Move peakhour5/24/2023 In some large cities, peak and low periods are evident owing to the uneven distribution of daily passenger flow. As the main tool to alleviate urban traffic congestion, the subway can transport passengers rapidly. In this context, the development of public transportation has been prioritized to alleviate urban traffic problems. In recent years, traffic congestion caused by the increasingly prominent contradiction between urban traffic demand and supply has become a social problem in countries worldwide. Finally, relevant parameters are discussed. The results show that the objective function is reduced by 17.5%, the congested section is reduced by 9.1% when the full-load rate is 90% of the train loading capacity, and the passenger flow shifts to both ends of the peak period. Based on an example, we obtain the specific fare and passenger flow distribution of each train after fare adjustment. A simulated annealing algorithm is introduced to solve the bilevel model. To achieve a more realistic model, the range of acceptable train numbers for each passenger is considered. The upper level of the model determines the discount factor to minimize the total number of passengers exceeding the full-load rate, and the lower level of the model determines the distribution of passengers on the line, in which the cost-minimizing behavior of each passenger is considered using the allocation method based on the probability of selection. A bilevel model is proposed herein to solve the congestion problem for an urban rail line. In urban rail transit, adjusting fares to satisfy passenger flow requirements is a new method to relieve urban congestion.
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