Incorporating human-factors in car-following models: A review of recent developments and research needs |
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Affiliation: | 1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;2. State Key Laboratory of Fire Science and School of Engineering Science, University of Science and Technology of China, Hefei 230026, China;3. Department of Civil and Environmental Engineering, University of California Davis, Davis, CA 95616, United States;4. Department of Traffic Engineering, School of Transportation Engineering, Tongji University, Shanghai 200092, China;1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, China;2. School of Traffic and Transportation Engineering, Central South University, Changsha, China;1. Polytechnic Institute of Viseu, Campus Politécnico de Repeses, 3504-510 Viseu, Portugal;2. University of Coimbra, Rua Luís Reis Santos, 3030-788 Coimbra, Portugal |
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Abstract: | Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area. |
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Keywords: | Car-following Driver behavior Human factors Risk taking Driver error |
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