计及车辆信息的隐马尔可夫地图匹配优化算法
Hidden Markov Map Matching Optimization Algorithm Considering Vehicle Information
滕志军 1皇甫泽南 2王安晨2
作者信息
- 1. 东北电力大学,现代电力系统仿真控制与绿色电能新技术教育部重点实验室,吉林 132012
- 2. 东北电力大学,电气工程学院,吉林 132012
- 折叠
摘要
为解决车辆在路况重叠的高架区域进行地图匹配时信号传输受到遮挡,导航易出现误匹配、输出时延增加和车道偏移等现象的问题,提出计及车辆信息的隐马尔可夫地图匹配优化算法.首先,剔除采样数据中冗余和漂移的定位点;然后,确定候选道路时生成网格索引,利用道路拓扑删除不相连道路,减少计算量、降低输出时延;最后,利用道路和车辆信息生成可信度函数,融合速度相似性改进转移概率,确定匹配路段.试验结果表明,车辆行驶至高架区域时,所提出算法匹配时间更短,时长未随路段的增多而增加,且具有较高准确率,满足车辆在三维区域的匹配需求.
Abstract
The signal transmission is obscured when vehicles are matched in elevated areas,and navigation is prone to mismatching,increased output latency and lane drift,etc..To address such navigation defects,this paper proposes the hidden Markov map matching optimization algorithm with vehicle information.The algorithm eliminates redundant and drifting localization points in the sampled data;generates a grid index when determining the candidate roads,and uses the road topology to delete unconnected roads to reduce the computation and output delay;generates a confidence function using the road and vehicle information,and improves the transfer probability by fusing the speed similarity to determine the matching road sections.The experimental results show that the matching time is shorter when the vehicle drives to the elevated area,and the duration does not increase with the increase of road sections;and it has a high accuracy rate to meet the matching demand of vehicles in the 3D area.
关键词
城市路网/隐马尔可夫模型/地图匹配/车辆信息Key words
Urban road network/Hidden Markov model/Map matching/Vehicle information引用本文复制引用
出版年
2024
NETL
NSTL
万方数据