Study on Mixed Traffic Flow Characteristics in an Expressway Environment Considering Illuminance Effects

Abstract

This study examines the influence of illuminance on car-following characteristics in mixed traffic flow. We selected an expressway tunnel with a large variation in illuminance and designed a real vehicle test to explore the influence of changes in tunnel illuminance on car-following characteristics. The load factor of vehicle recognition based on the critical speed of illuminance change is introduced to correct the delay time of adaptive cruise control vehicle recognition. The continuous cellular automata model was used to simulate a mixed traffic flow. The characteristics of the mixed traffic flow under the influence of illuminance are analyzed for traffic efficiency, stability, and safety. The results show that changes in illuminance cause vehicle speeds to diminish at tunnel entrances and exits while following distances increase. Inside the tunnel, however, vehicle speeds and following distances remain relatively stable. As connected autonomous vehicles (CAV) become more common, the maximum flow and average speed in expressway tunnels increase. In addition, the time to collision (TTC) value increases gradually, while the time exposed rear collision risk index (TERCRI) decreases gradually. When CAV penetration exceeds 80%, the speed-density curve is smoother, the vehicle motion state is close to a straight line on a certain slope, and the position of deceleration is less, which is close to the ideal state of stable driving. This study could have a positive impact in reducing the speed fluctuation of vehicles in expressway tunnels, improving the efficiency of traffic, and preventing rear-end crashes in mixed traffic flow environments.