关键词: 城市交通, 公交线路规划, 强化学习, 定制公交, 跨区域通行

Abstract:

This paper investigates a customized transit scheduling strategy for urban residents commuting across multiple regions with comprehensively considering the demand of massive urban commuters, as well as the characteristics of transit passenger density and flow in urban network. The Q- learning reinforcement learning improved method is applied to optimize the bus route. Through the integrated road congestion status, passenger demand and residential area location, the reward and punishment function of Q-learning reinforcement learning is set, and the linear coefficient, full load rate and transit time of the customized bus area path are improved. The results show that the proposed improved method can reduce the travel time of commuters across regions, and effectively improve the efficiency of customized bus lines during peak hours.

Key words: traffic engineering, bus route planning, reinforcement learning, custom bus, cross-regional travel