We have successfully designed and implemented a multi-player, multi-modal virtual reality (VR) co-simulator that integrates both pedestrians and cyclists within the same VR environment. This co-simulator is designed to support multi-player, multi-modal VR experiments aimed at comprehensive data collection in transportation research. It features advanced functionalities including body tracking for pedestrians and cyclists, high-quality digital human representations, and comprehensive data collection technologies such as eye gazing data. A VR experiment was conducted to evaluate the effectiveness of the VR co-simulator and investigate the interactions between vulnerable road users (VRUs) and automated vehicles (AVs) in shared spaces. The assessment demonstrated the co-simulator's capabilities and feasibility in terms of simulator sickness, presence, realism, and usability. The experiment also confirmed the impact of VRU combinations and initial relative positions on the interactions between VRUs and AVs in shared space.

This study examines the impact of Adaptive Cruise Control (ACC) systems on traffic flow efficiency and road safety, with a particular emphasis on transition control between automated and manual driving. Empirical data from the OpenACC database and the SAE Level 2 naturalistic driving study were analyzed to capture key ACC characteristics, which were then used in simulations to reflect the variability among different ACC systems. Simulations were conducted on a section of the Dutch A13 highway, with ACC market penetration rates (MPRs) set at 25% and 75%. The ACC and transition control models were integrated as external driver models in PTV VISSIM under the assumption of nearly ideal human driver responses, excluding potential response delays and the string instability typically associated with ACC systems.

The results indicate that ACC systems with transition control models significantly enhance traffic flow efficiency and safety, particularly at higher MPRs. The introduction of ACC vehicles reduced congestion and increased time-to-collision (TTC) values, reflecting improved traffic safety. However, the study highlights limitations, including simplified human driving behaviors and the exclusion of string stability effects. Future research should focus on more complex driving scenarios, such as urban environments, and enhance data collection methods to further understand ACC system performance in diverse traffic conditions.

Autonomous Driving Systems (ADS) are an innovative solution to urban mobility problems and have the potential to transform the Dutch roads radically. However, before these systems can be widely adopted, they must undergo a rigorous certification process to meet safety and reliability standards. Regulatory authorities are currently grappling with the challenge of certifying ADS responsibly. Despite significant technological progress, there is still limited understanding of the root causes behind these certification challenges. Without a clear understanding of these obstacles, finding effective solutions remains difficult. Therefore, this research aims to explore the barriers to responsible ADS certification and provide insights into how these challenges can be overcome.

This study investigates how Dutch municipalities can measure and use subjective road safety. A literature review was conducted, analyzing 31 scientific sources. In addition, gray literature and practical differences were examined, involving 13 different parties. Interviews were also held with six municipalities to discuss their perspectives on the definition of subjective road safety, the data they currently have, their goals regarding subjective road safety, the resources available for further measurements, and their most pressing needs. The study found that there is still significant ambiguity within municipalities regarding the definition of subjective road safety. For many municipalities, the individual’s perception of safety plays a central role. Furthermore, there is confusion about the relationship between objective and subjective road safety. Municipalities need more concrete goals to make informed decisions about whether to measure subjective road safety reactively or proactively. Policies can be developed based on these goals, but it is crucial that objective road safety is not compromised. Using subjective road safety as a measure to gain insight into objective road safety is not advisable, as the relationship between these two dimensions is not yet fully understood. While they coexist and influence each other, they function independently.

In order to increase traffic safety in the Netherlands, the government implemented the GOW30-policy. However, evaluation of this policy shows that drivers do not comply with this newly imposed speed limit sufficiently. For this reason, roads need to be designed in such a way that speed limits are perceived as credible. At the same time, the need for sustainable road designs arises, due to factors as increased urban heat stress and population growth. Thus, road designers need to make trade-offs between spatial quality and mobility. Incorporating greenery is a promising way to reduce urban heat stress, but the presence of greenery, particularly thick trees, can also increase the severity of traffic accidents. This study evaluated the impact of roadside greenery on driving behaviour, utilising a driving simulator experiment complemented by a post-experiment survey. Linear Mixed Model analyses (LLM’s) together with survey insights revealed that perceived driving comfort leads to increased driving speeds. Comfort increases on wider roads and on roads with more overview. For this reason, it is not recommended to incorporate low greenery on GOW30 roads. Moreover, high and dense greenery is shown to reduce driving speeds while promoting better positioning on the road. It is furthermore recommended that research is performed in real-life, whilst evaluating roadside greenery in combination with cycling lanes under varying traffic and weather conditions.

New applications of connectivity between vehicles and the infrastructure are developed. One of these applications is providing upstream information on variable speed limits to connected and automated vehicles. It is expected that the connectivity can contribute to safer roads due to better compliance to the posted speed limits. Those expectations are based on microscopic models with the assumption that human drivers behave similarly in mixed traffic as they do in only human driven vehicles traffic. However, few studies have shown that human drivers tend to change their driving behavior when interacting with automated vehicles in mixed traffic. For this reason, a driving simulator experiment is executed to investigate the effect of the penetration rate of connected and automated vehicles and the distance at which the information is provided on the driving behavior of human drivers. The driving behavior was analyzed in terms of longitudinal and lateral behavior in the context of a three-lane motorway. The penetration rate was found to only impact the speed adaptation when combined with a large distance of upstream information. Lower means speeds, lower section entry speeds and increased speed compliance was observed with an increasing level of penetration rate. For the effect of distance of upstream information, a similar effect was observed. When the distance was increased the mean speed lowered, section entry speed lowered, and speed compliance increased. No change was observed regarding the lateral behavior or Time Headway. As a result, it can be concluded that the cooperation between connected and automated vehicles and variable speed limits on motorways can be used to slow down unconnected vehicles more upstream, without inducing aggressive driving behavior in terms Time Headway and lane changing behavior.

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

Railways are facing the challenge to simultaneously increase the capacity and the operational performance of their network. Automatic train operation (ATO) can be one of the technologies to increase the capacity of the railway network. The specifications for ATO over the European Train Control System (ETCS) automatic train protection system have been defined. However, testing is taking place over legacy automatic train protection systems , such as ATBNG, as well. ATO requires information from the automatic train protection system. The goal of this master thesis is to determine the data gap between ETCS and ATBNG in relation to ATO. First a generic ATO model is developed from literature. This model presents the information required and produced by ATO. The model is used as a framework for the analysis of ATO over ETCS and ATO over ATBNG. This analysis resulted in a conceptual model of both ATO over ETCS and ATO over ATBNG. The conceptual model shows that ATBNG can provide the required information if the ATBNG operational envelope is used as the relevant safety envelope. However, currently the operational envelope of the NS’54 signalling system is the relevant safety envelope. Additional information is required to allow ATO to determine the NS’54 operational envelope. Furthermore, ATBNG is not capable of presenting ATO information to the train driver. A new ATO DMI is required. Moreover, the ProRail traffic management system is not yet capable of providing ATO with the required information for both ATO over ETCS and ATO over ATBNG. To validate the conceptual ATO over ATBNG model three case studies have been worked out. The study performed for this master thesis is an exploratory study, therefore validation of the findings and assumptions is required.