复杂场景下二阶HMM的自适应地图匹配算法  

Adaptive map matching algorithm using second-order hidden Markov models for complex scenarios

作　　者：郭思雨 郭圆 李必军[1] 吴超仲[3] GUO Siyu;GUO Yuan;LI Bijun;WU Chaozhong(State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;School of Resources and Environmental Engineering,Wuhan Polytechnic University,Wuhan 430070,China;Wuhan Polytechnic University,Wuhan 430070,China)

机构地区：[1]武汉大学测绘信息遥感工程全国重点实验室,湖北武汉430079 [2]武汉理工大学资源与环境工程学院,湖北武汉430070 [3]武汉理工大学,湖北武汉430070

出　　处：《测绘通报》2025年第3期93-98,共6页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(52332010)。

摘　　要：随着城市交通系统的复杂性显著上升,现有地图匹配方法在处理交叉路口、高架遮挡等复杂城市交通场景时仍面临较大的挑战。针对上述问题,本文提出了一种针对复杂城市道路的地图匹配算法。首先,通过方向性和连通性两部分特征,量化匹配过程中轨迹点所处路网场景的复杂程度并实现轨迹分段;然后,对简单轨迹使用加入方向约束的隐马尔可夫模型进行匹配,对复杂轨迹段则采用二阶模型,利用路网复杂度作为权值参数自适应地调整HMM中观测概率和转移概率的权重比,提高复杂路网的地图匹配精度和效率;最后,与传统HMM方法和ST-Matching方法的匹配结果进行对比。结果表明,本文算法在复杂场景下的匹配准确率分别提高了5.4%和6.0%,具有更高的匹配效率。As the complexity of urban transportation systems has significantly increased,existing map matching methods still face considerable challenges in handling complex urban traffic scenarios such as intersections and overpass obstructions.To address these issues,we propose a map-matching method tailored for complex urban road networks.Firstly,through the features of directionality and connectivity,we quantify the complexity of the road network scene where trajectory points reside and achieve trajectory segmentation.Then,for simple trajectories,we use a direction-constrained hidden Markov model(HMM)for matching,while for complex trajectory segments,a second-order model is adopted that uses the complexity of the road network as a weighting parameter to adaptively adjust the ratio of observation probabilities and transition probabilities in the HMM,improving the accuracy and efficiency of map matching in complex road networks.Finally,we compare traditional HMM methods with the ST-Matching method.The results show that the proposed algorithm improves matching accuracy by 5.4%and 6.0%respectively in complex scenarios and has higher matching efficiency.

关 键 词：路网复杂度 隐马尔可夫模型 地图匹配 自适应算法 

分 类 号：P208[天文地球—地图制图学与地理信息工程]