Urban rail transit driving scheme calculation method based on multi-day passenger flow fusion

Abstract

The invention discloses an urban rail transit driving scheme calculation method based on multi-day passenger flow fusion, and the method comprises the following steps: S1, carrying out the user-defined setting of an intersection path, a calculation time domain, a calculation time granularity, a driving interval value range constraint and a maximum load factor constraint according to the basic information of a line; S2, preprocessing the corresponding multi-day passenger flow data according to the calculation time domain and the time granularity, and obtaining the section passenger flow demand quantity in different time periods by adopting a clustering analysis method; S3, calculating a driving interval and a double-intersection driving proportion which meet the passenger flow demand, the load factor and the value range constraint in each time granularity in a classified manner according to different intersection forms and the number of fixed passengers of the whole train; and S4, outputting a driving scheme calculation result and a corresponding passenger flow demand quantity according to a time sequence, and combining time granularities with the same or similar results to form a multi-peak period scheme. The method has the advantages of improving multi-day passenger flow data processing efficiency, refining transport capacity and transport volume matching, fitting operation practice rules and the like.

Description

technical field [0001] The invention relates to the technical field of rail transit traffic planning, in particular to a calculation method for urban rail traffic traffic planning based on multi-day passenger flow integration. Background technique [0002] Urban rail transit mainly serves the commuter passenger flow, and the operating unit needs to formulate a train operation plan that matches the passenger flow demand. In addition to the limitations of line infrastructure, passenger flow characteristics are the main basis for formulating train operation plans. The tidal nature of the passenger flow, the two-way unevenness, and the unevenness of time and space affect the complexity of the travel plan. [0003] The operation plan mainly includes the train interval plan, the train marshalling plan and the train stop plan. The vehicle marshalling plan is generally determined at the beginning of the line design, and the stop plan is determined according to the initial passenge...

AI Technical Summary

Problems solved by technology

However, due to the lack of auxiliary decision-making tools that use passenger flow data to directly calculate the driving plan, map editors need to first analyze the passenger flow data, and then manually estimate the driving plan, which is not only inefficient, but also prone to human errors

In addition, precise operation needs to analyze and make decisions in combination with a large number of passenger flow data of multiple characteristic days, which is difficult to achieve with the current method.

Relevant research mainly focuses on uneven timetables and irregular stop schemes driven by passenger flow, and it is difficult to directly apply the theory and results to practice

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