自主车辆避障安全路径的可达集建模

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (3): 526-533.

自主车辆避障安全路径的可达集建模

曹凯^1,2, 黄肖肖¹, 于云¹, 刘春¹

1.山东理工大学交通学院,山东淄博 255000;
2.山东英才学院计算机电子信息工程学院,山东济南 250104

收稿日期:2014-10-26 修回日期:2015-04-20 发布日期:2020-07-02
作者简介:曹凯(1965-),男,黑龙江哈尔滨,博士,副教授,研究方向为智能交通、车路协同、交通信息工程及控制。
基金资助:
国家自然科学基金资助项目(61573009);山东省自然科学基金(ZR2010FM007)

Modeling Method Based on Reachable Set for Safety Path in Autonomous Vehicle Obstacle Avoidance

Cao Kai^1,2, Huang Xiaoxiao¹, Yu Yun¹, Liu Chun¹

1. School of Traffic & Vehicle Engineering, Shandong University of Technology, Zibo 255000, China;
2. School of Computer and Electronic Information Engineering, Shandong Yingcai University, Jinan 250104, China

Received:2014-10-26 Revised:2015-04-20 Published:2020-07-02

摘要/Abstract

摘要： 针对传统的路径规划算法在车辆不确定行为状态方面存在的问题,提出将运动车辆视为在连续和离散模式间动态切换的混合系统,采用单一安全目标位置建模车辆避障最优轨迹,并基于多目标轨迹束建立安全状态可达集的建模方法。借此分析了车辆碰撞不可避免的条件,提出了车辆避障最优控制问题的松弛约束。仿真表明,该方法不仅可以规划车辆避障轨迹,还可以推断避障过程中车辆安全状态的可达范围,增强了系统对未来某一时间间隔内车辆状态安全的预测能力。

关键词: 安全路径, 道路交通, 混合系统, 可达集, 轨迹规划

Abstract: In view of problem in all possible uncertain behavior of vehicle unable existed by the traditional path planning algorithm, a modeling method was proposed which deemed a moving vehicle as a hybrid system switching dynamically between continuous and discrete mode, modeled an optimal trajectory for vehicle obstacle avoidance by using a single security target location, and built a safe state reachable set based on the trajectory beam of multiple security target locations. On this basis, the condition of the inevitable collision of vehicle was analyzed, and the optimal control problem with loose constraints for the vehicle obstacle avoidance was proposed. The simulation results show that the method can not only plan trajectories for vehicle avoiding obstacle, but also infer the reachable range of security state of vehicle,and the predictive power of vehicle state security is enhanced within a future time interval.

Key words: safety path, road traffic, hybrid systems, reachable set, trajectory planning

中图分类号:

曹凯, 黄肖肖, 于云, 刘春. 自主车辆避障安全路径的可达集建模[J]. 系统仿真学报, 2016, 28(3): 526-533.

Cao Kai, Huang Xiaoxiao, Yu Yun, Liu Chun. Modeling Method Based on Reachable Set for Safety Path in Autonomous Vehicle Obstacle Avoidance[J]. Journal of System Simulation, 2016, 28(3): 526-533.

参考文献

[1] Gonzalez-Rodriguez A G, Gonzalez-Rodriguez A. Collision-free motion planning and scheduling[J]. Robotics and Computer -Integrated Manufacturing (S0736-5845), 2011, 27(3): 657-665.
[2] Masoud A A.Motion planning with gamma-harmonic potential fields[J]. IEEE Trans on Aerospace and Electronic Systems (S0018-9251), 2012, 48(4): 2786-2801.
[3] Duan H, Huang L.Imperialist competitive algorithm optimized artificial neural networks for UCAV global path planning[J]. Neurocomputing (S0925-2312), 2014, 125(3): 166-171.
[4] Zhangqi W, Xiaoguang Z, Qingyao H.Mobile robot path planning based on parameter optimization ant colony algorithm[J]. Procedia Engineering (S1877-7058), 2011, 15(4): 2738-2741.
[5] Kala R.Multi-robot path planning using co-evolutionary genetic programming[J]. Expert Systems with Applications (S0957-4174), 2012, 39(3): 3817-3831.
[6] Hsieh H T, Chu C H.Improving optimization of tool path planning in 5-axis flank milling using advanced PSO algorithms[J]. Robotics and Computer-Integrated Manufacturing (S0736-5845), 2012, 29(6): 3-11.
[7] 邵杰, 杨静宇, 万鸣华, 等. 基于学习分类器的多机器人路径规划收敛性研究[J]. 计算机研究与发展, 2010, 47(5): 948-955.
[8] Tuncer A, Yildirim M.Dynamic path planning of mobile robots with improved genetic algorithm[J]. Computers & Electrical Engineering (S0045-7906), 2012, 38(11): 1564-1572.
[9] Das Sharma K, Chatterjee A, Rakshit A.A PSO-Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision-based robot navigation[J]. IEEE Trans on Instrumentation and Measurement (S0018-9456), 2012, 61(7): 1908-1914.
[10] Juang C F, Chang Y C.Evolutionary group based particle-swarm-optimized fuzzy controller with application to mobile robot navigation in unknown environments[J]. IEEE Trans on Fuzzy Systems (S1063-6706), 2011, 19(2): 379-392.
[11] 刘秉政, 曹凯. 自主车辆行为决策的安全验证方法[J]. 山东理工大学学报(自然科学版), 2011, 25(6): 6-12.
[12] 方敏, 张雅顺, 李辉. 混合系统的形式验证方法[J]. 系统仿真学报, 2006, 18(10): 2921-2924.
[13] R Baier, M Gerdts.A computational method for non-convex reachable sets using optimal control[C]// Proceedings of the European Control Conference (ECC) 2009, Budapest, Hungary. Holland: Elsevier, 2009: 97-102.
[14] 曹凯, 于少伟, 周芦芦. 基于动态目标位置的智能车辆控制研究[J]. 信息与控制, 2008, 37(4): 476-480.
[15] Gerdts M, Karrenberg S, Muller-Beßler B, et al.Generating Optimal Trajectories for an Automatically Driven Car[J]. Optimization and Engineering (S1389-4420), 2009, 10(4): 439-463.
[16] Baier R, Gerdts, M, Xausa I. Approximation of Reachable Sets using Optimal Control Algorithms[J]. Numerical Algebra, Control & Optimization (S2155-3289), 2013, 3(3): 519-548.