The increasing prevalence of micromobility vehicles in urban environments has raised concerns about safety in shared cycling spaces. This study examines the overtaking behavior of e-scooter and e-bike riders to inform traffic management strategies and infrastructure development. A controlled experiment was conducted using strategically placed cameras to track vehicle trajectories and inertial measurement units (IMUs) to capture roll data. Extensive data processing ensured accuracy and synchronization of trajectory and IMU information. Key findings reveal that e-bikes overtaking e-scooters initiate maneuvers from greater distances but maintain smaller lateral distances compared to e-bikes overtaking e-bikes.
Lateral position differences showed a stronger correlation with speed difference than longitudinal position differences. The highest roll rates and angles occurred during the overtaking phase. Pre-overtaking, higher roll rates and angles were observed when e-bikes overtook other e-bikes, indicating greater control adjustments. No significant gender differences were found in overtaking behavior. However, in non-interactive scenarios, male e-scooter riders traveled at higher speeds than females, while no gender differences were observed among e-bike riders. These results provide insights into the complex interactions between different types of micromobility vehicles during overtaking maneuvers. The findings underscore the need for targeted safety interventions and infrastructure improvements to mitigate risks associated with shared cycling spaces, ensuring safer coexistence of micromobility users and conventional cyclists in urban environments.

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.

Bicycles have an important role to play in the transition towards a more sustainable mobility. In order to achieve the modal shift towards bicycles, more must be done to accommodate cyclists. Although controlled intersections do increase the (perceived) safety of crossings with motorized vehicles, they are seen as major obstacles, and cyclists tend to avoid them when possible. The negative effects of controlled intersections for cyclists may be reduced by new methods of intersection control. This thesis combines the concepts of the connected environment and structure free control, to design an intersection controller that uses a genetic algorithmto determine the optimal signal plan, hereafter referred to as the SFGA controller. The controller is designed for an isolated intersection and considers car drivers and cyclists. Desires of cyclist with regard to controlled intersections, are identified by means of a literature review on the determinants of bicycle use, which are then projected on the controlled intersection. A traffic system model, based on validated models found in literature, is set up and a design for the structure free controller is proposed. A set of control objectives is proposed, including different metrics related to the desires of cyclists and car drivers. Objective function weights can be varied to achieve different levels of cyclist prioritization. A maximumwaiting time of 100 seconds is enforced in order to prevent prioritization of cyclists to result in unreasonable delays for car drivers, because red light running probabilities increase at larger waiting times. The performance of the structure free controller is evaluated for 15, 35 and 45% traffic saturation (percentage of intersection capacity), by means of a simulation based case study. The designed controller is benchmarked to vehicle actuated control (VA). VA has a cyclic, fixed control structure in which green times of movements are flexible and depend on the queue size. SFGA is benchmarkedwith an equalweight for the delay of car drivers and cyclists, and no weight included for the number of stops. The effect of incorporating weights that prioritize the desires of cyclists over those of car drivers is investigated. The SFGA controller results in average delays 1.8, 2.7 and 3.0 times lower than VAC for each of the evaluated traffic saturation levels. The number of stops is 1.9, 2.3 and 3.1 times lower. Including weights in the objective function to explicitly prioritize cyclists, results in even lower average delays and number of stops for cyclists. As is to be expected, this comes at the cost of additional delays for car drivers, especially for higher traffic saturation. The better performance of SFGA is attributed to two main differences between the controllers. First of all, the structure free aspect allows for a larger degree of freedom to choose more effective combinations of traffic lights to show green at the same time, instead of following the fixed sequence of VA. Additionally, the controller allows traffic that otherwise would experience the largest total delay to cross first, even if this means delaying some travellers in close proximity of the traffic light. This contrary to VA, that extends green time based on detected traffic in the active block. Without inclusion of weights that prioritize the desires of cyclist over cars, the controller already tends towards prioritization of the cyclists. This is caused by the controller considering the number of travellers that are influenced by its’ control decisions, combined with the higher traffic densities, that can be expected on bicycle paths in urban areas. Weights to prioritize cyclists can be included to include more priority, for example when bicycle traffic volumes are low. This work implicates that, in order to better serve the cyclists, it is not explicitly required to prioritize cyclists over cars. In areas with large volumes of cyclists, considering the number of travellers and their proximity to the traffic light can already result in cyclists being served better. This work could be used as a starting point or inspiration to design and eventually implement more cyclist oriented intersection controllers. Improvements for the controller and extensions for the research scope are proposed that are required for the controller to be suitable for practical implementation in the real world. If a future version of the controller is to be implemented, it will reduce the negative effects of controlled intersections on cyclists, thereby making the bicycle a more suitable replacement for the car.

In 2019 a virus surfaced in China that would later cause a pandemic: the coronavirus. Across the world measures were taken to reduce the spread of the virus. Public Transport (PT) had a unique position, being both an essential service and a place where the virus can easily be spread. This research investigates the measures taken in PT in the Netherlands and internationally in an objective manner. No assessment is made of any kind of any measure. In the Netherlands, the Outbreak Management Team collaborated with the public transport association OV-NL to ensure every companies response was similar. Through an interview with the chairman of OV-NL, Pedro Peters, more information was gathered on this particular aspect of the research. Besides taking measures to reduce the virus, mainly by reducing or avoiding contact (both between people and with surfaces), companies reduced their service levels. This reduction was a response to the large decrease in passenger demand and partly to more of the personnel reporting sick. This research investigated this reduction of service throughout the first period of the virus outbreak in the Netherlands (27th of February – 1st of June). Besides the Netherlands, measures taken in other countries were also investigated, showing many similarities. However, other measures were taken as well, like checking the temperature of passengers in for example Thailand, China or Iran or using a proximity app which happened in Singapore. Not every country experienced the virus outbreak at the same time. In the research, data by the Oxford University and Blavatnik School of government was used to create world maps that visualize the closing of public transport for all days of the outbreak up to June 1st. The same was done to create a map for lockdowns and using data found through an online search a world map visualisation was made about the mandatory use of face masks in public transport. The maps show a general trend: following the virus, but it is clear that some countries responded early or late and that the correct response to the virus was unclear. Especially the face mask visualisation shows a more random pattern. So while within the Netherlands the response to the virus was uniform, internationally the response was quite random. This research can be used to further research the measures taken and assess the measures with regards to for example effectiveness, safety or comfort.

To intrigue more people to cycle, it is essential to assess the current design of the cycling infrastructure to guarantee the efficiency and safety for the users. A credible simulation of cyclists is helpful to evaluate different designs of infrastructure and point out the problem. A valid simulation model requires proper verification and validation. However, there was hitherto no standard procedure to conduct model verification, and limited studies were found related to the verification of cyclist simulation models. To fill this gap, this study develops a verification framework for traffic simulation models based on the methodologies used in the literature. It also briefly discusses the difference to verify a cyclist simulation model. The framework is assessed by applying to a case study of the cyclist-queue-formation simulation model. The results prove the applicability of the framework to verify a cyclist simulation model. The organised structure of the framework provides a systematic measure for the verification of traffic simulation models. Furthermore, the cyclist-queue-formation simulation model is verified within the study area, where its conceptual model is proposed. The room for improvement of the simulation model regarding the relatively slow correction behaviour in steering and pedalling of the cyclists was also indicated.