摘要
车辆GPS轨迹的地图匹配是交通大数据挖掘中的一项重要的基础性工作,可靠的轨迹匹配结果对于道路交通运行状态监测、实时交通信息发布、车辆定位与智能调度、出行路径选择行为分析等具有重要意义。由于城市道路网络中大量存在高架路、主辅路和立体交叉等复杂的道路场景,传统的地图匹配算法在这些场景下难以对车辆轨迹进行准确匹配。针对这一问题,该文提出一种基于道路网络拓扑结构的轨迹匹配算法,将轨迹匹配问题转换为在加权道路网络中寻找最优路径的问题。利用成都市道路网络中上万辆出租车的实际运行轨迹数据对本文算法进行了验证,结果表明在复杂的城市道路网络中应用该算法能够获得较高的匹配成功率和准确率。
Map-matching for GPS trajectories is a key groundwork in mining transportation data. Reliable matching results are significant for monitoring traffic situation, publishing real-time transportation information, vehicle tracking, smart vehicle dispatching, and routing behavior analysis. In real urban road networks, there are numerous complicated road structures such as elevated roads, frontage roads, and interchange bridges. Traditional map-matching algorithms could not match trajectories on these structures accurately. In this paper, we propose a map-matching algorithm based on the topological structure of the road networks and transform the problem of matching GPS trajectories in road map into the problem of finding the shortest path in a weighted road network. We test the algorithm with the real data of GPS trajectories of tens of thousands of taxis in Chengdu. The results show that the presented algorithm can acquire a high success ratio and accuracy ratio in complicated urban road networks.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2016年第6期1008-1013,共6页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(61304177,71671015)
四川省教育厅科研项目(15ZB0345)
关键词
GPS轨迹
地图匹配
道路网络
出租车
GPS trajectories
map-matching algorithm
road networks
taxi
