Abstract
A flexible bus route optimization scheduling model that considers the dynamic changes of passenger demand is proposed to address the large difference in demand for flexible bus passengers and real-time variability. This model uses the heuristic algorithm based on gravity model to determine the following: passenger booking; vehicle passenger capacity; team known conditions such as size, according to the dynamic changes of passenger demand for real-time iterative update shuttle travel time; vehicle operating costs (vehicle); and time cost for passengers (passengers waiting time for the vehicle, actual time of arrival, and the difference between expected and actual times of arrival) before minimization as the target. Finally, the practicabilities of the model and algorithm are verified by an example. Analysis results show that for 102 travel demands of 15 randomly generated demand points, completing all services requires 17–21 vehicles with average travel time of 24.59 minutes each. The solution time of 100 groups of data is within 25 seconds and the average calculation time is 12.04 seconds. Under the premise of real-time adjustment of connection planning time, this optimization model can thus better meet the dynamic demand of passengers compared with the current scenario. The model effectively reduces the planning path error, shortens the travel distance and passenger travel time, and achieves better results than the flexible bus scheduling model that ignores changes of connection travel time.
Highlights
How to realize optimal scheduling is the main problem faced by urban public transport operation and management
This system can improve the line service rate, reduce running time, and reduce travel time cost of passengers [1,2,3]. e traditional bus route optimization method is mainly designed based on experience, long-term observation, or IC card data statistical analysis. e objective is to extend, shorten, add, or delete certain lines, adjusting to the optimization and priority that meet the passenger demand of large passenger flow site. is method is mainly suitable for fixed-line bus route optimization with long cycle adjustment [4,5,6,7]. e emergence of flexible buses provides the possibility for dynamic optimization and adjustment of routes [7,8,9,10]
The present study proposes a flexible bus route optimization scheduling method based on passenger dynamic demand and the “many-to-many” pattern. is method considers dynamic changes of passenger demand and the resulting changes of vehicle connection travel time
Summary
How to realize optimal scheduling is the main problem faced by urban public transport operation and management. A good bus scheduling system can quickly optimize and adjust the line operation plan according to the travel needs of passengers. Flexible buses need to calculate the change of vehicle connection travel time caused by changes according to the “dynamic demand” of passengers. These buses need to adjust routes to achieve dynamic optimization. E case of multiple flexible sites corresponding to multiple target sites (the “many-tomany” pattern) has rarely been studied With such consideration, the present study proposes a flexible bus route optimization scheduling method based on passenger dynamic demand and the “many-to-many” pattern. Is method considers dynamic changes of passenger demand and the resulting changes of vehicle connection travel time. A flexible bus route optimization scheduling model is constructed on the basis of the known passenger carrying capacity and vehicle fleet size. en, the connection trip time is updated in real time according to the dynamic variation characteristics of passenger demand and considering the time cost of vehicle operation and passenger travel
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