基于路径预测的不确定性推理组合地图匹配算法  

A Driver Route Prediction Based Map-matching Algorithm Integrating Uncertain Reasoning

作　　者：唐进君[1] 刘芳[1] 

机构地区：[1]内蒙古农业大学能源与交通工程学院,内蒙古呼和浩特010018

出　　处：《测绘学报》2010年第5期546-550,共5页Acta Geodaetica et Cartographica Sinica

摘　　要：提出一种新的基于预测的不确定性推理组合地图匹配算法。该方法首先利用云模型这样一种处理定性与定量间不确定转换的工具,通过对当前信息的不确定性推理,计算定位点相对于候选道路的匹配可信度。之后,利用隐马尔科夫模型预测驾驶员出行路径及目的地,通过对模型中的观察值函数重新设定,将路径预测信息与当前地图匹配算法结合,构建组合地图匹配算法。同时,采用学习算法更新模型中的信息。最后,通过仿真实例证明该组合算法的可行性与有效性。结果表明:该方法能够预测驾驶员行驶路径,起到预匹配的作用,提高地图匹配算法的精度。A novel integrated algorithm combining route prediction with uncertain reasoning was proposed.The cloud model,a powerful tool to perform uncertain converting between numerical quantitative analysis to conceptual qualitative analysis,was firstly used to calculate the credibility of positioning point to candidate roads by uncertain reference with current locating data.Then,a hidden Markov model（HMM）was built to predict the driver＇s routes and destinations.Through redesigning observation function in HMM,an integrated map matching algorithm was established by combining route predicting information with current matching approach.Additionally,the learning algorithm was carried out to support the algorithm and update the information.Finally,the experimental results demonstrate the feasibility and effectiveness of the proposed algorithm：it can predict a driver＇s routes to improve the accuracy of map matching algorithm according to the utility of pre-matching.

关 键 词：地图匹配算法 车辆导航 云模型 隐马尔科夫模型 驾驶员路径预测 

分 类 号：P208[天文地球—地图制图学与地理信息工程]