2020
DOI: 10.1155/2020/8365194
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Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles

Abstract: The last mile travelling problem is the most challenging part when using public transit. This study designs a high-freedom responsive feeder transit (HFRFT) system to serve at the transfer station, given vehicle routes, departure time, and service area based on demand. The proposed feeder transit system employs a travelling mode with multitype vehicles. In order to improve the operation of the HFRFT system, the optimization design methods are suggested for vehicle routes, scheduling, and service area. A mixed … Show more

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Cited by 5 publications
(7 citation statements)
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“…On the other hand, optimising at the same time the size of the vehicles used along with their routes and schedules increases the complexity of the optimisation problem, and suitable solution techniques are needed in order to produce good‐quality solutions in a reasonable time, as pointed out by Wang et al. (2020a).…”
Section: Towards An Integration Of Fixed and Flexible Transport Servicesmentioning
confidence: 99%
“…On the other hand, optimising at the same time the size of the vehicles used along with their routes and schedules increases the complexity of the optimisation problem, and suitable solution techniques are needed in order to produce good‐quality solutions in a reasonable time, as pointed out by Wang et al. (2020a).…”
Section: Towards An Integration Of Fixed and Flexible Transport Servicesmentioning
confidence: 99%
“…Chandra and Quadrifoglio [28] extended this model [18], using a gravity-based accessibility model to evaluate the accessibility impacts for first-/last-mile transport connectivity in the case of fixed-route transit and DRT, although using the same uniform demand across space. Other issues investigated through analytical models were fleet sizing based on a given quality of service for users [10], route design [20,29], and the choice between different flexible transit strategies to accommodate a variable demand level [30], or estimating how user and operator costs vary according to the demand density, the service area [31], and the fleet size [32].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Pan et al [4] optimized irregular service areas and optimal routes with the objectives of maximizing the number of passengers served and minimizing operating costs. Wang et al [3] designed a highdegree-of-freedom responsive transit system and proposed an optimization method for vehicle routing, scheduling and service area. ey also constructed the model by considering factors such as vehicle capacity constraints.…”
Section: Literature Reviewmentioning
confidence: 99%
“…is key factor makes the relationship between users and operators balanced [3]. It can help operators determine the service areas to make them efficient and attractive enough to the public.…”
Section: Introductionmentioning
confidence: 99%