检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]上海汽车集团股份有限公司,上海200041 [2]武汉中海庭数据技术有限公司,湖北武汉430200 [3]武汉光庭信息技术股份有限公司,湖北武汉430073
出 处:《地理空间信息》2018年第5期53-56,共4页Geospatial Information
基 金:测绘地理信息公益性行业科研专项资助项目(201512007)
摘 要:首先分析了国内外高精度地图车道模型的研究现状,针对车道模型在自动驾驶中的融合应用,提出了一种基于车道驾驶态势的拓扑构建和路径规划方法。车道驾驶态势是指在遵循正确交通规则的前提下驾驶车辆通过车道后将达到的空间方位和通行状态。利用车道驾驶态势可生成车道级可通行区间集合,并构建可通行区间之间的拓扑关系,再利用Dijkstra算法可进行最优路径规划。可通行区间内部通过驶入和驶出接口点列表达可任意变道的拓扑关系,快速完成车道级路径规划,为自动驾驶多源数据融合与二次规划提供基础参考。We analyzed the global research about lane model of HAD map in this paper. Aimed at the application of lane model in autonomous driving, we proposed a topology construction and route planning method based on lane driving condition. Lane driving condition refers to space orientation and traffic situation of the vehicle when driving through the lane at the correct traffic rules. Firstly, we used lane driving condition to generate the lane-level range of passable zone, and then built the topological relationship between passable zones. In the end, we used Dijkstra algorithm to optimize route planning. Within the passable zone, the topological relationship could be achieved by entering and exiting interface points to describe that vehicle could change lane in any position of the zone. So lane-level route planning could be quickly completed, which could provide the basic reference for multi-source data fusion and second planning of autonomous driving.
分 类 号:P208[天文地球—地图制图学与地理信息工程]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.12.34.36