Abstract
Coordinating train arrivals at transfer stations by altering their departure times can reduce transfer waiting time (TWT) and improve level of service. This paper develops a method to optimize train departure times from terminals that minimizes total TWT for an urban rail network with many transfer stations. To maintain service capacity and avoid operational complexity, dispatching headway is fixed. An integrated Simulated Annealing with parallel computing approach is applied to perform the optimization. To demonstrate model applicability and performance, the Shenzhen metro network is applied, where passenger flows (i.e., entry, transfer, and exit) at stations are approximated with the automatic fare collection system (AFCS) data. Results show that the total TWT can be significantly reduced.
Highlights
For large-scale metro networks, large numbers of passengers arrive simultaneously at transfer stations, especially during peak periods
Transfer time is defined in this study as the elapsed time between a passenger alighting from a “delivery” train to boarding a “pickup” train, which consists of walking time between platforms and transfer waiting time (TWT) for the “pickup” train
Reduced TWT needed for data transfer is significant compared with the time needed for computation, the results show that the parallel computing (PC) method can be useful for some loop iterations that require long times to execute with big data
Summary
For large-scale metro networks, large numbers of passengers arrive simultaneously at transfer stations, especially during peak periods. Transfer time incurred by passengers has been considered as an index of service quality. Synchronizing vehicle arrival times to facilitate effective timed transfer is desirable. Transfer time is defined in this study as the elapsed time between a passenger alighting from a “delivery” train to boarding a “pickup” train, which consists of walking time between platforms and transfer waiting time (TWT) for the “pickup” train. Walking time is dependent on the layout of the station and walking speed, while TWT is affected by the arrival/departure times of the trains and walking time. To minimize TWT for a large metro network, the relationship between demand (i.e., spatiotemporal transfer passenger distribution) and supply (i.e., network configuration, service frequency, and departure time) must be carefully formulated
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