In response to the growing housing shortage in the Netherlands, particularly in urban areas where land availability is constrained, local governments are increasingly considering urban expansion into peripheral areas, even those near freeways. These areas offer convenient car access but pose challenges for sustainable development due to the potential for increased congestion. This research focuses on developing mobility design strategies to reduce car usage and promote public transit in such peripheral areas. The central research question is: "Which mobility design strategies, regarding public transit and car parking planning, should be implemented to reduce car usage and enhance the attractiveness of public transit in a peripheral urban area?" To address this question, a Discrete Choice Model was developed to analyze commuting mode choice behavior under different scenarios. The research began by identifying influencing factors from the literature, including relevant urban transportation modes (bus, light rail, car, and bike), trip characteristics, personal attributes, and environmental factors. The study focuses on Rijnenburg, an outskirt area of Utrecht, which is poised for significant urban development but faces challenges due to its car-friendly location at the intersection of two major highways. Three design scenarios—Conventional, Sustainable, and Ambitious—were developed based on existing municipal development strategies. These scenarios consider various factors such as public transit stop density, line frequency, route planning, vehicle type, parking facility location, and parking costs. A Stated Preference survey was conducted to gather data from 200 respondents, which informed the construction of both a Multinomial Logit (MNL) model and a Panel Mixed Logit (Panel ML) model. While the MNL model was ultimately chosen for its balance of accuracy and interpretability, the study revealed a strong preference for bikes over cars among respondents, highlighting the potential for shifting mode choice through strategic design interventions. The analysis showed that the Ambitious scenario, which includes tougher interventions such as higher parking costs and restricted parking locations, was most effective in reducing car usage. However, the scenario's feasibility was questioned, leading to a recommendation for a hybrid approach combining elements of the Sustainable scenario with stricter car parking measures. The research also highlighted several limitations, including potential biases in the survey sample and the exclusion of certain factors from the model. Nonetheless, the findings suggest that a combination of mobility strategies—focused on optimizing public transit accessibility and increasing barriers to car use—can significantly contribute to sustainable urban development in peripheral areas like Rijnenburg. In conclusion, the recommended strategies, particularly the reduction of transfers in public transit and the strategic location of parking facilities, are expected to play a crucial role in promoting sustainable mobility in Rijnenburg. Further research is recommended to refine these strategies and explore their applicability to a broader range of contexts.

The National Model System (Landelijk Model Systeem [LMS]) is used to model and predict travel behaviour for the whole of the Netherlands. The LMS is a multimodal model that makes predictions for the main road and rail network of the Netherlands and is an important tool for policy making. One of the inputs of the LMS is data based on yearly travel surveys (Onderzoek Verplaatsingen in Nederland [OViN]).

The work in this thesis shows that the LMS is currently unable to accurately capture the effect of the differences in spatial environment effectively. The LMS uses the Degree of Urbanisation (DU) to model the spatial environment, which proves insufficient to correctly model travel behaviour.

This conclusion was reached by using a cluster analysis and propensity score matching and by comparing the ‘real’ modal split (OViN) with the ‘predicted’ modal split (LMS). All zones in the Netherlands were clustered based on characteristics of the spatial environment. This was done using the so-called D-variables.

The propensity score matching showed that the differences in modal split between the different DUs and the different clusters are caused by both demographic characteristics and differences in the spatial environment. However, the effect of the spatial environment is larger.

Policy makers and other users of the LMS should be aware that testing policies or future scenarios in the LMS that change aspects of the spatial environment might introduce additional uncertainties in the forecasts of some regions.

