To alleviate peak-hour congestion in urban rail transit, this study proposes a new off-peak fare discount strategy to incentivize passengers to shift their departure time from peak to off-peak hours. Firstly, a questionnaire survey of Shanghai metro passengers is conducted to analyze their willingness to change departure time under different fare strategies. Secondly, based on the survey results, a time-differentiated fare discount model is constructed, considering both the company’s revenue and passengers’ travel benefits, and with the optimization objective of achieving balanced peak-hour and off-peak-hour train loads throughout the day. Subsequently, a genetic algorithm with nested fmincon functions is designed and combined with the actual data of Shanghai rail transit line 9 for arithmetic analysis. Finally, the effectiveness of the model is validated using the survey data. The research results show that the off-peak fare discount strategy can incentivize 6.88% of passengers traveling in the morning peak and 6.66% of passengers traveling in the evening peak to shift to off-peak travel. This research provides theoretical support and decision-making guidance for implementing time-differentiated pricing in urban rail transit systems.

为了缓解城市轨道交通高峰时段的拥堵，本研究提出了一种新的错峰票价折扣策略，以激励乘客将出发时间从高峰时段转移到非高峰时段。首先对上海地铁乘客进行问卷调查，分析不同票价策略下他们改变发车时间的意愿。其次，根据调查结果，综合考虑公司收入和旅客出行效益，以实现全线高峰淡季列车荷载平衡为优化目标，构建分时段票价折扣模型。天。随后设计了嵌套fmincon函数的遗传算法，并结合上海轨道交通9号线的实际数据进行了算术分析。最后，利用调查数据验证了模型的有效性。研究结果显示，错峰票价折扣策略可以激励6.88%的早高峰出行旅客和6.66%的晚高峰出行旅客转向错峰出行。本研究为城市轨道交通系统实施分时定价提供理论支持和决策指导。