Lane Change Behavior Patterns and Risk Analysis in Expressway Weaving Areas: Unsupervised Data-Mining Method

Author:

Guo Yinjia1,Gu Xin2,Chen Yanyan3,Guo Jifu4,Wan Huaiyu5,Zhou Yuntong1

Affiliation:

1. Beijing Key Laboratory of Traffic Engineering, Beijing Univ. of Technology, Beijing 100124, China.

2. Tutor, Beijing Key Laboratory of Traffic Engineering, Beijing Univ. of Technology, Beijing 100124, China.

3. Professor, Beijing Key Laboratory of Traffic Engineering, Beijing Univ. of Technology, Beijing 100124 China (corresponding author).

4. Professor, Beijing Transport Institute, Beijing 100073, China.

5. Professor, Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong Univ., Beijing 100044, China.

Publisher

American Society of Civil Engineers (ASCE)

Reference65 articles.

1. Driver Maneuver Detection and Analysis Using Time Series Segmentation and Classification

2. Agamennoni G. S. Worrall J. R. Ward and E. M. Neboty. 2014. “Automated extraction of driver behaviour primitives using Bayesian agglomerative sequence segmentation.” In Proc. 17th Int. IEEE Conf. on Intelligent Transportation Systems (ITSC). New York: IEEE.

3. Ahmed K. I. 1999. “Modeling drivers’ acceleration and lane changing behavior.” Ph.D. thesis Dept. of Civil and Environmental Engineering Massachusetts Institute of Technology.

4. Ahmed K. I. M. E. Ben-Akiva H. N. Koutsopoulos and R. G. Mishalani. 1996. “Models of freeway lane changing and gap acceptance behavior.” In Proc. 13th Int. Symp. on Transportation and Traffic Theory. Washington DC: National Highway Traffic Safety Administration.

5. Investigation of Automated Vehicle Effects on Driver's Behavior and Traffic Performance

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