Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents

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 perc...

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Main Authors: Minqing Zhu, Peng Shi, Hongjun Cui, Xinye Li, Xinwei Ma
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2023/7864340
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author Minqing Zhu
Peng Shi
Hongjun Cui
Xinye Li
Xinwei Ma
author_facet Minqing Zhu
Peng Shi
Hongjun Cui
Xinye Li
Xinwei Ma
author_sort Minqing Zhu
collection DOAJ
description 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.
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spelling doaj-art-4230acc8cbd14f8487e877bb5bea67092025-02-03T06:42:50ZengWileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/7864340Modeling the Traveler’s Route Choice Behavior under Unexpected AccidentsMinqing Zhu0Peng Shi1Hongjun Cui2Xinye Li3Xinwei Ma4School of Architecture and Art DesignSchool of Civil and Transportation EngineeringSchool of Civil and Transportation EngineeringSchool of Civil and Transportation EngineeringSchool of Civil and Transportation EngineeringTo 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.http://dx.doi.org/10.1155/2023/7864340
spellingShingle Minqing Zhu
Peng Shi
Hongjun Cui
Xinye Li
Xinwei Ma
Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
Journal of Advanced Transportation
title Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
title_full Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
title_fullStr Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
title_full_unstemmed Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
title_short Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents
title_sort modeling the traveler s route choice behavior under unexpected accidents
url http://dx.doi.org/10.1155/2023/7864340
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AT pengshi modelingthetravelersroutechoicebehaviorunderunexpectedaccidents
AT hongjuncui modelingthetravelersroutechoicebehaviorunderunexpectedaccidents
AT xinyeli modelingthetravelersroutechoicebehaviorunderunexpectedaccidents
AT xinweima modelingthetravelersroutechoicebehaviorunderunexpectedaccidents