Optimal method for traffic flow in peak period of urban rail transit based on coordinated train timetable

Abstract

The invention provides a method for optimizing the flow of urban rail traffic during the peak period for coordinating train timetables. The method includes: collecting urban rail transit AFC data and train planning timetable data, and processing the collected data to obtain time-varying passenger arrival rate, alighting rate and train section running time during peak hours; based on the set assumptions Conditions, establish an optimization model of urban rail transit current-flow measures during peak hours to coordinate train schedules, and the objective function of the collaborative optimization model of current-limiting measures is to minimize the number of passengers waiting; the proposed collaborative optimization model of train timetable and current-limiting measures is carried out Solve the solution, and get the optimization scheme of urban rail transit peak flow. The method of the present invention can be used to synergistically optimize urban rail transit train timetables and flow-limiting measures, rationally set passenger flow management measures and timetable operation schemes, improve the internal operation safety and passenger safety of urban rail transit systems, and reduce passenger traffic accidents at some stations. Stay for a long time.

Description

technical field [0001] The invention relates to the technical field of current limit optimization of urban rail transit, in particular to a method for optimizing current limit of urban rail transit during peak hours by coordinating train timetables. Background technique [0002] As the backbone mode of public transportation in big cities, realizing the collaborative optimization of urban rail transit train operation and passenger flow control can effectively improve the efficiency of urban rail transit train transportation, relieve the pressure of large passenger flow, and meet the increasing traffic demand. In recent years, in order to cope with the sharply increased passenger flow pressure during peak hours, the departure frequency of urban rail transit trains in some major cities has been shortened to the minimum to ensure train safety. For example, the minimum departure frequency of the subway in Shanghai is 2 minutes and 5 seconds. Under such high-frequency and high-dem...

AI Technical Summary

Problems solved by technology

However, this scheme only considers the impact of passenger flow control on the train timetable, without co-optimization of train scheduling and passenger flow control

[0004] At present, most of the research schemes on current limiting measures in the existing technology adopt fixed demand, without considering the time-varying nature of passenger flow

Moreover, the existing technical solutions lack an optimization method that jointly considers train schedules and current limiting measures

This leads to the fact that the currently proposed current limiting measures and train schedules are independent, without considering and analyzing the mutual influence and restrictive relationship between the two, and it is difficult to improve the travel efficiency of urban rail transit passengers while ensuring safety

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