无人车多目标分配与路径规划双向优化

白礼婷; 刘旭磊; 周国峰; 彭忆强

doi:10.12382/bgxb.2025.0195

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无人车多目标分配与路径规划双向优化

更新时间：2026-04-24

- 无人车多目标分配与路径规划双向优化
- Bi-directional Optimization of Multi-target Task Allocation and Path Planning for Autonomous Vehicles
- 兵工学报 2026年47卷第3期页码：250195
- 作者机构：
  
  西华大学汽车与交通学院，四川成都 610039
  西华大学宜宾研究院，四川宜宾 644000
  四川省新能源汽车智能控制与仿真测试技术工程研究中心，四川成都 610039
  上海海洋大学工程学院，上海 201306
- 作者简介：
  
  通信作者邮箱：xuleiliu@mail.xhu.edu.cn
- 基金信息：
  
  汽车测控与安全四川省重点实验室基金(QCCK2024-003);汽车产业校企协同应用型人才培养项目(YBXH-2024-001)
- DOI：10.12382/bgxb.2025.0195
  中图分类号： TP242.6
- 收稿：2025-03-20，
  
  网络首发：2026-02-04，
  
  纸质出版：2026-03
- 稿件说明：
移动端阅览
白礼婷, 刘旭磊, 周国峰, 等. 无人车多目标分配与路径规划双向优化[J]. 兵工学报, 2026,47(3):250195.

BAI Liting, LIU Xulei, ZHOU Guofeng, et al. Bi-directional Optimization of Multi-target Task Allocation and Path Planning for Autonomous Vehicles[J]. Acta Armamentarii, 2026, 47(3): 250195.
白礼婷, 刘旭磊, 周国峰, 等. 无人车多目标分配与路径规划双向优化[J]. 兵工学报, 2026,47(3):250195. DOI： 10.12382/bgxb.2025.0195.

BAI Liting, LIU Xulei, ZHOU Guofeng, et al. Bi-directional Optimization of Multi-target Task Allocation and Path Planning for Autonomous Vehicles[J]. Acta Armamentarii, 2026, 47(3): 250195. DOI： 10.12382/bgxb.2025.0195.

摘要

目前，无人作战车辆已成为现代战争中重要的作战力量，两方对抗作战的关键在于实现合理的目标分配并寻求快速的接近打击。然而，由于战场环境复杂，存在目标分配不准确以及目标分配与路径规划之间的时间空窗期等问题。针对多目标分配与路径规划的协同优化问题，提出一种双向优化方法。该方法构建了考虑路径规划影响的目标任务分配模型，并引入贪心轮转算法对分配方案进行迭代优化，从而快速获取最优任务分配结果。在此基础上，采用改进的双向A*算法执行路径规划，通过将优化后的分配方案与路径规划深度融合，生成无人车的具体行驶路径。在大型障碍物及密集障碍物环境下的仿真实验表明，该双向优化算法在复杂场景中具有显著的优越性和有效性。

Abstract

In modern warfare

the unmanned combat vehicles have emerged as a critical operational force

and the success of adversarial engagements hinges on rational target allocation and rapid approach-and-strike capabilities. However

the battlefield environmental complexities introduce there are challenges such as inaccurate target allocation and a temporal gap between target allocation and path planning due to the complex battlefield environment. To address these issues

a bidirectional optimization method for target allocation and path planning is proposed. A target allocation model influenced by path planning is established

and the greedy rotation algorithm is employed to optimize the allocation plan

thereby rapidly obtaining optimal target allocation schemes. Subsequently

an improved bidirectional A

algorithm is used for path planning. The specific trajectories for the unmanned vehicles are determined by deeply integrating the optimized allocation plan with the planned paths. The autonomous vehicles are tested in simulated environments with large-scale obstacles and dense obstacle clusters. The test results demonstrate that the proposed bidirectional optimization algorithm method for target allocation and path planning exhibits significantly superior performance.

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references

刘兴宇,郭荣化,任成才,等.基于身份匈牙利算法的无人机蜂群分布式目标分配方法[J].兵工学报,2023,44(9):2824-2835.

LIU X Y,GUO R H,REN C C,et al. Distributed target allocation method for uav swarm based on identity hungarian algorithm[J]. Acta Armamentarii,2023,44(9):2824-2835. (in Chinese)

朱建文,赵长见,李小平,等.基于强化学习的集群多目标分配与智能决策方法[J].兵工学报,2021,42(9):2040-2048.

ZHU J W,ZHAO C J,LI X P,et al. Multi-target allocation and intelligent decision-making method for swarm based on reinforcement learning[J]. Acta Armamentarii,2021,42(9): 2040-2048. (in Chinese)

王俊森,石章松,徐慧慧,等.基于改进快速搜索树和合同网的多智能体目标分配算法[J].兵工学报,2025,46 (5):240743.

WANG J S,SHI Z S,XU H H,et al. Multi-agent target allocation algorithm based on improved rapidly-exploring random tree and contract net[J]. Acta Armamentarii,2025,46(5):240743. (in Chinese)

田洪清,马明涛,张博,等.越野环境下势场搜索树智能车辆路径规划方法[J].兵工学报,2024,45(7):2110-2127.

