Citation

Wu J, Xu H, Zhang Y, Tian Y, Song X. Sensors (Basel) 2020; 20(8): e2342.

Affiliation

School of Qilu Transportation, Shandong University, Jinan 250061, China.

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s20082342

PMID

32326028

Abstract

Real-time queue length information is an important input for many traffic applications. This paper presents a novel method for real-time queue length detection with roadside LiDAR data. Vehicles on the road were continuously tracked with the LiDAR data processing procedures (including background filtering, point clustering, object classification, lane identification and object association). A detailed method to identify the vehicle at the end of the queue considering the occlusion issue and package loss issue was documented in this study. The proposed method can provide real-time queue length information. The performance of the proposed queue length detection method was evaluated with the ground-truth data collected from three sites in Reno, Nevada.

RESULTS show the proposed method can achieve an average of 98% accuracy at the six investigated sites. The errors in the queue length detection were also diagnosed.

Language: en

Keywords

queue length; roadside sensor; vehicle detection