自动驾驶汽车换道决策行为分析及分子相互作用势建模

Analysis of lane-changing decision-making behavior and molecular interaction potential modeling for autonomous vehicles

伴随智能网联环境的技术赋能,自动驾驶技术迎来新的发展阶段。为提高自动驾驶汽车的换道安全性与高效性,而对其换道决策机制进行研究。首先,通过系统相似性分析车辆与分子的相似性;其次,引入分子相互作用势建立换道模型,系统分析自动驾驶汽车的换道决策行为特性,有效认知换道车辆的交通场景;最后,运用SUMO平台将SL2015换道模型与分子相互作用势换道模型进行对比分析。结果表明,分子相互作用势换道模型下自动驾驶汽车运行速度的波动程度降低了15.45%,车辆通过数增加了5.93%,提升了换道的安全性与高效性。自动驾驶汽车换道决策行为的分子相互作用势建模综合考虑了交通环境中动态要素的相互作用关系,科学地展现了换道决策机制。

With the technological support of an intelligent networked environment,autonomous driving technology is ushering in a new stage of development.In order to improve the lane-changing safety and efficiency of autonomous vehicles,the lane-changing decision-making mechanism is studied.Firstly,the similarity between vehicle and molecule is explored through system similarity analysis.Secondly,the molecular interaction potential is introduced to establish a lane-changing model,which systematically analyzes the lane-changing decision-making behavior characteristics of autonomous vehicles and effectively recognizes the traffic scene of lane-changing vehicles.Finally,the SUMO platform is used to compare the SL2015 lane-changing model with the molecular interaction potential lane-changing model.The results show that under the molecular interaction potential lane-changing model,the speed fluctuation of autonomous vehicles is reduced by 15.45%and the number of passed vehicles is increased by 5.93%,which improves lane-changing safety and efficiency.The molecular interaction potential modeling of lane-changing decision-making behavior for autonomous vehicles comprehensively considers the interactional relationship between dynamic fac tors in the traffic environment and scientifically shows the lane-changing decision-making mechanism.