针对智能车辆在单交叉口环境下存在因冲突风险引起的碰撞率高和通行效率低的问题,提出一种基于局部博弈算法的路径规划算法。通过建立路口冲突风险模型分析存在的冲突风险,对车辆与行人的冲突提出消解方法;引入局部博弈理论,建立收益函数评价可行决策,求出在约束条件下纯策略纳什均衡的解,并对车辆速度进行规划,最终实现智能车辆的路径规划。仿真结果表明,提出的路径规划算法在不同车流量下相比于演化博弈和合作博弈算法交互成功率提升9.32%,通行效率平均提升33%,能有效缓解交通压力。
Aiming at the problems of high collision rate and low traffic efficiency caused by conflict risk of intelligent vehicles in single intersection environment, a path planning algorithm based on local game algorithm is proposed. By establishing the intersection conflict risk model, the conflict risk is analyzed, and the conflict resolution method between vehicles and pedestrians is proposed. The local game theory is introduced to establish the profit function to evaluate the feasible decision, and the solution of the pure strategy Nash equilibrium under the constraint condition is obtained. The vehicle speed is planned, and the path planning of the intelligent vehicle is finally realized. The simulation results show that the proposed path planning algorithm improves the interaction success rate by 9.32% compared with the evolutionary game and cooperative game algorithm under different traffic flows, and the traffic efficiency increases by 33% on average, which can effectively alleviate the traffic pressure.
[1] 高自友,吴建军. 出行者博弈、网络结构与城市交通系统复杂性[J].复杂系统与复杂性科学,2010,7(4):55-64.
GAO Z Y, WU J J. Travelers game, network structure and urban traffic system complexity[J]. Complex Systems and Complexity Science, 2010, 7(4): 55-64.
[2] SALAHUDDIN M A, AL-FUQAH A, GUIZANI M. Software-Defined networking for RSU clouds in support of the Internet of vehicles[J]. Internet of Things Journal IEEE, 2015, 2(2): 133-144.
[3] 陈慧岩,陈舒平,龚建伟. 智能汽车横向控制方法研究综述[J] ,兵工学报,2017,38(6):1203-1214.
CHEN H Y, CHEN S P, GONG J W. A review on the research of lateral control for intelligent vehicles[J]. Acta ArmamentarII, 2017, 38(6): 1203-1214.
[4] TANG G, TANG C Q, CLARAMUNT C, et al. Geometric a-star algorithm: an improved a-star algorithm for AGV path planning in a port environment[J]. IEEE Access, 2021, 9: 59196-59210.
[5] DOLGOV D, THRUN S, MONTEMERLO M, et al. Path planning for autonomous vehicles in unknown semi-structured environments[J]. The International Journal of Robotics Research, 2010, 29(5): 485-501.
[6] 李秀智,赫亚磊,孙炎珺,等. 基于复合式协同策略的移动机器人自主探索[J]. 机器人,2021,43(1):44-53.
LI X Z, HE Y L, SUN Y J,et al. Autonomous exploration of mobile robot based on compound cooperative strategy[J]. Robot, 2021, 43(1): 44-53.
[7] MOHAMMED H, ROMDHANE L, JARADAT M A. RRT* N: an efficient approach to path planning in 3D for static and dynamic environments[J]. Advanced Robotics, 2021, 35(3/4): 168-180.
[8] GAMMELL J D, SRINIVASA S S, BARFOOT T D. Informed RRT*: optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic[C] //2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Chicago,IL,USA: IEEE, 2014: 2997-3004.
[9] ZHAO C, LI L, PEI X, et al. A comparative study of state-of-the-art driving strategies for autonomous vehicles[J]. Accident Analysis & Prevention, 2021, 150: 105937.
[10] 高海龙,王炜,常玉林,等. 无信号交叉口临界间隙的理论计算模型[J]. 中国公路学报,2001(2):80-82.
GAO H L, WANG W, CHANG Y L, et al. A mathematical model for critical gap of unsignalized intersections[J]. China Journal of Highway and Transport, 2001(2): 80-82.
[11] 陈卓然,韩定定. 一类交通信息物理系统的动态路径引导[J]. 复杂系统与复杂性学,2022,19(1):81-87.
CHEN Z R, HAN D D. Dynamic route guidance strategy in transportation cyber-physical systems[J]. Complex Systems and Complexity Science, 2022, 19(1): 81-87.
[12] YANG Z, HUANG H, WANG G, et al. Cooperative driving model for non-signalized intersections with cooperative games[J]. Journal of Central South University, 2018, 25(9): 2164-2181.
[13] 郭蓬,吴学易,戎辉,等. 基于代价函数的无人驾驶汽车局部路径规划算法[J]. 中国公路学报,2019,32(6):79-85.
GUO P, WU X Y, RONG H,et al. Local path planning of driver less cars based on cost function[J]. Chan J Highw Transp, 2019, 32(6): 79-85.
[14] 马庆禄,聂振宇. 基于博弈论的无信号交叉口冲突消解方法[J]. 重庆理工大学学报:自然科学,2021,35(10):144-151.
MA Q L, NIE Z. Conflict resolution method based on game theory at unsignalized intersection[J]. Journal of Chongqing University of Technology (Natural Science), 2021, 35(10): 144-151.
[15] WANG H, MENG Q, CHEN S K, et al. Competitive and cooperative behaviour analysis of connected and autonomous vehicles across unsignalised intersections: a game-theoretic approach[J]. Transportation Research Part B: Methodological, 2021, 149: 322-346.
[16] ZHANG Y, TIAN F, SONG B, et al. Social vehicle swarms: a novel perspective on socially aware vehicular communication architecture[J]. IEEE Wireless Communications, 2016, 23(4):82-89.
[17] 孙启鹏,武智刚,等. 基于风险预测的自动驾驶车辆行为决策模型[J]. 浙江大学学报(工学版),2022,56(9):1761-1771.
SUN Q P, WU Z G, et al. Decision-making model of autonomous vehicle behavior based on risk prediction[J]. Journal of Zhejiang University (Engineering Science), 2022, 56(9): 1761-1771.
[18] 魏丽英,崔裕枫,李东莹. 基于演化博弈论的行人与机动车冲突演化机理研究[J]. 物理学报,2018,67(19):37-49.
WEI L Y, CUI Y F, LI D Y. Evolution mechanism of conflict between pedestrian and vehicle based on evolutionary game theory[J]. Acta Phys Sin, 2018,67(19):37-49.
