Improved Driver Clustering Framework by Considering the Variability of Driving Behaviors across Traffic Operation Conditions-Reference-Cited by-同舟云学术

Improved Driver Clustering Framework by Considering the Variability of Driving Behaviors across Traffic Operation Conditions

Published:2022-07 Issue:7 Volume:148 Page:
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Zhang Jianbo¹^ORCID,Lu Hongyu²,Sun Jianping³

Affiliation:

1. Engineer, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing 100044, China; Engineer, Intelligent Transportation Dept., Beijing Transport Institute, Beijing 10073, China; Engineer, Intelligent Transportation Dept., Beijing Transport Institute, Beijing International Science and Technology Cooperation Base of Urban Transport, Beijing Key Laboratory of Urban Transport Simulation and Decision Making Support, Beijing 10073, China (corresponding author). ORCID: .

2. Engineer, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332.

3. Professorate Senior Engineer, Beijing Transport Institute, Beijing International Science and Technology Cooperation Base of Urban Transport, Beijing Key Laboratory of Urban Transport Simulation and Decision Making Support, Beijing 10073, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000686

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3. Carboni, E. M., and V. Bogorny. 2014. “Inferring drivers behavior through trajectory analysis.” In Vol. 322 of Intelligent systems’ 2014. Advances in intelligent systems and computing, 837–848. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-11313-5_73.

4. Carmona J. M. Miguel D. Martin F. Garcia and A. Escalera. 2016. “Embedded system for driver behavior analysis based on GMM.” In Proc. 2016 IEEE Intelligent Vehicles Symp. (4) 61–65. New York: IEEE. https://doi.org/10.1109/IVS.2016.7535365.

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