Balanced flow distribution model based BRT passenger trip benefit optimization method

Abstract

The invention discloses a balanced flow distribution model based BRT passenger trip benefit optimization method. The balanced flow allocation model based BRT passenger trip benefit optimization method comprises the steps that 1, a research object and a research range are selected, and relevant basic information is acquired; 2, the passenger demand characteristics are analyzed: a passenger classification concept meeting passenger OD demands is proposed, a distributable passenger flow and a non-distributable passenger flow are divided, and station passenger flow characteristics are analyzed; 3, a distribution principle is determined: the characteristics of different types of passengers are considered to determine the distribution principle; 4, optimization is performed under constraint conditions: passenger riding time cost, delay time cost, the congestion cost and relevant constraint conditions are considered to determine a target function, and a corresponding optimization algorithm is designed to output an optimal plane. The balanced flow distribution model based BRT passenger trip benefit optimization method fully considers the passenger riding time cost, delay waiting time cost and the total congestion cost based on the passenger trip characteristics, determines a passenger flow distribution scheme according to maximized passenger trip benefits and effectively improves the passenger trip satisfaction and the service quality of a BRT system.

Description

technical field [0001] The invention relates to the technical field of passenger travel benefits of urban bus rapid transit (BRT), in particular to a BRT passenger travel benefit optimization method based on a balanced distribution model. Background technique [0002] At present, in the operation and management of the domestic urban rapid transit system, the travel benefits of passengers have attracted more and more attention. At present, BRT stations are equipped with vehicle information platforms and other information equipment to transmit relevant vehicle information, such as arrival time, etc., but passengers still lack corresponding optimization guidance, especially because there are relatively many arriving vehicles in the channel, and there are many vehicles that can be boarded. And when the distance between the front and rear trains is short, passengers often choose the bus route based on their past experience, that is, choose the route according to their destination...

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Problems solved by technology

[0004] However, there is little research on the balanced flow distribution model in the field of BRT. Anjian studied the cognitive style and travel behavior of passengers under the condition of informatization through intelligent modeling methods, and established a simulation model; Zheng Xiaofeng et al. The passenger load balance model of buses achieves the total load balance of BRT lines through balanced flow distribution, but does not take passenger benefits into consideration. Solving the model by traversal method has certain applicability when the amount of data is small, but Lack of sufficient solution efficiency under big data conditions

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