车路协同环境下基于误差加权的车辆无线定位融合算法
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- 英文论文题名：Vehicle Wireless Location Algorithm Based on Error-Weighted Under the Condition of Connected Vehicle
- 论文作者：王江锋 ; 王娜 ; 高畅 ; 朱周元
- 英文论文作者：Wang Jiangfeng ; Wang Na ; Gao Chang ; Zhu Zhouyuan ; MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology ; Beijing Jiaotong University ; Beijing Operations ; China Automotive Technology & Research Center
- 年：2016
- 作者机构：城市交通复杂系统理论与技术教育部重点实验室,北京交通大学;中国汽车技术研究中心北京工作部;
- 论文关键词：车路协同 ; 无线定位 ; 车辆轨迹 ; 实证分析
- 英文论文关键词：Connected Vehicle ; Wireless Location ; Vehicle Trajectory ; Validation Analysis
- 会议召开时间：2016-11-16
- 会议录名称：第十一届中国智能交通年会大会论文集
- 语种：中文
- 分类号：TN92;U495
- 学会代码：ZJTX
- 会议名称：第十一届中国智能交通年会
- 会议地点：中国重庆
- 主办单位：中国智能交通协会
- 学会名称：中国智能交通协会
- 页数：5
- 文件大小：1158k
- 原文格式：D
- 会议级别：全国
摘要
针对车辆无线定位算法多基于良好环境进行测试而未考虑其对实际道路交通环境的适应性问题,提出一种基于误差加权的车辆无线融合定位算法作为辅助以实现车辆的全时空定位。在介绍经典无线定位方法基础上,给出了车辆无线融合定位算法的定位原理、逻辑流程以及算法模型。利用外场车路协同环境下采集的实际信号强度和车辆轨迹信息,验证了融合定位算法的有效性,结果显示95%的轨迹点定位精度小于122 m。
Considering the limitation of vehicle wireless location algorithm validated in good scenarios without considering its adaptability in actual road environment,a vehicle wireless fusion location algorithm based on error-weighted is proposed as supplementary method to achieve full spatial-temporal localization.Through the introduction of common wireless location algorithms,the positioning principle,logic flow and model of the fusion algorithm are presented.Using the actual signal strength and vehicle trajectory collected in connected vehicle environment,the effectiveness of the algorithm is validated,and the results show that the positioning accuracy of 95% trajectory points is less than 122 m.
Considering the limitation of vehicle wireless location algorithm validated in good scenarios without considering its adaptability in actual road environment,a vehicle wireless fusion location algorithm based on error-weighted is proposed as supplementary method to achieve full spatial-temporal localization.Through the introduction of common wireless location algorithms,the positioning principle,logic flow and model of the fusion algorithm are presented.Using the actual signal strength and vehicle trajectory collected in connected vehicle environment,the effectiveness of the algorithm is validated,and the results show that the positioning accuracy of 95% trajectory points is less than 122 m.
引文
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[9]彭玉旭,杨艳红.一种基于RSSI的贝叶斯室内定位算法[J].计算机工程,2012,38(5):237-240.
[10]张佳,吴延海,石峰,等.基于DV-HOP的无线传感器网络定位算法[J].计算机应用,2010,30(2):323-326.
[11]王江锋,闫学东,邵春福等.基于Min-Max方法和移动轨迹融合的车辆无线定位算法[J].车辆工程,2012.34(5):466-469.
[12]来磊,曲仕茹.交通无线传感网络运动车辆定位方法[J].交通运输工程学报,2013(2):114-120.
[2]Anupam M,Madhur C.Wi-Fi Localization using RSSI in Indoor Environment via a smartphone[J].International Journal Of Engineering And Computer Science,2012,1(2):94-98.
[3]Wu X,Tang D,Qian X.A Centralized Location Algorithm based on RSSI in Large-Scale Wireless Sensor Network[J].Procedia Engineering,2011,15:2004-2009.
[4]Borenovic M,Neskovic A,Neskovic N.Vehicle positioning using GSM and cascade-connected ANN structures[J].IEEE Transactions on Intelligent Transportation Systems,2013,14(1):34-46.
[5]Kumar S,Kislay K,Singh M K,et al.A range-free tracking algorithm in vehicular ad-hoc networks[C].Proceedings of IEEE Twentieth National Conference on Communications(NCC),2014:1-6.
[6]雷谦.基于RSSI的无线传感器网络定位算法[D].昆明:昆明理工大学硕士学位论文,2014.
[7]毛永毅,谢川.基于遗传算法优化神经网络的定位算法[J].西安邮电大学学报,2014,19(7):45-48.
[8]石晓伟.基于BP神经网络和改进质心算法的室内无线定位技术的研究[D].北京:北京工业大学硕士学位论文,2012.
[9]彭玉旭,杨艳红.一种基于RSSI的贝叶斯室内定位算法[J].计算机工程,2012,38(5):237-240.
[10]张佳,吴延海,石峰,等.基于DV-HOP的无线传感器网络定位算法[J].计算机应用,2010,30(2):323-326.
[11]王江锋,闫学东,邵春福等.基于Min-Max方法和移动轨迹融合的车辆无线定位算法[J].车辆工程,2012.34(5):466-469.
[12]来磊,曲仕茹.交通无线传感网络运动车辆定位方法[J].交通运输工程学报,2013(2):114-120.