The introduction of electric buses (EBs) is required in order to achieve global greenhouse emission goals. However, operating an electric bus fleet (EBF) requires careful consideration of both the mobility and energy systems in charging strategies. In literature and in real life many cases show careful consideration of only one of the systems and an oversimplification of the other, resulting in failed implementations. This paper focuses on the need for additional charging of EBs during the day using on-route opportunity charging during the on- and offboarding of passengers in residential neighbourhoods. This research aims to provide an integrated approach to bus service design, including both the mobility and energy systems. Additionally, this paper presents insights into the effect of traffic management on the feasibility of on-route opportunity charging. Two simulation tools are used for the integrated decision-making approach: SUMO and Gaia. The Simulation of Urban MObility (SUMO) software provides results regarding the energy consumption behaviour and charging needs of the EBs. Gaia provides results regarding the transformer load rate in the residential distribution grid. This paper proposes five strategies with a varying configuration of charging capacities, charging times and the introduction of traffic management via traffic priority. The five strategies are tested against three requirements: two from the mobility system and one from the energy system. The research presented uses a case study of bus line 36 in Rotterdam, the Netherlands. The results of this research show that residential neighbourhoods are often unable to handle chargers with the maximum capacity of the buses in the case study of 450 kW. A mid-range charger of 200 kW is possible in most cases. With a 200 kW charger, the on- and offboarding time of passengers is insufficient to complete daily operations. Therefore, additional charging time is necessary. Without the introduction of traffic priority, the timetable cannot be completed. With the introduction of traffic priority, travel time and energy consumption are reduced by 9.8% and 4.5%, respectively, and daily operations can be completed while satisfying the requirements of the mobility and energy systems. The results presented in this thesis suggest that an EB route design with opportunity charging is impossible without considering both mobility and energy systems simultaneously. From the mobility perspective, opportunity charging is feasible only if the charging infrastructure can meet the buses' energy needs without disrupting the schedule. From the energy perspective, it is essential that opportunity charging is implemented where and when sufficient charging capacity is available. The introduction of traffic priority allows for the satisfaction of all requirements and displays an example of the connection between mobility and energy systems.

Traffic congestion is a challenge that frequently emerges due to changes in the roadways such as tunnels and sags, causing capacity reduction. The capacity drop phenomenon exacerbates traffic congestion, due to decreased queue discharge rates. Among the strategies employed for traffic management, Variable Speed Limit (VSL) control is a common approach to alleviate congestion and mitigate capacity drop. The control is expected to be more powerful when integrated with Connected Vehicles (CVs). However, the intricate interplay between the Market Penetration Rate (MPR) of CVs and the parameters governing VSL remains under-explored.
This study seeks to quantify the relationship between the MPR of CVs and the key VSL parameters, encompassing factors like the optimal acceleration length and speed limits. The VSL control is applied to CVs at the road section upstream of a tunnel bottleneck modelled by a continuum car-following model with bounded acceleration. The findings of this research suggest a minimum MPR of CVs essential for preventing capacity drop and reaching the maximal outflow. Intriguingly, this challenges the conventional notion that regulating solely the leading vehicle suffices to govern the behaviours of all following vehicles. The value of the minimum MPR threshold is affected by the acceleration behaviours vehicles exhibit.
Furthermore, this study underscores the importance of considering the MPR of CVs when devising the optimal speed limit and acceleration length for the VSL. It shows that while a higher speed limit can lead to higher throughput, the optimal acceleration length increases exponentially with the increasing speed limit, particularly in cases with low MPR of CVs. While adopting a relatively lower speed limit, the acceleration length can be reduced to 0m for all levels of MPR of CVs. In summary, it suggests that when implementing VSL in practice, a balance between the resulted throughput, the required acceleration length and the robustness of VSL across different levels of MPR of CVs should be considered.

Enhancing and expanding public transportation is becoming a crucial solution to the high costs of congestion and the escalating environmental impacts of car-centric transportation systems observed in numerous cities today. One approach to enhance the quality of public transportation, and thereby boosting its ridership, is through the intelligent design of stop locations. Strategically locating stops can increase coverage of transit and reduce overall trip times. However, selecting stop locations is a relatively intricate task as it involves striking a balance between two competing objectives; accessibility and efficiency.

In this thesis, a multi-objective optimisation model is presented to make the trade-offs between several factors influencing stop locations explicit. The model enables a comprehensive assessment of transit objectives by evaluating alternatives, determining demand and running times in detail, and examining network effects. Relevant factors such as sociodemographic characteristics within catchment areas, travel patterns, transit alignments, and transfer locations are modelled for different areas of the system.

