Method and system for precisely inducing passenger flow in multiple scenes of urban rail transit

Abstract

The invention provides a method and a system for accurately inducing passenger flow in multiple scenes of urban rail transit, and belongs to the technical field of urban rail transit train operation control. The method comprises the following steps: establishing a passenger path selection behavior model taking utility maximization as a target under multi-scene induction information; calculating the time when the passenger passes through each section and each transfer station on the effective path, quantitatively evaluating the overall congestion level of the path based on the congestion condition of each section and each transfer station at the corresponding time, and reflecting the congestion degree; sorting the feasible paths based on the passenger path selection behavior model; and forthe sorted feasible paths, optimizing path selection behavior model parameters in combination with a Q-learning learning algorithm to obtain an optimal induction path. According to the method, the feasible paths are sorted in combination with related factors such as congestion degree, time and transfer times, and are recommended to passengers as induction information; and finally, parameters of the path selection behavior model are optimized in combination with a reinforcement learning method, so that the informatization level and the service quality of urban rail transit are effectively improved.

Description

technical field [0001] The invention relates to the technical field of urban rail transit train operation control, in particular to a method and system for precisely inducing passenger flow in multiple scenarios of urban rail transit. Background technique [0002] In recent years, the operating mileage and traffic volume of my country's urban rail transit have been among the top in the world, and it has shown characteristics such as networking, large passenger flow, and high density. Rail transit has become a key support for urban operation. However, the capacity of some sections of the line and stations during peak hours is insufficient, and the section load rate during peak hours and the density of station platforms continue to be too high, which has become the norm in subway operations. It is urgent to induce and manage the travel process of passengers during peak hours. Although there has been some research progress in induction theory at home and abroad, it is mainly co...

AI Technical Summary

Problems solved by technology

Although there has been some research progress in induction theory at home and abroad, it is mainly concentrated in the field of road traffic, and there are few studies on the direction of passenger flow induction in rail transit; in terms of the practical application of induction technology, the application of induction systems in Chinese cities is too simple, It cannot meet the information needs of passengers in diverse and multi-scenes, so it is very important for the precise guidance of passenger flow in urban rail transit in multiple scenarios

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