Abstract
Abstract
The Urban Rail Transit (URT) network possesses the features of multi-route and big volume of passengers. To study the route choice behavior and volume control of passengers is a bridge to match the capacity supply and passenger demand in URT network. It’s also a crucial problem proposed by the networked operation of URT. We analyze systematically the effect factors of passengers’ route choice behavior and related research on passenger volume control in URT network, as well as the updated representation of URT network and nature of passenger demand. Then we set up the integrated calculation formula for general travel cost in URT network. afterwards, we summarize the classical research method for route choice behavior, including its main study procedure, the search and identify method for effective routes, logit model, probability distribution model, multi-agent simulation and calculation of the match probability by using big data e.g. AFC data. Importantly, we propose the framework for joint comprehensive prediction of passenger route choice behavior and volume control in URT network based on big data, which displays the mind map of passenger-flow-based prediction control and intelligent decision for future study. This review has great theoretical and practical meanings in improving the service efficiency and quality of URT, so as to balance the load of each line and station in URT network, as well as to reduce or eliminate the passenger waiting time for those being left behind because of congestion.
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