Research on the Safety Characteristics of Mixed Traffic Flow under Different Penetration Scenarios of Autonomous Vehicles

Abstract

Since it will take time for vehicles to be fully automated, research on mixed traffic flow with different levels of vehicles will be the focus in the future. This paper takes L0, L1, L2, L3, L4, L5 vehicles as the research object, selects the Intelligent Diver Model (IDM), Adaptive Cruise Control (ACC) model, F-STCA model and LC2013 model to construct the vehicle's driving behaviour model, builds SUMO (Simulation of Urban Mobility) and Python co-simulation platform to conduct models simulation verification and safety analysis. The results show that: (1) The improved IDM model can realize the error caused by the heterogeneity of driver's personality; the improved ACC model can improve speed and keep a small change range with the interfering vehicle; the improved F-STCA model can expand the vehicle's lane-changing intention and reflect the driver's driving uncertainty. (2) The increase of penetration can increase the number of lane changes in basic sections, but in merging area, they are proportional at low density and inversely proportional at high density; penetration can reduce the occurrence of traffic conflicts and change the distribution of Time-To-Collision (TTC). This paper can predict the evolution law of traffic flow under the new technology, and provide a reference for future traffic planning and management.

Keywords

• driving behaviour model
• mixed traffic flow
• penetration
• SUMO