A Review of Near-Collision Driver Behavior Models
Journal article, 2012

Objective: This article provides a review of recent models of driver behavior in on-road collision situations. Background: In efforts to improve traffic safety, computer simulation of accident situations holds promise as a valuable tool, for both academia and industry. However, to ensure the validity of simulations, models are needed that accurately capture near-crash driver behavior, as observed in real traffic or driving experiments. Method: Scientific articles were identified by a systematic approach, including extensive database searches. Criteria for inclusion were defined and applied, including the requirement that models should have been previously applied to simulate on-road collision avoidance behavior. Several selected models were implemented and tested in selected scenarios. Results: The reviewed articles were grouped according to a rough taxonomy based on main emphasis, namely avoidance by braking, avoidance by steering, avoidance by a combination of braking and steering, effects of driver states and characteristics on avoidance, and simulation platforms. Conclusion: A large number of near-collision driver behavior models have been proposed. Validation using human driving data has often been limited, but exceptions exist. The research field appears fragmented, but simulation-based comparison indicates that there may be more similarity between models than what is apparent from the model equations. Further comparison of models is recommended. Application: This review provides traffic safety researchers with an overview of the field of driver models for collision situations. Specifically, researchers aiming to develop simulations of on-road collision accident situations can use this review to find suitable starting points for their work.







driver behavior


Gustav M Markkula

Volvo Group

Ola Benderius

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Chalmers, Vehicle and Traffic Safety Centre at Chalmers (SAFER)

Krister Wolff

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Mattias Wahde

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Human Factors

0018-7208 (ISSN) 1547-8181 (eISSN)

Vol. 54 6 1117-1143

Areas of Advance


Subject Categories

Applied Psychology

Vehicle Engineering



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