Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents

• Published in: Journal of advanced transportation Vol. 2023; pp. 1 - 11
• Main Authors: Zhu, Minqing, Shi, Peng, Cui, Hongjun, Li, Xinye, Ma, Xinwei
• Format: Journal Article
• Language: English
• Published: London Hindawi 15.03.2023; Hindawi Limited; Wiley
• Subjects: Accidents; Analysis; Behavior; Decision making; Decision theory; Equilibrium; Expected utility; Flow distribution; Optimization; Perception; Psychological aspects; Rationality; Roads & highways; Route choice; Route selection; Scale effect; Temporal perception; Traffic accidents & safety; Traffic congestion; Traffic control; Traffic flow; Traffic management; Traffic regulations; Transportation planning; Travel; Travel time; Travelers
• ISSN: 0197-6729; 2042-3195
• DOI: 10.1155/2023/7864340

To investigate the route choice behavior of travelers under unexpected accidents, this study designs four different scenarios of travelers’ route choice behavior experiments according to the severity of unexpected accidents. The bounded rationality characteristics of travelers, such as the time perception difference coefficient, psychological threshold effect coefficient, and scale effect, are introduced into the generalized random regret minimization (GRRM) model. An improved generalized random regret minimization (IGRRM) model is constructed based on travelers’ route choice behavior under unexpected accidents. The collected data of travelers’ route choice results under four different congestion-level scenarios are analyzed by the IGRRM model. The study finds that with the increase in congestion level, travelers are more willing to change the route; during the commute, travelers tend to choose the route with less travel time and angular cost; in the moderate and serious congestion scenarios, travelers no longer reject the detour route; attribute perception difference, scale effect, and psychological threshold effect; affect travelers’ route choice behavior. The IGRRM model based on the route choice behavior of travelers can more accurately characterize the route choice behavior of travelers under unexpected accidents, provide a basis for traffic flow distribution under unexpected accidents, and benefit traffic management departments to take traffic control and guidance measures to ease the traffic congestion caused by unexpected accidents.