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Abstract
Every commuter utilizing urban rail transit decides the departure time from home to a station according to individual judgment for the biggest possibility to board a train as soon as possible after the arrival. Therefore, the departure time choice behavior of the commuters is complicated especially when the transport capacity of this transit line cannot meet the travel demands of its users in rush hour. This research first develops a travel cost function mainly considering the travel time to rationally describe the volume distribution of the commuters arriving at a station at different time periods. Furthermore, an optimization model is accordingly proposed to rationalize the arrival distribution of the commuters on the basis of the amount of the arrived commuters who are able to board a train from the perspective of the systematic operation of a rail transit line for the minimal total travel cost of all the commuters along this line. It is found that the total travel cost can be reduced by 19.0% at most through the arrival distribution rationalization with the optimization model.
Highlights
The growing traffic congestion in large cities has forced traffic to be inefficient and caused high energy consumption
The volume distribution of commuters arriving at a station at different time periods of morning rush hour is assumed as a Poisson distribution [21,22,23]
A travel cost function mainly considering the travel time to rationally describe the volume distribution of the commuters arriving at a station along a rail transit line with multiple origins and a single destination has been proposed
Summary
The growing traffic congestion in large cities has forced traffic to be inefficient and caused high energy consumption. There are some differences between mass transit and road transport which should be considered. The problem of choosing departure time and route simultaneously in a mass transit system has been studied without explicitly considering capacity constraints. In Beijing urban mass transit system, for example, scheduled intervals of different lines have been shortened by 28 times in order to increase the transport capacity of the system during the past six years. We focus on the commuters’ departure time choice model of the peak period commuting in a mass transit line with multiple origins and a single destination, which may emerge when the mass transit line serves a concentric city where all commuters are assumed to work in a highly compact city centre and live in the dispersed surrounding suburban area.
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