摘要
路径规划一直以来是自动驾驶汽车研究发展的关注点之一。路径规划根据环境信息掌握的全面性分为两个层次:全局路径规划和局部路径规划。文章详细介绍了这两个层次下的算法,并对6种主要算法进行了深入分析,旨在为自动驾驶汽车在各种环境中寻找最优路径提供理论支持和实践参考。全局路径规划侧重于利用高精度地图和定位系统确定从起点到终点的整体路线,而局部路径规划则侧重于实时环境数据,如由传感器提供的道路条件,以动态调整车辆行进路径,确保其符合运动学和动力学限制,遵守交通规则,并避免与障碍物碰撞。这两种规划方法的结合使自动驾驶汽车能够在复杂多变的道路环境中安全、高效地行驶。通过对这些算法的研究和总结,为自动驾驶汽车的路径规划问题提供了参考,有助于推动自动驾驶技术的发展和应用。
Path planning has always been one of the key focuses of the research and development of autonomous vehicles.Path planning is divided into two levels according to the comprehensiveness of environmental information:global path planning and local path planning.The paper introduces the algorithms at these two levels in detail and analyzes the six main algorithms in depth,aiming to provide theoretical support and practical reference for autonomous vehicles to find the optimal path in various environments.Global path planning focuses on using high-precision maps and positioning systems to determine the overall route from start to destination,while local path planning focuses on real-time environmental data,such as road conditions provided by sensors,to dynamically adjust the vehicle's path to ensure it complies with kinematic and dynamic constraints,obeys traffic rules,and avoids collisions with obstacles.The combination of these two planning approaches enables autonomous vehicles to operate safely and efficiently in complex and changing road environments.Through the research and summary of these algorithms,the paper provides a reference for the path planning problem of autonomous vehicles,which is helpful to promote the development and application of autonomous driving technology.
作者
岳旭生
李军
王耀弘
YUE Xusheng;LI Jun;WANG Yaohong(School of Mechatronics and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074,China;Chongqing Academy of Metrology and Quality Inspection,Chongqing 401121,China)
出处
《传感器世界》
2024年第3期1-8,共8页
Sensor World
基金
重庆市研究生联合培养基地(No.JDLHPYJD2018003)。