The developed model is employed in a case study that focuses on the tram network of The Hague in the Netherlands. Various objectives are evaluated to determine the optimal stop locations and the factors that affect them. The results reveal that the ideal stop locations are contingent on the objectives established. Despite this, the number of stops in the system of The Hague is reduced by at least 6% for all considered objectives. When the user costs are minimised, an increase in ridership of 4% can be achieved, whilst saving 3% of operator costs. Moreover, it is concluded that optimising the network for either the operator or society results in 17% fewer stops, and a subsequent estimated cost saving of 9%, without any negative impact on ridership.

Adaptive Cruise Control (ACC) relieves human drivers’ tasks by taking over the control of the throttle and braking of the vehicles automatically. However, it has been demonstrated in many empirical studies that current production ACC systems fail to guarantee string stability. It is believed that if vehicles can take the longitudinal dynamics further downstream into account and react to the propagating disturbance earlier, the string stability in the platoon may be improved. Instead of relying on inter-vehicle communication technologies, the ego-vehicle should be able to detect the second leading vehicle by leveraging the power of on-board sensors. Still, the second leader measurements can be highly erroneous. Therefore, it is important to consider the entailed measurement uncertainties when designing and evaluating such ACC systems. This study proposes several ACC systems which possess the property of multi-anticipation and uncertainty handling.

The possible sensor technology which can collect the second leader measurements is first investigated. Based on the considered setup, the measurement uncertainties are modelled to reflect the real-world conditions. The ACC system architecture and control system design method are then proposed. Deep reinforcement learning is applied for the controller design in light of its great potential in describing the complex non-linear control task and handling the uncertainties. Kalman filters and recurrent policies with a Long-Short-Term-Memory network are applied to cope with uncertain measurements. The first method estimates the state information before feeding it back to the controller agent, while the latter incorporates the state estimator into the controller to actively consider the uncertainties while making decisions.

A numerical simulation approach is adopted to theoretically assess the performance of the proposed ACC systems. A traffic disturbance event and multiple levels of measurement noise are considered in the experiment. To analyze the performance in terms of string stability and ride comfort and understand the car-following behavior mechanism resulted from the proposed systems, a quantitative analysis framework is developed.

The evaluation results demonstrate the applied learning-based approach succeeds to train ACC control policies which can ensure string stability. It is also found that the multi-anticipation ability significantly improves the string stability and ride comfort performance. In the scenarios with measurement noise, systems using the tuned Kalman filters exhibit the ideal level of string stability performance. However, ride comfort cannot be guaranteed in scenarios with large measurement noise. On the other hand, systems using recurrent policies can better ensure ride comfort performance while maintaining string stability at certain levels. Based on the results, the performance limits of the proposed ACC systems in the handling of measurement uncertainties are explored. In addition, with the different policy training setups, the trade-off between these two performance aspects is shown.

The findings of this study are anticipated to trigger the development of advanced multi-leader ACC system by automakers, sensor manufacturers, and traffic engineers. Future work can be directed to an enhanced controller design. Robustness of the systems with respect to other sources of measurement uncertainties, more types of traffic disturbance, and platoon heterogeneity is worth further design consideration and analysis.

