北京出租车GPS轨迹数据地图匹配算法研究
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摘要
由于车辆位置数据匹配到电子地图时,会出现车辆轨迹偏离实际道路的情况,为了提高出租车GPS轨迹数据匹配到地图的准确率,提出一种出租车地图匹配算法:基于GPS定位精度的距离范围和车辆行驶方向与道路方向的夹角区间确定候选路段,依据车辆的速度确定方向权重,计算距离和方向的综合权重值进行轨迹点匹配,通过最短路径算法进行行驶轨迹的选择,并采用北京市西二环周围100辆出租车24860条GPS数据进行实验验证。实验表明该匹配算法的匹配正确率可达到96.72%。其具有地图匹配的准确性。
The purpose is to improve the accuracy of map matching, based on taxi track data. Due to the vehicle trajectory deviates from the actual driving road when the GPS position data is displayed on the electronic map. Based on the track data, an algorithm for map matching is studied. The method is as follow: the algorithm includes candidate road determination based on distance range of GPS positioning accuracy and angle range between vehicle driving direction and road direction. Then determining directional weight based on vehicle speed range Direction weights based on vehicle speed range. Then the trajectory points are matched by calculating the comprehensive weights of distance and direction. Finally do the selection of travel path through shortest path algorithm. And the article adopts the data of 100 taxis around the West Second Ring Road in Beijing were tested for 24860 GPS data. Experiments show that the matching accuracy of the matching algorithm proposed by the author can reach 96.72%. The conclusion is that the algorithm satisfies the matching accuracy.
The purpose is to improve the accuracy of map matching, based on taxi track data. Due to the vehicle trajectory deviates from the actual driving road when the GPS position data is displayed on the electronic map. Based on the track data, an algorithm for map matching is studied. The method is as follow: the algorithm includes candidate road determination based on distance range of GPS positioning accuracy and angle range between vehicle driving direction and road direction. Then determining directional weight based on vehicle speed range Direction weights based on vehicle speed range. Then the trajectory points are matched by calculating the comprehensive weights of distance and direction. Finally do the selection of travel path through shortest path algorithm. And the article adopts the data of 100 taxis around the West Second Ring Road in Beijing were tested for 24860 GPS data. Experiments show that the matching accuracy of the matching algorithm proposed by the author can reach 96.72%. The conclusion is that the algorithm satisfies the matching accuracy.
引文
[1] 张鹏飞,徐泮林.多系统GNSS在弱信号环境下比较研究与精度评估[J].北京测绘,2018,32(8):905-909.
[2] 赵小平,刘文龙,陈恒美.GPS/GSM车辆定位跟踪系统中电子地图匹配问题[J].北京测绘,2003(3):32-34.
[3] 付梦印,李杰,邓志红.一种适于车辆导航系统的快速地图匹配算法[J].北京理工大学学报,2005,25(3):225-229.
[4] 张小国,王庆,万德钧.基于路网拓扑特性及先验知识的地图匹配算法[J].东南大学学报 (自然科学版),2006,36(4):625-629.
[5] 唐进君,刘芳.基于路径预测的不确定性推理组合地图匹配算法[J].测绘学报,2001,39(5): 546-550.
[6] 苏海滨,土光政,土继东.基于模糊神经网络的地图匹配算法[J].北京科技大学学报,2012(1):43-47.
[7] ZHANG T, YANG D G, LI K Q, et al. Fuzzy Map-matching Algorithm with Confidence Feedback for Vehicle Navigation[J].Tsinghua Univ Sci Technol,2009,49(2):277.
[8] XU H, LIU H C, TAN C W, et al. Development and Application of an Enhanced Kalman Filter and Global Positioning System Error-correction Approach for Improved Map-matching[J].Intell TranspSyst,2010,14(1):27.
[9] ZELENKOV A V. Calculation of the Parameters of Hidden Markov Models Used in the Navigation Systems of Surface Transportation for Map Matching: a review[J].Autom Control Comput Sci,2010,44(6):309.
[10] NEWSON P, KRUMM J. Hidden Markov Map Matching through Noise and Sparseness[C]Proceedings of the 17th ACM Sigspatial International Conference on Advances in Geographic Information Systems. Seattle, Washington: ACM, 2009.
[11] LOU Yin, ZHANG Chengyang, ZHENG Yu, et al. Map-Matching for Low-Sampling-Rate GPS Trajectories[C]//Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, Washington, ACM, 2009:352-361.
