Research on Merging Strategies of Connected and Autonomous Vehicles Based on the Game Theory under On-ramp Scenarios

How to make vehicles run efficiently under safe conditions is one of important research topics in the field of transportation. The development of connected and autonomous vehicles (CAVs) could improve the driving efficiency with intelligence of CAVs. In this study, we firstly analyze several typical vehicles merging scenes, and establish driving models during the merging process. Then, this paper takes a typical on-ramp merging scene as an example, and proposes a vehicle merging strategy based on improved cooperative game theory. Finally, by quantifying the safety and efficiency of vehicle traffic, and assigning them different weights, simulation experiments verify the effectiveness of a vehicle merging strategy in improving traffic efficiency. Taking the trajectory of the vehicles and the average travel time of all vehicles as the output result, comparing with the vehicle merging model controlled by the fixed timing of traffic lights, the result shows that the vehicle merging strategy based on improved cooperative game theory can significantly improve traffic efficiency. Especially, under the test of different traffic flows, the average travel time of all vehicles increased by 10.95%. The merging strategy based on improved cooperative game theory can contribute to solve traffic conflict in the future.