The European Commission has mandated the requirement of advanced safety features in all vehicles sold in the EU from 2022 onwards. This will help drivers get gradually used to ADS, eventually transitioning to fully autonomous driving in the distant future. There are more vehicles on road now equipped with lane-keeping systems and other driver assistance systems due to the added benefit of safety. One such Advanced Driver Assistance System (ADAS) feature is the lane-keeping system which has plenty of performance evaluation research being done on it but lacks research from an Operational Design Domain (ODD) perspective in simulation. ODD is the set of conditions for which the vehicle is designed to function. There are many ODD taxonomies present in academic literature for the classification of ODD attributes in the ODD definition. These are recommended to be used by Original Equipment Manufacturers (OEM) to classify their ODD definition of the system for effective comparison between the same ADAS feature offered by two different OEMs. However, this is not seen to be done by the OEMs and causes a disparity between the ODD definitions, leading to misunderstanding or misinterpretation of the defined ODD. The OEMs do not exactly specify the ODD boundaries in publicly available instruction manuals of the vehicles. The conditions where the system cannot function properly are very vaguely mentioned. Furthermore, the different OEMs provides the same ADAS feature with different names with differently defined ODD boundaries. Bringing these ODD definitions of all these OEMs under one umbrella is currently being attempted by policymakers and regulatory organisations. A standard way of testing the impact of the different ODD attributes on the performance of a lane-keeping system is still absent. Therefore, this research aims to provide a method to assess the ODD boundaries of a lane-keeping system using the simulation software Prescan by Siemens and is intended to be used by researchers, policymakers and OEMs to refine the ODD and to test the effect of the ODD attributes on the performance of the system. It was found in this research that there is a strong interdependency between the tested ODD attributes. This can lead to a possibility that the ODD definition may not exactly be a straightforward set of specific values in the form of a table, but instead can be dynamic considering this interdependency. It was also observed that some test cases classified inside ODD from the initial ODD assessment had poor lane-keeping performance and some test cases classified outside ODD had good lane-keeping performance. Another observation from the test cases was the ability of the test vehicle to move at higher speeds in narrow lane widths with good lane-keeping performance compared to wider lane widths. This falls in line with findings from previous literature and will require validation. The research approach of this study is used to develop a conceptual framework to assess the ODD boundaries of an ADAS feature in a simulation environment.

Current indicators for measuring traffic safety such as fatalities and severe injuries are lagging indicators, meaning that an accident first needs to happen before it can be measured. With the rise of automation in vehicles, the opportunity may arise to measure leading indicators. These can proactively measure traffic safety by measuring traffic conflicts, interactions that are dangerous but do not necessarily result in an accident.
This research uses the knowledge of experts on traffic safety and/or vehicle sensor data to evaluate the suitability of five types of indicators to measure traffic safety based on vehicle sensor data. It also evaluates ten potential barriers for using vehicle sensor data in practice. While limited differences are found between the types of indicators, none of the potential barriers is rated as unsurmountable by the experts. In doing so, this research proofs that it would be possible to measure traffic safety with vehicle sensor data and provides a starting point for further research

Interacting with cyclists is a difficult challenge for Automated Vehicles (AVs). It is important that the introduction of AVs does not lead to a decrease in cyclist safety. This study presents a new methodology that is developed to assess road safety between AVs and cyclists. Surrogate Measures of Safety are identified specifically for the interaction between AVs and cyclists. The methodology makes use of the presented Surrogate Measures of Safety to objectify road safety, by classifying each into three different safety levels. The methodology is presented in a rubric that can be used to assess road safety of conflict situations. The methodology is demonstrated for a case-study in the Netherlands, analyzing 163.5 km of road with a total of 118 conflict situations. For each conflict situation, road safety is assessed and accident risk factors are identified. Common accident risk factors found are reduced visibility of a cyclists’ trajectory path, unclear infrastructure due to missing road surface markings, and infrastructure facilitating visual communication and occasional cyclist traffic violations. Although safety primarily needs to be on-board of AVs, road authorities can improve road safety by providing clear and predictable infrastructure, with good visibility of conflict situations and cyclists’ trajectory paths. Future research should focus on improving the performance of cyclist detection, classification, and trajectory prediction by AVs. Potential conflict situations between AVs and cyclists should be analyzed in more detail to quantify their safety level, and AVs should be trained in conflict situations where cyclists can be encountered.

