Abstract: In order to meet the requirement of high-level intelligent vehicles for lane recommendation, this paper has completed the mapping relationship between road and lane based on the correlation matching which is from standard definition map (SD-Map) and high-definition map (HD-Map), proposes the feasible domain space of road network, and the calculation rule of the comprehensive lane recommendation coefficient.Based on the remaining distance of road, lane speed limit and lane congestion information, a vehicle kinematics model is established, the speed space is defined by the dynamic window method (DWA) optimization algorithm, and a comprehensive cost function based on the remaining distance of the road, lane speed limit and lane congestion information is established, and the optimal lane recommendation list is obtained through iterative optimization. Finally, the optimization results are verified through the real vehicle test. Compared with the most recommended lanes based on the static map data, it can recommend lanes more effectively and flexibly based on the remaining distance from the destination, the lane speed limit and the lane congestion state, so as to ensure the optimal driving speed of the vehicle.effectively and flexibly based on the remaining distance from the destination, the lane speed limit and the lane congestion state, so as to ensure the optimal driving speed of the vehicle.

Key words: High precision map; Lane recommendation development; Road network model; SDMap; HD-Map; DWA

摘要： 为满足当前高阶智能化车辆对车道推荐引导的需求，文章基于车机导航地图（SD-Map） 和高精度地图（HD-Map）进行关联匹配，完成道路和车道的映射关系表达，提出了可行域空 间的路网模型和车道综合推荐系数的计算规则。基于行车道路剩余距离、车道限速和车道拥 堵信息，建立车辆运动学模型，使用动态窗口法（DWA）优化算法定义速度空间，建立以车 道路剩余距离、车道限速和车道拥堵信息为因子的综合成本函数，通过迭代优化获得最优车 道推荐列表。最后通过实车测试验证优化结果，与基于静态地图数据推荐的车道相比，能够 更加有效灵活地基于距离目的地剩余距离、车道限速情况和车道拥堵状态进行车道推荐，保 证车辆当前行车速度最优。

关键词: 高精度地图；车道推荐开发；路网模型；SD-Map；HD-Map；DWA