Abstract
This study proposed a mathematical model for designing a feeder transit service for improving the service quality and accessibility of transportation hubs (such as airport and rail station). The proposed model featured an integrated framework, which simultaneously guided passengers to reach their nearest stops to get on and off the bus, designed routes to transport passengers from these selected pick-up stops to the transportation hubs, and calculated their departure frequencies. In particular, the maximum walking distance, the upper and lower limits of route frequencies, and the load factor rate of each route were fully accounted for in this study. The main objective of the proposed model was to simultaneously minimize the total walking, riding time, and waiting time of all passengers. As this study explored an NP-hard problem, a two-stage genetic algorithm combining the Dijkstra search method was further developed to yield metaoptimal solutions to the model within an acceptable time. Finally, a test instance in Chongqing City, China, demonstrated that the proposed model was an effective tool to generate a pedestrian, route, and operation plan; it reduced the total travel time, compared with the traditional model.
Highlights
Feeder transit system (FTS) aims at arranging access to vehicles located at different depots at all demand points and transporting residents from these selected pick-up stops to transportation hubs. e FTS transit network, including a set of nodes and links between them, is regarded as an effective tool to provide a better first/ last mile service to and from the major fixed-route transit networks
Frequencies were increased to improve the level of service under hub-and-spoke route structures, while they were reduced in fully connected route structures
The majority of FTS have neglected an integrated operation of designing transit route structures and setting their frequencies [1, 4, 5]. erefore, it is especially important to optimize a combination of FTS route design and frequency setting to reveal an optimal relationship between in-vehicle congestion and waiting time at bus stops
Summary
Feeder transit system (FTS) aims at arranging access to vehicles located at different depots at all demand points and transporting residents from these selected pick-up stops to transportation hubs (rail station and airport, etc.). e FTS transit network, including a set of nodes (transportation hubs, bus stops, demand points, and depots) and links between them, is regarded as an effective tool to provide a better first/ last mile service to and from the major fixed-route transit networks. Erefore, it is especially important to optimize a combination of FTS route design and frequency setting to reveal an optimal relationship between in-vehicle congestion and waiting time at bus stops Another important observation was that most studies made an assumption of locations of demand points being pick-up stops and all stops being visited. E study focused on some research tasks as follows: (1) determination of the optimal design of FTS route and frequency with the assignment of all demand points to selected pick-up stops and (2) creation of a genetic algorithm- (GA-) based heuristic approach to efficiently find good solutions to such an NP-hard problem.
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