Analysis on the Heterogeneity of Proximity Resistance in Car Following

Abstract

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.