标题:Automatic vehicle tracking with lidarenhanced roadside infrastructure
作者:Wu, Jianqing ;Zhang, Yongsheng ;Tian, Yuan ;Yue, Rui ;Zhang, Hongbo
作者机构:[Wu, Jianqing ] School of Qilu Transportation, Shandong University, Jinan, Shandong; 250061, China;[Zhang, Hongbo ] School of Qilu Transportation, Sha 更多
通讯作者:Zhang, Hongbo
来源:Journal of Testing and Evaluation
出版年:2020
卷:49
期:1
DOI:10.1520/JTE20190859
关键词:Connected vehicle; Light Detection and Ranging; Speed evaluation; Vehicle tracking
摘要:Vehicle tracking technology is a prerequisite for the connected-vehicle (CV) system. However, a mixture of CV and unconnected vehicles will be under normal conditions on roads in the near future. How to obtain the real-time traffic status of unconnected vehicles remains a challenge for traffic engineers. The roadside Light Detection and Ranging (LiDAR) sensor provides a solution for collecting real-time high-resolution micro traffic data of all road users (CV and unconnected vehicles). This article developed a systematic procedure for vehicle tracking using the roadside LiDAR sensors. The procedure can be divided into five major parts: point registration, background filtering, point clustering, object classification, and vehicle tracking. For each step, the corresponding data processing algorithms were provided. A field test was conducted to evaluate the performance of the proposed method. Compared to the state-ofthe-art method, the proposed methods can track vehicles with higher accuracy and lower computation loads. Copyright © 2020 by ASTM International.
收录类别:EI;SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082528563&doi=10.1520%2fJTE20190859&partnerID=40&md5=869471ca93e525102b395611ef764ad5
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