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基于D-S证据推理的车辆导航系统地图匹配算法
引用本文:毕军,付梦印,张宇河. 基于D-S证据推理的车辆导航系统地图匹配算法[J]. 北京理工大学学报, 2002, 22(3): 393-396. DOI: 10.3969/j.issn.1001-0645.2002.03.035
作者姓名:毕军  付梦印  张宇河
作者单位:北京理工大学,自动控制系,北京,100081
摘    要:研究地图匹配算法中的匹配道路的选择问题,提出基于D-S证据推理理论的地图匹配算法.根据D-S证据推理的基本原理,结合车辆行驶情况,给出当前时刻车辆位置信息和方向信息的基本概率分布函数的设计方法.按照D-S合成公式,对位置和方向信息进行融合,并根据融合结果选择匹配道路.在设计方法中,引入位置信息和方向信息的可靠性参数.仿真结果表明,该方法是行之有效的,通过适当地调整可靠性参数的值,就能识别出车辆所在的道路.

关 键 词:D-S证据推理  地图匹配  车辆导航  数据融合
文章编号:1001-0645(2002)03-0393-04
收稿时间:2002-01-17
修稿时间:2002-01-17

A Map Matching Algorithm for Vehicle Navigation Systems Based on Dead Reckoning (D-S) Evidence Reasoning
BI Jun,FU Meng yin and ZHANG Yu he. A Map Matching Algorithm for Vehicle Navigation Systems Based on Dead Reckoning (D-S) Evidence Reasoning[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2002, 22(3): 393-396. DOI: 10.3969/j.issn.1001-0645.2002.03.035
Authors:BI Jun  FU Meng yin  ZHANG Yu he
Affiliation:Dept. of Automatic Control, Beijing Institute of Technology, Beijing100081, China;Dept. of Automatic Control, Beijing Institute of Technology, Beijing100081, China;Dept. of Automatic Control, Beijing Institute of Technology, Beijing100081, China
Abstract:Selection of matching road as a part of map matching algorithm is studied. A map matching algorithm based on dead reckoning (D S) evidence reasoning is proposed. According to the principle of D S evidence reasoning and the vehicle's running status, the basic probability assignment function for vehicle's information on position and direction at the moment is designed. According to the D S combination formula, the fusion of position and direction information is made, and the fusion result is used to select the road matching. Reliability parameters on the position and direction information are introduced in the design. Simulation results show that the method is effective and can recognize the road on which the vehicle is running, if the value of reliability parameters is suitably adjusted.
Keywords:D S evidence reasoning  map matching  vehicle navigation  data fusion
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