Abstract:

In order to study the impact mechanism of human-machine mixed driving traffic flow composed of Human-Driven Vehicle (HDV) and Connected and Automated Vehicle (CAV) under occasional accident, this paper improves the cellular automata rules under the framework of the KKW model, and introduces the synchronization factor to consider the CAV human-like driving strategy, and constructs the HDV and CAV following rules for different following modes. Based on the demand of vehicle lane-changing in accident scenarios, it constructs the free lane-changing strategy of HDV and CAV multi-lane considering the willingness to choose the intermediate lanes, and establishes the mandatory lane-changing rule considering the pressure of lane-changing. And after numerical simulation, it analyzes the different traffic volumes, CAV penetration rates, CAV accident information sensing ranges and CAV human-like driving strategy on traffic flow. The results show that the increase of CAV can effectively alleviate the congestion of traffic flow after occasional accidents and limit the spatial and temporal scope of congestion. In the case of medium and high traffic volume with CAV penetration rate greater than 0.4, with the increase of CAV accident information sensing range, the congestion space in the merging area is gradually dispersed, and traffic efficiency is improved. With the transition of the CAV human-like driving strategy from aggressive to conservative, the flow of the human-machine mixed driving traffic flow is gradually reduced, and the range of slow queues expands, traffic congestion gradually worsens, and the trend of speed fluctuations in each lane gradually converges over time.

Key words: traffic engineering, occasional accident, cellular automata; human-machine mixed driving traffic flow