A comparison of patterns and contributing factors of ADAS and ADS involved crashes

Author:

Yan Song1,Huang Chunxi2,He Dengbo134

Affiliation:

1. Thrust of Intelligent Transportation, The Hong Kong University of Science and Technology, Guangzhou, China

2. Interdisciplinary Programs Office (IPO), The Hong Kong University of Science and Technology, Hong Kong, China

3. HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Shenzhen, China

4. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

Funder

National Natural Science Foundation of China

Guangzhou Municipal Science and Technology Project

Guangzhou Science and Technology Program City-University Joint Funding Project

Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone

Publisher

Informa UK Limited

Subject

Safety Research,Transportation

Reference47 articles.

1. Akaike, H. (1973). Information theory as an extension of the maximum likelihood principle. In B. N. Petrov & F. Csaki (Eds.), Second International Symposium on Information Theory. Academiai Kiado.

2. Pairwise dynamic time warping for event data

3. California DMV (2022). Autonomous vehicle collision reports . California Department of Motor Vehicles. Retrieved from https://www.dmv.ca.gov/portal/vehicle-industry-services/ autonomous-vehicles/autonomous-vehicle-collision-reports/

4. Analysis of Factors Affecting the Severity of Automated Vehicle Crashes Using XGBoost Model Combining POI Data

5. Longitudinal Collision Avoidance and Lateral Stability Adaptive Control System Based on MPC of Autonomous Vehicles

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