Cooperative Driving in Mixed Traffic: An Infrastructure-Assisted Approach

Abstract

Automated driving in urban traffic requires extensive information from the surroundings. The most promisring approach to facilitate automated driving in mixed traffic is platooning of connected and automated vehicles (CAV). In this research, we investigate a human-leading strategy (HL) by which CAVs drive in platoons with the CAV leading the platoon driven by a human. We thoroughly formulate the problem of managing CAV platoons by the HL strategy, systematically model the platoon dynamics and the traffic system, as well as propose two approaches to implement this strategy. By conducting experiments in a simulation framework that combines the traffic and the communication network, the implementation of the HL strategy is evaluated with the consideration of travel time, automated driving experience, and communication reliability. The simulation results revealed that the HL strategy makes it feasible for CAVs to drive in automated mode in an urban mixed traffic network, while its performance relies on the CAV penetration rate and communication reliability. In addition, the results suggest that the performance of the HL strategy can be significantly improved by approaches that allow uninterrupted platooning and result in stable platoon dynamics.

Keywords

• CAV management
• platoon dynamics
• vehicular communication
• traffic system modeling