Travelling to work is one of the essential activities in individuals’ daily lives. However, commuters who depend on public transport often face significant challenges in accessing job opportunities, resulting in transport-related social exclusion risks. In recent years, shared mobility services have gained popularity as a solution, offering greater flexibility in first/last-mile segments of multimodal trips. These services have promising potential to improve accessibility for those who rely on public transport, thereby addressing issues of accessibility inequity. Such an intervention aligns well with the unique Dutch cycling culture, where cycling already accounts for a substantial portion of transit journeys. However, limited bike availability at the egress side diminishes the utilization of bikes for the last mile of a trip. To address this issue, integrating shared bikes with transit as an egress mode could be an effective intervention.

This thesis conducted a ”what-if analysis” in the Amsterdam Transport Region to investigate the impacts on job accessibility for different commuters and the equity of the whole transportation system if shared bikes are provided at transit stations as the egress mode. The results highlight the considerable potential of this integration in improving job accessibility and promoting social equity.

Implications drawn from the analysis provide valuable insights. Statistically, groups without car access can benefit more than groups with car access from integrating transit and shared bikes, but benefits might favour high-income groups. Geographically, accessibility improvements are mainly distributed to commuters living next to transit stations, while equity improvements are concentrated in areas with dense and developed public transport systems. Additionally, commuters living close to transit stations are more likely to contribute significantly to the overall accessibility deficiency, even though they have convenient first-mile segments. These implications guide policymakers in prioritizing interventions for targeted groups or regions, and facilitating the creation of a more equitable transportation system.

Car-following behaviour is a fundamental element for vehicle manoeuvre. The heterogeneity among driving behaviour has gained significant importance since some researchers argued that it might be relevant to capacity drop and traffic oscillations. Driver space is an area around a vehicle, and drivers will feel a rapid increase in discomfort when their comfort boundary is intruded. The response intensity of discomfort caused by spatial intrusion is represented by proximity resistance. With the development of Advanced Driver Assistance Systems (ADAS), it is crucial for drivers to feel comfortable within the implemented system. Therefore, understanding the heterogeneity of driver space has enormous potential to develop better customised ADAS. This report aims to analyse the impacts of heterogeneity on proximity resistance in car-following. The HighD dataset was processed to differentiate car-following driving styles for cars and trucks through the k-means clustering methodology. After successfully inferring the proximity resistance for each driver at each frame, the impacts of heterogeneity on proximity resistance in terms of different traffic states, vehicle types and driving styles were analysed. The results show that these three heterogeneities have different extent impacts on the proximity resistance of different drivers in car following. This study is beneficial for further investigations on the potential reasons for heterogeneous proximity resistance and the development of personalised car-following models.