Modeling boundedly rational route choice in crowd evacuation processes

Xiang, Wang; Chraibi, Mohcine; Chen, Juan; Li, Ruoyu; Ma, Jian

doi:10.1016/j.ssci.2021.105590

Cited by 27 publications

(7 citation statements)

References 36 publications

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“…Taking the evacuation starting point one as an example, when facing the flood of once-in-50-year, some better evacuation routes than the existing Mingxin Village Shelter are selected (Figure 12). The comparison models used are the original route, 2D Dijkstra route, rational route [39], and original least direct change route [40]. The original route is limited by the location of the shelter and road factors, so the evacuation time is longer.…”

Section: Comparison Between Ours and Other Methodsmentioning

confidence: 99%

Optimal Evacuation Route Planning of Urban Personnel at Different Risk Levels of Flood Disasters Based on the Improved 3D Dijkstra’s Algorithm

Zhu

Wang

et al. 2022

Sustainability

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In the event of a flood, the choice of evacuation routes is vital for personnel security. This is particularly true when road factors play an important role in evacuation time. In this study, the traditional Dijkstra algorithm for route planning is improved, and the evacuation model is improved from 2D to 3D. At the same time, the Lasso regression method is adopted to take the road factors into account in the pedestrian speed, and the location of shelter is selected and optimized through the calculation results, and then based on the improved 3D Dijkstra’s algorithm, an optimal evacuation route method in different flood disasters risk levels is proposed, which can make pedestrians reach the shelters within the shortest time. After taking into account road factors (road width, slope, non-motorized lane width, and pedestrian density), through the calculation of the pedestrian speed formula, the estimated evacuation time of pedestrians is obtained. By combining available shelters with evacuation routes, the optimized algorithm improves the evacuation efficiency facing different risk levels of flood disasters. The results show that when residents are confronted with flood disasters of once-in-20-year, once-in-50-year, and once-in-100-year, the proposed optimization algorithm can save 7.59%, 11.78%, and 17.78% of the evacuation time. Finally, according to the verification of the actual effect in Meishan Town, the proposed method of optimal evacuation route planning can effectively reduce the evacuation time of pedestrians, evaluate, and optimize the location of existing shelter, and provide suggestions for urban road reconstruction.

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Section: Comparison Between Ours and Other Methodsmentioning

confidence: 99%

Optimal Evacuation Route Planning of Urban Personnel at Different Risk Levels of Flood Disasters Based on the Improved 3D Dijkstra’s Algorithm

Zhu

Wang

et al. 2022

Sustainability

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“…Another reason may be that, in some trials, the differences of the predicted route travel times among the three routes (predicted by per-trip traffic information) or the difference of the predicted link travel times between two links (predicted by en-route traffic information) were not significant. As proposed by the literature [44][45][46], there is an "indifference band" that exists in the traveler's route choice behavior, and if the difference between travel times on the current route and on the best available route is within this indifference band, the traveler will not switch a route. Therefore, the compliance ratios were not always equal to 100% under the influence of traffic information.…”

Section: Pre-trip Traffic Information Vs En-route Traffic Informationmentioning

confidence: 99%

Analysis of the Conflict between Car Commuter’s Route Choice Habitual Behavior and Traffic Information Search Behavior

2022

Sensors

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Motivated by the conflict between travelers’ habitual choice behavior and traffic information search behavior, in this paper, a behavioral experiment under different types of traffic information (i.e., per-trip traffic information and en-route traffic information) was designed to obtain data regarding car commuters’ daily route choices. Based on the observed data, participants’ route choices, habit strength, response time, and information search behaviors were analyzed. It is concluded that, in the beginning, the traffic information had a great influence on the habit participants’ route choices, let them think more, and made most of them switch from habit route to the best route (as recommended by traffic information); however, as time went on, the impact of traffic information declined, and several features of habits, such as automatically responding and repeated behavior, would reappear in some participants’ decision-making. Meanwhile, the different way of traffic information search behaviors (i.e., in active performance or in passive reception) could cause different information compliance ratios. These results would help to understand the interrelationship between car commuters’ daily route choice behaviors and traffic information search behaviors in short-term and in long-term, respectively, and provide an interesting starting point for the development of practical traffic information issuing strategies to enhance the impact of traffic information to alleviate traffic congestion during morning commuting.

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“…To date, researchers have extensively investigated evacuation processes within certain typical geometric layouts, such as corners [21], T-junctions [22], and corridors [23]. These distinctive geometric configurations have given rise to unique phenomena of self-organized pedestrian behaviors, including phenomena like pedestrian queuing, merging, and corridor diversion [24]. Additionally, the presence of obstacles can potentially augment the complexity of pedestrian evacuation processes [25].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on Pedestrian Behaviors during Fire Emergency Conditions with Minecraft: Case Studies in a Classroom

Zhang,

et al. 2023

Fire

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The comprehension of the fire evacuation process is crucial for developing effective evacuation management strategies to enhance pedestrian safety. In this study, we construct a classroom with internal obstacles forming intersecting pathways in Minecraft, and conduct a series of virtual evacuation experiments involving multiple pedestrians to investigate the pedestrian behaviors. Case studies in a single-exit classroom demonstrated that normal obstacles and fire in the main evacuation path prompt pedestrians to detour, and pedestrians exhibit fire-avoidance behavior in advance during fire emergency. In the two-exit classroom experiments, normal obstacles have a limited effect on the exit choices of pedestrians, as they primarily choose the nearest exit. Pedestrians positioned in the center of classroom are influenced by their initial orientations, and some pedestrians opt for exits in their initial facing directions. The presence of fire has a greater influence on pedestrians’ exit choices, with most opting for exits away from the fire. Furthermore, during fire emergencies, some pedestrians engage in risk-taking behavior by choosing higher-risk paths in pursuit of a faster evacuation. These adventurous pedestrians proactively plan routes that maximize their distance from the fire and exhibit orderly queuing behavior. These findings are helpful to reveal pedestrian behaviors during fire emergencies.

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Modeling boundedly rational route choice in crowd evacuation processes

Cited by 27 publications

References 36 publications

Optimal Evacuation Route Planning of Urban Personnel at Different Risk Levels of Flood Disasters Based on the Improved 3D Dijkstra’s Algorithm

Optimal Evacuation Route Planning of Urban Personnel at Different Risk Levels of Flood Disasters Based on the Improved 3D Dijkstra’s Algorithm

Analysis of the Conflict between Car Commuter’s Route Choice Habitual Behavior and Traffic Information Search Behavior

Experimental Study on Pedestrian Behaviors during Fire Emergency Conditions with Minecraft: Case Studies in a Classroom

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