网联混合车流车辆换道博弈行为及模型

车联网环境中,交通系统将长期呈现智能网联汽车和传统人工驾驶车辆混合共存的状况.针对智能网联交通环境下的新型混合车流,建立了车辆的换道行为决策模型.对于混合车辆交通流引入最小安全区域模型,自主车辆交通流基于博弈论的思想进行建模.自主车辆之间的换道被看作为1种非合作博弈行为,车辆以自身行驶状态为博弈收益,寻求行驶条件更优的车道.运用SUMO软件对提出的换道模型进行仿真验证分析.仿真结果表明,博弈换道模型相比于传统间隙阈值接受模型具有较高的车道利用率和安全稳定性.

Modeling Lane-Changing Behavior in Mixed Traffic Flow Connected Environment based on Game Theory

On the Internet of Vehicles environment, the transportation system will present a long-term coexistence of intelligent, connected cars and traditional manual driving vehicles. Proposed to establish vehicles for new hybrid traffic under intelligent, connected traffic based on the optimal speed of vehicles under different driving styles. Decision-making model of lane change behavior. For the mixed vehicle traffic flow, introducing the minimum safe area model, autonomous vehicle traffic flow is modeled based on the idea of game theory. Lane changing between autonomous vehicles is regarded as a kind of non-cooperative game behavior. Vehicles use their driving status as game revenue to find a lane with better driving conditions. The SUMO software was used to simulate and analyze the lane change model proposed in this paper. Compared with the simulation results, the game lane change model has a higher lane utilization rate and safety, stability than the traditional clearance threshold acceptance model.