A Collision Avoidance Model for On-Ramp Merging of Autonomous Vehicles

Connected and autonomous vehicles (CAVs) have the ability to enhance traffic flow and road safety by significantly reducing human error. Although some collision risks may be eliminated in autonomous vehicles, other potential risks remain, especially at on-ramp merging areas. This paper proposes a collision avoidance model for on-ramp merging of autonomous vehicles under different scenarios. Simulation results suggest that the proposed method can reduce the risks of collision at on-ramp merging areas. Moreover, we assessed the effectiveness of the strategy in terms of traffic flow speed variations with different penetration rates of CAVs. Results show that the collision avoidance strategy leads to lower speed variations. This study reveals that the information obtained from the proposed collision avoidance model could be helpful for improving traffic safety and enhancing urban mobility.