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.

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.

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.

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.

In crowded pedestrian environments, individuals often resort to rotating their bodies as a strategy to avoid collisions. Surprisingly, this rotational behavior, despite its significant implications for crowd capacity, has received relatively little attention in research. This study seeks to fill this gap by diving into the complicated world of pedestrian rotation behavior, particularly in the context of high-density bidirectional and crossing flows.
Drawing upon data gathered from the CrowdLimits experiments, we start the exploration of how various factors impact the rotation behavior of pedestrians. Our investigation covers crowd density, the fundamental movement scenarios (bidirectional and crossing flows), flow ratio, and the influence of disturbances within the crowd under different scenarios.
Our key findings reveal that all these factors play a role in shaping the frequency of rotations within a crowd. However, the extent and precise conditions under which these factors influence this subject demand further in-depth research and exploration.
In essence, this study addresses the fundamental question: How does shoulder rotation behavior vary concerning macroscopic crowd characteristics, including crowd density, flow ratio, and movement patterns like bidirectional and crossing flows? Through this research, we hope to highlight the complex interplay between these factors and the rotational strategies operated by pedestrians, ultimately enhancing our understanding of crowd dynamics.

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.

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.

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.

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.

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.

This research explored two types of models, ARIMA and multiple linear regression, for forecasting tourist counts in 7 locations around Amsterdam red light district, for the prediction horizon of up to 30 minutes.

This research aims at analyzing route choice behavior of E-bikers, in terms of which factors play a role and to what extent. The research is performed based on E-bikers route data in Ghent. Two interesting developments are aimed to include as well, in terms of multi-attribute cost functions as input for route generation and including land use attributes to cyclist’s route choice models.

Understanding pedestrian traffic is essential to design for safe and reliable pedestrian infrastructures, facilities and operations. For the assessment and design of pedestrian transfer areas at stations capacity standards for uni- and bidirectional flows are applied. It has been observed that, at railway stations, also other configurations of flows occur, such as intersecting flows at different angles (e.g. intersections between transfer areas and stairs/escalators or shops). In contrast to uni- and bidirectional flows, for which many researches have quantitatively studied the pedestrian flow characteristics, only little research has been done to intersecting flows. The purpose of this research is to gain insight into how the flow capacity of a pedestrian intersection at a railway station is influenced by several factors and to explore methods that can estimate the flow capacity of a pedestrian intersection. A theoretical framework has been constructed that shows the hypothesized causal relations between the research topic - intersection flow capacity - and several variables that describe the context of this study. Furthermore, three capacity estimation methods were proposed to estimate the flow capacity of a pedestrian intersection. According to the field study, the second and third method both seem suitable for capacity estimations, even though the intersection flow capacity (according to the traffic flow principles) could not be estimated in this study. Several recommendations have been made for future research, including points of improvement regarding the the studied methods, directions for research focus and the usability of the findings in this study.

At mass events, pedestrians can experience the level of crowdedness as unsafe, unpleasant and stressful. To gain a better understanding of perceived crowdedness, the effects of personal, trip and event characteristics at an event are researched. Data collection was performed by a simultaneous survey and monitoring study at the TT Festival in Assen and at the Red light district in Amsterdam. A SEM model shows that perceived crowdedness is influenced by mainly by the density, quantified using Wi-Fi sensor data. Besides that, trip purpose and familiarity with the event influence perceived crowdedness as well. Furthermore, this research shows that perception of safety, comfort, atmosphere and attractiveness of the environment are also related to the perception of crowdedness.

Due to increasing urbanisation rates worldwide combined with growing transportation demand, liveability of the urban environment is under pressure (UN, 2018). In response, many governments worldwide have set goals for increasing the share of trips made using sustainable modes of transport, such as walking and cycling. The use of active modes (i.e. walking and cycling) provides health benefits for individuals due to increased activity levels, and on a network level these modes (standalone or in combination with public transport) can potentially reduce traffic jams and the associated externalities (including air and noise pollution) when substituting the car. To achieve the desired increase in active mode shares, targeted policies need to be implemented. This requires a better understanding of who currently uses these modes, who could be persuaded to switch to active modes, and which determinants are driving active mode choice.
This intended change towards active modes requires an adequate representation of walking and cycling in the transportation planning models in order to assess the effect of active mode policies on modal shares and distribution over the network. However, this is often not the case. Moreover, integration of active modes in these models occurs very slowly. Walking and cycling are often missing in transportation planning models, treated as a ‘rest’ category, or combined into slow/active modes, all of which result in incorrect estimates of the active mode shares, making it impossible to correctly identify the impact of potential policy measures on active mode shares. Examples of these policy measures are introduction of new infrastructure or changes to existing infrastructure, which impact route choice and distribution over the network, and reimbursement of using the bicycle to go to work, which impacts the mode choice of individuals.
Investigating mode and route choice of active mode users increases the knowledge on active mode choice behaviour. By bridging this gap, the transportation planning models can potentially be improved. The objective of this thesis is ‘to understand and model mode and route choice behaviour of active mode users’. We identify six topics that are imperative to travel choices. First, we investigate the daily mobility patterns of individuals in relation to attitudes towards modes, because attitudes are considered to influence travel behaviour (Chapter 2). Afterwards, we zoom in on individual trips. We aim to understand which determinants drive the choice to walk or cycle (Chapter 3). In this topic we define the mode choice set as all feasible modes per individual and trip. However, not all feasible modes are used by individuals. Therefore, the third topic focuses on modes used over a long period of time, which we coin the experienced choice set. We investigate which determinants are relevant for including or excluding modes in this choice set (Chapter 4). Regarding cyclists’ route choice, we investigate the determinants influencing this choice (Chapter 5). This research is based on the experienced choice set. Accordingly, we compare this method to frequently used choice set generation methods to identify the added value of the experienced choice set (Chapter 6). Finally, we perform a literature review on how mode and route choice can be modelled simultaneously (Chapter 7).

This research investigates the question how the choice of scenarios and metrics influences the calibration of pedestrian simulation models. By calibrating a pedestrian model using different combinations of scenarios and metrics and comparing the results it was concluded that it matters what scenarios and metrics are included during the calibration. The implication of this is that one should calibrate a pedestrian model based on its intended usage and that this should be leading in the choice of which scenarios and metrics to use.