TY - JOUR
T1 - Planning Tourists Evacuation Routes with Minimal Navigation Errors
AU - Nahum, Oren E.
AU - Wachtel, Guy
AU - Hadas, Yuval
N1 - Publisher Copyright:
© 2020 The Authors. Published by Elsevier B.V.
PY - 2020
Y1 - 2020
N2 - Tourism is one of the largest growing industries worldwide, and so are the increased safety concerns. This is due to increasingly frequent and severe natural hazards as well as terrorism, where large crowds of tourists can be targeted. Furthermore, tourists are often less informed and are therefore more vulnerable to be trapped in chaotic situations. In such situations, normally we are interested in fast evacuation routes. However, tourists, especially during emergencies, are prone to orientation and navigation errors. Such errors can be avoided by providing electronic guidance at various intersections along the evacuation path (controlled intersections). This study formulates the above-mentioned situation as the shortest path problem with stochastic routing. The stochastic routing is the probabilistic selection of an outgoing arc at each node. As it is practically difficult to equip every intersection with guidance devices, a multi-objective model is developed. The model simultaneously minimizes the number of controlled intersections and minimizes the evacuation time gap between the proposed evacuation route and the optimal evacuation route. The problem is formulated as a stochastic multi-objective problem. A Pareto-front of solutions is obtained using a genetic algorithm and a simulation.
AB - Tourism is one of the largest growing industries worldwide, and so are the increased safety concerns. This is due to increasingly frequent and severe natural hazards as well as terrorism, where large crowds of tourists can be targeted. Furthermore, tourists are often less informed and are therefore more vulnerable to be trapped in chaotic situations. In such situations, normally we are interested in fast evacuation routes. However, tourists, especially during emergencies, are prone to orientation and navigation errors. Such errors can be avoided by providing electronic guidance at various intersections along the evacuation path (controlled intersections). This study formulates the above-mentioned situation as the shortest path problem with stochastic routing. The stochastic routing is the probabilistic selection of an outgoing arc at each node. As it is practically difficult to equip every intersection with guidance devices, a multi-objective model is developed. The model simultaneously minimizes the number of controlled intersections and minimizes the evacuation time gap between the proposed evacuation route and the optimal evacuation route. The problem is formulated as a stochastic multi-objective problem. A Pareto-front of solutions is obtained using a genetic algorithm and a simulation.
KW - Evacuation
KW - Multi-Objective Optimization
KW - Stochastic Shortest Path
UR - http://www.scopus.com/inward/record.url?scp=85084659585&partnerID=8YFLogxK
U2 - 10.1016/j.trpro.2020.03.094
DO - 10.1016/j.trpro.2020.03.094
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AN - SCOPUS:85084659585
SN - 2352-1457
VL - 47
SP - 235
EP - 242
JO - Transportation Research Procedia
JF - Transportation Research Procedia
T2 - 22nd EURO Working Group on Transportation Meeting, EWGT 2019
Y2 - 18 September 2019 through 20 September 2019
ER -