In this research, the link between air travel and the first/last mile trip with public transportation will be researched, as in practice, ticket platforms (such as Booking.com or Expedia) do not yet provide this integrated air- and public transport service. Eventually, the idea would be to create an integration platform that serves as a mediator to integrate booking and payment of air- and public transport tickets. As a result, travellers normally booking an airline ticket for airport-to-airport travel, would then be able to buy an integrated ticket involving air- and public transport for travelling from origin to end destination. This research therefore has used methods to judge the feasibility and desirability for this idea, namely a literature review regarding this topic, desk researches, a survey for travel preferences regarding this integration, a stakeholder analysis, and interviews with potential linked parties and governance experts. Eventually the end goal is coming up with a conceptual framework that shows the most important factors regarding the feasibility and desirability of this integration platform, and a business model canvas. It can be said that integrating booking and payment of air- and public transport tickets can be feasible and that certain (shares of) parties think it is or find it desirable. However, the conceptual framework and business model canvas displayed a high amount of important factors, which mostly need to fall into place at the same time. Results of the survey indicated positive reactions, but the question will still be if in reality this interest from potential users will play out. Also, technological developments regarding payment in public transportation can jeopardise this initiative. All in all, risks of this integration platform for potential initiators are not excluded.

The traditional transport hubs are shaping into the idea of the mobility hubs with the advent of multiple vehicle-sharing forms, such as bike-sharing and car-sharing. Also, a gradual shift in the culture of consumption towards more usage and less ownership, as well as the shared economy supported by internet platforms and mobile apps, allows easy access to multiple daily mobility choices, especially in urban environments. The Mobility hubs seek to merge conventional public transport with these new shared services which have the potential to serve as a solution to the first/last mile problem within the public transport and will allow operators increase their ridership. Transport demand models are used to forecast future travel demand but consider the same travel behaviour as that of today. Mobility Hubs have the potential to change the travel behaviour of travellers and travel demand models should not only be able to forecast the future travel demand but also take into consideration the potential changes in travel behaviour due to the mobility hubs. This study deals with a microsimulation travel demand model, OCTAVIUS and to identify the extent to which such a microsimulation demand model can capture the travel behaviour associated with the future mobility hubs.

The accessibility of cities is under pressure in the Netherlands. Automated vehicles are often mentioned as a possible solution for this problem. In this study, the financial feasibility of automated buses is examined from an operator
perspective. A financial model is developed and applied on the bus network of Almere where four different levels of automated buses were compared. The comparison are based on the following factors: operational costs, investment costs and ridership. Based on the case study results, it can be concluded that automated buses that still require a driver or steward in the bus for supervision are not yet financially feasible from an operator perspective. Decreasing costs of
automated technologies can however change this financial feasibility. In automated buses where the driver is removed it could be financially feasible from an operator point of view. However, many challenges will arise in this situation regarding safety regulations, passenger acceptance and operational infrastructure domain.

During tenders in public transport, the bus network is reconsidered and adjusted. An accurate prediction of the effect on ridership is required. Due to the tender environment, time and input data are limited. This research focuses on deriving a relation between level-of-service (LOS) and ridership, and implementing this in a model suitable for the tender environment. A before-after study is performed based on two different levels of detail: OD-based and line-based. An OD-based analysis shows two issues for translation to model parameters: a poor fit of the trend line and a large share of a-typical data. A line-based approach provides more promising results. The range of elasticities and growth factors found is large, which is insufficiently acknowledged by current literature. Context is one of the main explanations for the large range. A regression analysis indicates a significant relation between LOS and ridership and indicates possible significance of additional predictors for ridership change. A comparison model is developed, which enables the user to match its request with an entry in the data base, providing the ridership development and context. The model is able to provide the user with growth factors for full day and peak/off-peak interaction and indicates sensitivity of the user groups. Future expansion of the model is recommended.

There is a pressing need for road authorities to take a proactive role in the deployment of automated vehicles on the existing road network. This requires a comprehensive understanding of the road infrastructure requirements that would lead to safe operation of automated vehicles. In this context, a field test with Lane Departure Warning and Lane Keeping Systems-enabled vehicles was conducted in the province of North Holland, The Netherlands. The performance of these automated systems was evaluated using performance indicators such as Mean Lateral Position and Standard Deviation of Lane Position. In this study, the Systems Theoretic Accident Modelling and Processes (STAMP) model was adopted to understand the relationships between the various components of the “Road System”, which in this study include the road authority, the automated vehicle system, elements of the road infrastructure, and weather conditions. Empirical data from the experiment is used to estimate the relationships between the different components, followed by the assessment of their impact on the performance of the automated vehicles. It was found that visibility conditions have a significant effect on detection performance, which worsens in rainy conditions especially under streetlights. It has been also observed that there is a significant difference in Lane Position between Left Curves and Straight sections, and between lane widths less than 250 cms and those that have larger widths. These findings are combined with the results from the STAMP analysis to formulate a set of road infrastructure requirements that would lead to safe performance of Lane Assistance Systems.

