Timetable for Multi-Level Bus Transit Considering Differences in Arrival Time
Jinjing Gu, Zhibin Jiang
Abstract
Jinjing Gu, Zhibin Jiang
Abstract
The differences in arrival time at transfer stations, including internal hierarchy and between levels based on layout mode and service characteristics, were considered to maximize the cohesion efficiency of transfer stations and improve the utilization ratio of the network in a multi-level public transit system. In this paper, a timetable model that aims to minimize the cost incurred by passengers and companies was created in terms of departure time and interval. The timetable model was solved by genetic algorithms and subsequently achieved a multi-level bus line running timetable. The model was verified by a numerical example. Calculation results show that although this model increases the investment in public vehicles by 8.5%, the timetable shortens the waiting time of passengers by 23.5% and reduces the overall cost. In the actual operation, the interests of the passengers and public transport companies should be balanced when considering the actual demand.
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The differences in arrival time at transfer stations, including internal hierarchy and between levels based on layout mode and service characteristics, were considered to maximize the cohesion efficiency of transfer stations and improve the utilization ratio of the network in a multi-level public transit system. In this paper, a timetable model that aims to minimize the cost incurred by passengers and companies was created in terms of departure time and interval. The timetable model was solved by genetic algorithms and subsequently achieved a multi-level bus line running timetable. The model was verified by a numerical example. Calculation results show that although this model increases the investment in public vehicles by 8.5%, the timetable shortens the waiting time of passengers by 23.5% and reduces the overall cost. In the actual operation, the interests of the passengers and public transport companies should be balanced when considering the actual demand.
Key concepts: Public transport, Transport engineering, Arrival time, Transfer (computing), Genetic algorithm, Interval (graph theory), Operations research, Transit (satellite)