@inproceedings{410e25106e744d0c8630a92e343759d9,
title = "LANE-BASED TRAVEL TIME ESTIMATION FOR MULTIPLE VEHICLE TYPES: A VEHICLE REIDENTIFICATION APPROACH",
abstract = "Travel time are crucial information for route guidance and traffic management. On urban roads with many lane-changing movements, different types of vehicles will have different traveling speeds and the traffic conditions of different lanes are not the same. However, little attention has been given to estimate travel times for different types of vehicles traveling on different lanes. This paper proposed a lane-based travel time estimation for multiple vehicle types through the matching of low-resolution vehicle images from surveillance cameras. Vehicle size and high-dimensional deep-learning features are extracted from vehicle images for vehicle classification. Lane-based bipartite graph matching technique, which based on matching probabilities estimated from vehicle features, are adopted to reidentify vehicles. Case study is conducted on a congested four-lane urban road in Hong Kong, and the results shows that the proposed model generally give an accurate estimation of travel times for different types of vehicles traveling on different lanes.",
keywords = "Lane-based travel time, Vehicle re-identification, Vehicle type, Video images",
author = "Cheng Zhang and Ho, {H. W.} and Lam, {William H.K.} and Wei Ma and Wong, {S. C.} and Chow, {Andy H.F.}",
note = "Funding Information: The work described in this paper was jointly supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos. PolyU R5029-18, 17204919) and the Research Institute for Sustainable Urban Development of the Hong Kong Polytechnic University (Project No. 5-ZJM5). The fifth author was supported by the Francis S Y Bong Endowed Professorship in Engineering. Publisher Copyright: {\textcopyright} 2021 Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility. All Rights Reserved.; 25th International Conference of Hong Kong Society for Transportation Studies: Sustainable Mobility, HKSTS 2021 ; Conference date: 09-12-2021 Through 10-12-2021",
year = "2021",
month = dec,
language = "English",
series = "Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility",
publisher = "Hong Kong Society for Transportation Studies Limited",
pages = "2--10",
editor = "Wong, {Ryan C.P.} and Jiangping Zhou and W.Y. Szeto",
booktitle = "Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021",
}