In a multimodal network with the bicycle as core, the design of the network is based on the use of the bicycle as access and egress mode. With the bicycle as access and egress mode instead of walking, travellers can travel much larger distances to bus/tram/metro (BTM) stops and train stations while having about the same travel time. This will make it possible to use fewer BTM stops, stations and transit lines, which will save travel time and operational costs. However, to which extent does this occur? This thesis “Multimodal network with the bicycle as core” is made to know more about the effects of using the bicycle as access- and egress mode in a multimodal trip on aspects like travel time, modal split and operational costs. The main question is: To what extent does a multimodal passenger transport network with the bicycle as core reduce the total travel time for most travellers and increase the modal split for (multimodal) transit trips, without high investment- and operational cost. Based on the findings of the literature study and remaining research gaps, several theoretical scenarios were made. In these scenarios, different combinations of bicycle catchment radius values and (multilevel) BTM service outlines were made. After applying these combinations, its effects on the (experienced) travel time, (experienced) connection quality, and costs were calculated. The results indicated, that an ‘asymmetrical’ catchment area combined with an one-level BTM service outline created the most potential for applying into a multimodal network with the bicycle as core. When travellers have to travel to a BTM stop in the opposite direction of their direction, the catchment radius should be 1000 m. Larger radius values had a too high negative impact on the travel time. If the stop is in the same direction as the destination, a catchment radius of 2000 m still had a positive impact on the travel time. Also, the results confirm that a bicycle-transit trip combination creates a lower travel time and operational costs compared to walking. The last part was as case study called Utrecht Science Park (USP). In this case study, a multimodal network with the bicycle as core was designed for the USP and region east of the city Utrecht. The goal of this study was to test if a multimodal network with the bicycle as core was capable to lower the total travel time of multimodal trips and decrease the car-use for trips to the USP. Eventually, two alternatives were chosen plus a zero alternative. The simulation results showed a large decrease of the total travel time for trips to the USP with a bicycle-transit mode combination. Furthermore, the number of car trips decreased with more than 1000 car trips (from nearly 8000). This thesis showed that a multimodal network with the bicycle as core indeed creates a lower travel time and operational costs compared to walking as access and/or egress. Furthermore, it attracts travellers previously using the car as main trip mode.

Water related disasters with higher impacts due to climate change and the possible occurrence of higher magnitude earthquakes that are expected to hit increase the need for tsunami resilient systems. Transport systems enable evacuation, and access for emergency services and materials for rebuilding. This research aims to clarify the term tsunami resiliency for transport systems by means of decomposing the concept of ‘tsunami resiliency’ into separate factors first and then design an assessment method based on these factors. The measurements and best and worst case scenarios for the factors form the basis for a scoring range for each factor. This allows the assessing of a transport system on its tsunami resiliency.

Studies have shown that car-sharing has a lot of potential. Because of this, municipalities require a tool to evaluate the effects of car-sharing. This research has developed a mode choice model that includes a car-sharing alternative considering an activity-based framework, for the city of Rotterdam.

The thesis project deals with the tactical determination of supply provision in terms of line frequencies and deployed vehicle capacities in public transport networks using a dynamic assignment model. To this end, an agent-based dynamic and stochastic simulation model for public transport operations, that can consider service reliability issues, is used in combination with a search algorithm based on simulated annealing. The model is applied to multiple case studies in order to test parameter sensitivities and identify practical benefits of the obtained results. Practical applications show that a change in supply provision proposed by the model results can create significant benefits.