Urban rail transit operation time period division method

Abstract

The invention discloses an urban rail transit operation time period division method, which comprises the following steps of firstly, setting a time interval and counting a target line one-way OD distribution matrix within the time interval; secondly, extracting a target line one-way OD probability matrix based on the target line one-way OD distribution matrix; thirdly, constructing an ordered sample sequence with the target line one-way OD probability matrix as a sample; and lastly, dividing the ordered sample sequence by utilizing an optimal segmentation method for clustering of ordinal samples. According to the method, a target line operation time period division scheme is provided through extracting a time sequence of the OD probability matrix, clustering through the optimal segmentation method and classifying the statistical time periods with the similar inter-site passenger flow transfer rules into one class, so that the decision basis is provided for a rail transit management department to carry out operation time period division and train operation plan optimization.

Description

technical field [0001] The invention belongs to the field of transportation, in particular to a method for dividing urban rail transit operation periods. Background technique [0002] The urban rail transit train operation plan stipulates the arrival and departure time of trains at each station along the line, which is the premise and basis for daily operation organization. In order to minimize the waiting time of passengers on the platform and improve the service level, operating units have widely adopted a train operation plan that departs at equal intervals. The specific performance of this scheme is: shorten the departure interval during the peak period of passenger flow, and reduce the waiting time of passengers by increasing the frequency of departure; extend the departure interval during the low passenger flow period, and save operating costs by reducing the number of departures. [0003] A common method of dividing operating periods is to divide the operating day in...

AI Technical Summary

Problems solved by technology

Although this classification method qualitatively considers the differences between passenger flow transfer laws in different operating periods, it fails to provide quantitative evaluation indicators for the differences between categories, and lacks further research on the passenger flow transfer laws in different operating periods.

Images