Abstract:

In order to improve driving safety in foggy weather, with a section of smart freeway as a research object, changes in driving behaviors under mixed traffic flow were analyzed, including decrease of safe speed, degradation of CAVs driving mode, and conservative lane-changing due to decrease in visibility. Then, a CAM of one-way freeway was established, where rules of longitudinal car-following and lateral lane-changing were designed. Finally, the model was validated through simulation, and traffic flow characteristics and accident probabilities were analyzed. The results indicate that under light fog, medium fog, heavy fog and dense fog conditions, the degradation ratios of CAVs are 52.3%, 60%, 63%, and 67.3%, lane-changing times during two hours are 161, 131, 104.3 and 69 (×10² veh), maximum free flow velocity is 90, 76.8, 62.6 and 46.8 km/h, and critical density is 42, 40, 38 and 36 veh/km, respectively, and they become more and more obvious with the decrease of permeability. Moreover, accident probability decreases greatly with increase of permeability, and it reduces by at least 52.9% when penetration reaches 50% compared to HVs environment.

Key words: freeway, foggy weather, connected and automated vehicles (CAVs), human vehicles (HVs), cellular automaton model (CAM), mixed traffic flow