Abstract
This paper presents a framework to identify affected commuter passengers and their rerouting decisions under metro operational disruption. A cumulative prospect theory (CPT) based model is proposed to capture commuters’ mental activity and behavior from individual perspective considering heterogeneities, including time value, requirement of arrival time, sensitivity of cost and attitudes toward risk. Thus, commuters’ rerouting decision among multiple modes such as metro, bus, taxi and walking, can be effectively and accurately identified, which successfully overcomes the limitation of simplification and assumption in traditional methods. Case study of Beijing metro network and corresponding data of Automatic Fare Collection System (AFC) under disturbance in real world proves the effectiveness of the presented method.
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