based decision-making in the context of Dutch DC’s near airports?’
The research question was answered through a mixed-methods approach including literature research and expert interviews. A case study was used to apply and validate the MCDM model. VGS were found to offer a range of supporting, regulating, provisioning and cultural ecosystem services. The performance of VGS in delivering these services was mainly determined by the plants, substrate and support system. In general, living walls have a higher performance than green façades, among which modular living walls perform best. However, context-specific valuation was considered key. Evaluating VGS on the interaction effects between the main system components and the ecosystem services is an effective approach for developing a MCDM model that enhances decision-making and creates support base for implementation. A context-specific impact assessment can be achieved by weighing the relevance of the ecosystem services. Further research that compares the impact of distinct types of VGS is needed to further develop and validate the model, specifically with regard to grey water treatment, education, and wellbeing.

Crowd management is a crucial element in keeping situations safe. Models can help understand in-event crowd management system more thoroughly, and illustrate potential effects of measures before they have to be implemented in real life. However, applications of crowd models for operational support on in-event crowd management are sparse. Two main reasons are the cause of this: (1) inherent uncertainty regarding crowd modelling; and (2) computational requirements regarding large-scale applications. This research proposed three methodological steps for model-based experimentation—exploration, selection, and evaluation—to overcome current challenges in the application of crowd models. These steps were then applied on a case study of operational in-event crowd management at the Grote Markt, in the city of Breda. The research question thereby was: “What effect do the in-event crowd management measures—traffic regulators, directional guidance, and object placement—have on the density and walking speed of pedestrians in the Grote Markt, Breda?”. To answers this question, this study: (1) constructed a detailed microscopic crowd model of the Grote Markt, utilizing open-source crowd simulation framework Vadere for rapid, yet sophisticated, development of an agent-based model; and (2) applied this model according to the proposed steps for model-based experimentation, using techniques from the field of exploratory modelling and analysis. A connector between Vadere and the Python based Exploratory Modelling and Analysis (EMA) Workbench was constructed to synergize these two steps. Main findings highlight the potential of the proposed traffic regulator measure, and its effectiveness compared to object placement and directional guidance. With the proposal of the methodological steps, this work provides the needed stepping stone for operational support on crowd management. One that utilizes crowd models to understand in-event crowd management systems, and thereby enables the comparison between different in-event measures before they have to be implemented in real life.

Over the last decade, summer recreation in urban green-blue open spaces has become increasingly popular in Amsterdam, but so has the amount of reported nuisance because of summer recreation. In this thesis, the nuisance that has been reported by citizens during the summer recreation season from 2020 has been analysed by coding the reports in Atlas.TI, and using a survey from the Muncipality of Amsterdam as a verification. There are two locations where large amounts of nuisance reports have been filed, the Bogortuin and Park Somerlust, and several smaller locations with quay walls in the Oostelijk Havengebied and on the Amstel river. The content on the individual nuisance experience in the reports has been separated in observations, providing the nuisance causes, and evaluations, providing the nuisance impact. Recreation in it self is not problematic per se, but the presence of large groups of youngsters and recreation during the evening hours and at night is. This impacts local residents because of noise nuisance, especially at night, and pollution of waste and public urination. The character of summer recreation nuisance can be classified as both physical and social nuisance that is experienced during the evening hours, on weekend days and when it’s dry and warm. Implemented interventions have been evaluated and together with proposed interventions been analysed with the prevention pyramid. The measures that deal with the physical nuisance, temporary public toilets and an increase of waste capacity are in general reviewed positively. One successful intervention on social nuisance is the anchoring ban with a buoy line in the water to prevent noise nuisance from boats. None of the measures has been designed in an integrated way, using all the levels of the pyramid.  

Predicting crowd movements in real-time during mass events has been shown to be a complex yet valuable task in order to reduce the risk of overcrowding. The aim of this research is to propose and validate a crowd movement forecasting method for which simulation is performed offline (i.e. prior to the event) but the forecast is done online, in real-time. A number of scenarios is formulated and simulated creating what is called a database of scenarios. In real-time, based on information from the event's crowd monitoring systems, a scenario from this database is then selected which corresponds to the prediction. The research is focused on addressing the concepts related to the two pillars of the method: the formulation of the scenarios to be included in the database, and the operationalization of the system to select a scenario in real-time.

Route choice of cyclists recently became a hot topic of research for different disciplines such as transport and urban planning. Among other factors that influence these route choices, the urban environment has been identified as one in a network, road or aesthetic level. However, how the morphology of the built environment influences the cyclists remains rather unexplored. Considering that two routes are equally distant and safe, would a cyclist choose the most idyllic route in terms of its spatial openness? This thesis aims to explore the extent that the visible views of the urban environment affect the route choosing of a cyclist while traveling in the center of Amsterdam, The Netherlands. It also For this purpose, 127 GPS trajectories of the Fietstelweek dataset of 2015 are compared with alternative routes suggested by OpenStreetMap (OSM) via the OpenRouteService Directions API. The suggested alternatives can be either the fastest routes, the longest routes or those recommended by OSM (in terms of travel distance, travel time or safety. Throughout this MSc thesis a methodology based on the visibility of the cyclistis proposed. The visibility analysisis based on the ray casting algorithm in a 3D environment and gives as an output 3D isovists. The 3D isovists are used in order to measure the spatial openness as the ratio of the amount of visible sky, visible buildings and visible ground, as well as the shape of the 3D isovist itself. Opposite to similar researches that are performing the visibility analysis on the actual GPS routes, this thesis project applies the visibility analysis to a simplified version of the OSM street network in the centre of Amsterdam. The simplified OSM street network consists of street segments, the nodes of which represent real road intersections. The output of the visibility analysis per street segment is later mapped to the GPS trajectories and the alternative routes as an aggregated value. Finally, the routes are compared to each other with the ANOVA statistical method (N=127) and the Tukey’s post hoc test, resulting to a quantification of the differences of the GPS routes in terms of spatial openness. The results of the statistical analysis indicate the importance of the distance in the cyclists route choices but also the importance of the ratio of buildings and visible sky, the ratio of buildings and ground as well as a significant preference of the cyclists towards non-homogeneous routes with variation on the street profiles. We consider the methodology as an interesting proposal of measuring attributes that are difficult to be interpreted by using the traditional space syntax methodology and as a new way to provide design guidelines of the city to urban planners and architects when a detailed 3D environment is provided.

As an increasing number of people work in office buildings and new sophisticated sensor technologies become available there is, both, a need and potential, to develop more complex building service controls that increase the energy efficiency of buildings as well as the well-being of employees. The data required for the testing and evaluation of such control systems is usually in the form of movements and locations of office building occupants collected over long periods of time. However, such data is generally difficult to obtain for reasons ranging from the need to evaluate un-commissioned buildings to privacy concerns related to data sharing. Therefore, this study develops a pedestrian behaviour model that can simulate office occupants’ movements and locations thereby acting as a research platform that produces data for external applications. The model is integrated as it simulates not only the movements of occupants between different locations in the building but also decisions that drive the movements such as which activities occupants want to carry out throughout the day, and when and where they want to perform these activities. Furthermore, the model is based on the guidelines of (i) flexibility – the model is able to simulate movements in different building plans and represent movement patterns of different organizations; (ii) extensibility – the model uses a modular framework that enables easy adoption of more complex components and integration with other workplace related studies as and when required; and (iii) data parsimony – the model has low and simple data requirements itself.