[12] WANG Meiling, CHENG Lin. Study on Map-matching Algorithm for Floating Car[J]. Acta Geodaetica et Cartographica Sinica,2012,41(1):133-138.
[13] 李清泉, 黄练. 基于GPS轨迹数据的地图匹配算法[J].测绘学报,2010,39(2):207-212.
[14] 章威,徐建闽,林绵峰. 基于大规模出租车数据的地图匹配算法[J].交通运输系统工程与信息,2007,7(2):39-45.
[15] 李清泉,胡波,乐阳.一种基于约束的最短路径低频出租车载数据地图匹配算法[J].武汉大学学报(信息科学版),2013,38(7):805-808.
[16] 曾喆,李清泉,邹海翔,万剑华.曲率积分约束的GPS出租车地图匹配方法[J]. 测绘学报,2015,44(10):1167-1176.
[17] 黄亦峰.基于GPS的地图匹配算法研究[J].电子科技,2017,30(6):54-56.
[18] VELAGA N R, QUDDUS M A, Bristow A L. Developing an Enhanced Weight-based Topological Map-matching Algorithm for Intelligent Transport Systems[J]. 2009, 17(6):672-683.
[2] 赵小平,刘文龙,陈恒美.GPS/GSM车辆定位跟踪系统中电子地图匹配问题[J].北京测绘,2003(3):32-34.
[3] 付梦印,李杰,邓志红.一种适于车辆导航系统的快速地图匹配算法[J].北京理工大学学报,2005,25(3):225-229.
[4] 张小国,王庆,万德钧.基于路网拓扑特性及先验知识的地图匹配算法[J].东南大学学报 (自然科学版),2006,36(4):625-629.
[5] 唐进君,刘芳.基于路径预测的不确定性推理组合地图匹配算法[J].测绘学报,2001,39(5): 546-550.
[6] 苏海滨,土光政,土继东.基于模糊神经网络的地图匹配算法[J].北京科技大学学报,2012(1):43-47.
[7] ZHANG T, YANG D G, LI K Q, et al. Fuzzy Map-matching Algorithm with Confidence Feedback for Vehicle Navigation[J].Tsinghua Univ Sci Technol,2009,49(2):277.
[8] XU H, LIU H C, TAN C W, et al. Development and Application of an Enhanced Kalman Filter and Global Positioning System Error-correction Approach for Improved Map-matching[J].Intell TranspSyst,2010,14(1):27.
[9] ZELENKOV A V. Calculation of the Parameters of Hidden Markov Models Used in the Navigation Systems of Surface Transportation for Map Matching: a review[J].Autom Control Comput Sci,2010,44(6):309.
[10] NEWSON P, KRUMM J. Hidden Markov Map Matching through Noise and Sparseness[C]Proceedings of the 17th ACM Sigspatial International Conference on Advances in Geographic Information Systems. Seattle, Washington: ACM, 2009.
[11] LOU Yin, ZHANG Chengyang, ZHENG Yu, et al. Map-Matching for Low-Sampling-Rate GPS Trajectories[C]//Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, Washington, ACM, 2009:352-361.
[12] WANG Meiling, CHENG Lin. Study on Map-matching Algorithm for Floating Car[J]. Acta Geodaetica et Cartographica Sinica,2012,41(1):133-138.
[13] 李清泉, 黄练. 基于GPS轨迹数据的地图匹配算法[J].测绘学报,2010,39(2):207-212.
[14] 章威,徐建闽,林绵峰. 基于大规模出租车数据的地图匹配算法[J].交通运输系统工程与信息,2007,7(2):39-45.
[15] 李清泉,胡波,乐阳.一种基于约束的最短路径低频出租车载数据地图匹配算法[J].武汉大学学报(信息科学版),2013,38(7):805-808.
[16] 曾喆,李清泉,邹海翔,万剑华.曲率积分约束的GPS出租车地图匹配方法[J]. 测绘学报,2015,44(10):1167-1176.
[17] 黄亦峰.基于GPS的地图匹配算法研究[J].电子科技,2017,30(6):54-56.
[18] VELAGA N R, QUDDUS M A, Bristow A L. Developing an Enhanced Weight-based Topological Map-matching Algorithm for Intelligent Transport Systems[J]. 2009, 17(6):672-683.