TIAN H Q, MA M T, ZHANG B, et al. Intelligent vehicle path planning method based on potential field-based search tree in off-road environments[J]. Acta Armamentarii,2024,45(7):2110-2127. (in Chinese)

张嘉辉,蒙志君,何家政,等.基于改进能量谷优化的多无人机空战目标分配[J].系统工程与电子技术,2024,46(11):3754-3763.

ZHANG J H, MENG Z J, HE J Z, et al. Multi-UAV air combat target allocation based on improved energy valley optimization[J]. Systems Engineering and Electronics,2024,46(11):3754-3763. (in Chinese)

WANG J F,JIA G W,LIN J C,et al. Cooperative task allocation for heterogeneous multi-UAV using multi-objective optimization algorithm[J]. Journal of Central South University,2020,27(2):432-448.

吴立冬,李宗璞,彭岳松,等.近距空中支援中无人机目标分配问题研究[J].空军工程大学学报,2024,25(3):86-93.

WU L D, LI Z P, PENG Y S, et al. Research on UAV target allocation in close air support[J]. Journal of Air Force Engineering University,2024,25(3):86-93. (in Chinese)

ZHANG Y J,ZHANG W J,MA Q H,et al. Multi-target optimized cooperative attack task allocation technology[C]∥Proceedings of 2021 IEEE International Conference on Artificial Intelligence and Industrial Design. Guangzhou,China:IEEE,2021:690-695.

CHEN Q H,ZHAO Q S,ZOU Z G. Threat-oriented collaborative path planning of unmanned reconnaissance mission for the target group[J]. Aerospace,2022,9(10):577.

GUO M,LONG T,LI H,et al. Reinforcement-learning-based path planning for UAVs in intensive obstacle environment[C]∥Proceedings of 2021 China Automation Congress. Kunming, China:IEEE,2021:6451-6455.

周同乐,陈谋,韩增亮,等.基于改进狼群算法的多无人机协同多目标分配[J].导航定位与授时,2022,9(05):46-55.

ZHOU T L,CHEN M,HAN Z L,et al. Multi-UAV collaborative multi-target allocation based on an improved wolf pack algorithm[J].Navigation,Positioning and Timing,2022,9(5):46-55. (in Chinese)

FAN J R,SUN H Y,SUN X,et al. Mission planning of MAV/UAV cooperative combat based on improved genetic algorithm[C]∥Proceedings of 2021 China Automation Congress. Kunming,China:IEEE,2021:3264-3269.

陈宇恒,陈进朝,陈雪聪.基于改进贪心算法的无人机集群协同任务分配[J].航空科学技术,2022,33(4):13-18.

CHEN Y H,CHEN J C,CHEN X C. UAV swarm collaborative task allocation based on an improved greedy algorithm[J]. Aeronautical Science and Technology,2022,33(4):13-18. (in Chinese)

GUO C,HUANG L,TIAN K. Combinatorial optimization for UAV swarm path planning and task assignment in multi-obstacle battlefield environment[J]. Applied Soft Computing, 2025:112773.

XU Z,LIU X,CHEN Q L. Application of improved astar algorithm in global path planning of unmanned vehicles[C]∥Proceedings of 2019 Chinese Automation Congress (CAC). Hangzhou,China:IEEE,2019:2075-2080.

TANG J,LIANG Y G,LI K B. Dynamic scene path planning of uavs based on deep reinforcement learning[J]. Drones, 2024, 8(2):60.

MA H C,YANG L W,ZHANG Y L,et al. Lateral maneuver a-star path planning algorithm of two UAV air combat confrontation[C]∥Proceedings of the 20235th International Conference on Artificial Intelligence and Computer Applications. Dalian, China: IEEE, 2023:22-27.

LIU H S,CHEN Q Y,PAN N,et al. Three-dimensional mountain complex terrain and heterogeneous multi-UAV cooperative combat mission planning[J]. IEEE Access,2020,8:197407-197419.

MIRZA I S,SHAH S S,SIDDIQI M Z,et al. Task assignment and path planning of multiple unmanned aerial vehicles using integer linear programming[C]∥Proceedings of TENCON 2023-2023 IEEE Region 10 Conference. Chiang Mai,Thailand:IEEE,2023:547-551.

YU T T, HUANG X, XU Z Y. Task assignment and planning model of multi-UAV cooperative operation based on fuzzy clustering algorithm[C]∥Proceedings of 2023 International Conference on Internet of Things, Robotics and Distributed Computing. Rio De Janeiro,Brazil:IEEE,2023.

刘钻东.基于目标意图预测的多无人机协同攻防智能决策[D].南京：南京航空航天大学,2020.

LIU Z D. Intelligent decision-making for multi-UAV cooperative attack and defense based on target intention prediction[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020. (in Chinese)

岳师光.面向计算机生成兵力的意图识别建模与推理方法研究[D].长沙：国防科学技术大学,2016.

YUE S G. Research on intent recognition modeling and inference methods for computer-generated forces[D]. Changsha:National University of Defense Technology,2016. (in Chinese)

董彦非,冯惊雷,张恒喜.多机空战仿真协同战术决策方法[J].系统仿真学报,2002,14(6):723-725.

DONG Y F,FENG J L,ZHANG H X. Method for collaborative tactical decision-making in multi-aircraft air combat simulation[J].Journal of System Simulation,2002,14(6):723-725. (in Chinese)

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