A passenger flow induction method for urban rail transit based on multi-agent simulation

Abstract

The invention provides an urban rail transit passenger flow induction method based on multi-agent simulation. The method includes: constructing a two-level planning model for passenger flow dynamic induction optimization considering the release range and content of the guidance information, and the upper layer optimization model is based on the total network travel cost and The sum of the induction cost is the objective function, and the passenger flow induction scheme is generated by the genetic algorithm. The lower layer simulation model is used to simulate and model the travel behavior of passengers in the current passenger flow induction scheme, and input the passenger flow and generalized cost of each road segment during the simulation period into the upper layer optimization model, and the upper layer optimization model combines the passenger flow induction scheme, The passenger flow and generalized cost are substituted into the objective function, and the fitness function under the current solution is obtained. Through multiple iterations, the optimal dynamic passenger flow induction scheme with the highest fitness function is obtained. The invention can realize the refined induction of "one station, one plan", can assist passengers to make reasonable path decisions, and relieve the local passenger flow congestion in the urban rail transit network.

Description

technical field [0001] The invention relates to the technical field of urban rail transit passenger flow management, in particular to an urban rail transit passenger flow induction method based on multi-agent simulation. Background technique [0002] With the increasing demand of urban rail transit passenger flow, the congestion problem of urban rail transit network is becoming more and more serious. While overcrowding reduces the operational efficiency of urban rail transit networks, it also affects the travel experience of passengers, leading some passengers to abandon rail transit and choose other modes of transportation. Therefore, formulating effective measures to alleviate the congestion of subway passenger flow plays an important role in improving the service level of rail transit. [0003] The subway operation department usually relieves the congestion of the line network by increasing the supply capacity or limiting the demand for passenger flow, such as increasing...

AI Technical Summary

Problems solved by technology

[0005] The disadvantages of the above-mentioned passenger flow guidance system in the prior art are: the road traffic guidance practice results show that when the participants in the traffic guidance only know their own interests and ignore the existence and decision-making behavior of other passengers on the road network, it is likely to cause too many passengers. Congregate on the same road segment at the same time, causing traffic jams

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