A methodology for choosing between fixed‐route and flex‐route policies for transit services

Qiu, Feng; Li, Wenquan; Haghani, Ali

doi:10.1002/atr.1289

Cited by 48 publications

(20 citation statements)

References 32 publications

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“…Nourbakhsh and Ouyang [16] developed a new structured point deviation system that outperforms fixed-route transit under low-tomoderate demand levels. Qiu et al [17] explored the feasibility of replacing fixed-route transit with point deviation policies and derived the switching demand densities between the two policies. Qiu et al [18] presented a new demi-flexible transit system and compared its performance with fixedroute and point deviation services.…”

Section: Literature Reviewmentioning

confidence: 99%

A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services

Zheng

Qiu

2018

Journal of Advanced Transportation

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Flexible transit services, which bring together the characteristics of fixed-route transit and demand-responsive transit, have been proven to be cost-efficient in low-density residential areas. In this paper, a methodology is proposed to assist planners in making better decisions when choosing between route deviation policy and point deviation policy, which are two promising types of flexible transit services. A user cost function is developed to measure the service quality of the transit systems, and analytical models are constructed to compare the system performance under both expected and unexpected demand levels. Based on the experiments for various scenarios over a real-life transit example, the critical demands, which represent the switching point between the two competing service policies, have been derived. Our findings show that point deviation policy is more efficient at low-demand levels, while route deviation policy is a better choice at low-to-moderate demand levels. At unexpectedly high demand levels, route deviation policy is better able to accommodate rejected passengers than point deviation policy.

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Section: Literature Reviewmentioning

confidence: 99%

A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services

Zheng

Qiu

2018

Journal of Advanced Transportation

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“…In our study, the service time fluctuation is not taken into account because it can be considered as part of the travel time between two stops. is line has been widely regarded as a benchmark and testbed of flex-route transit for comparing and evaluating different system settings, models, and solution methods [2,8,10,11,24,25]. e default parameter values are shown in Table 1.…”

Section: Travel Time Fluctuationmentioning

confidence: 99%

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Zheng

Gao

2021

Discrete Dynamics in Nature and Society

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To improve the reliability, responsiveness, and productivity of the flex-route transit service, this paper investigates the vehicle scheduling and routing problem under a dynamic operating environment. First, we discuss the new operating polices after the introduction of intelligent transportation systems (ITSs), including automatic vehicle location (AVL) system, mobile data terminal (MDT), and computer-aided dispatch (CAD) system. Second, a mixed integer programming (MIP) formulation is employed to solve the offline routing problem. Third, an online scheduling scheme is presented to tackle different dynamic events, such as dynamic requests, travel time fluctuations, cancellations of requests, and customer no-shows. Finally, simulation experiments based on a real-life flex-route transit service are conducted to assess the influence of different dynamic events. The results demonstrate that the proposed scheduling scheme is reliable for coping with various dynamic events, and our findings can be used to guide the policy making of flex-route transit services.

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“…Consider the fixed-route transit service for passengers with N stations (see Figure 2). It is a rectangle area with width 2W and length L. Based on the proof by Qiu et al [33], the expected value of walking time E(t wk ) for passengers to their nearest stations can be expressed as:…”

Section: B Fixed-route Policy Analytical Modelingmentioning

confidence: 99%

Fare Strategy for Flex-Route Transit Services: Case Study in Los Angeles

et al. 2019

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Flex-route transit service is now the most popular type of flexible transits to serve low-demand areas. In this paper, we develop a strategy to help transit planners to determine fare policies when the current traditional fixed-route transits turn to a flex-route operating policy. Analytical modeling and simulations are developed to appraise the service quality provided to different groups of passengers under these two operating policies. To be closer to reality, two criterions, defined as Criterion (NRP) and Criterion (RP), are introduced for further analysis based on the processing of the passengers refused by deviation service. Criterion (NRP) represents the scenario that the refused passengers would switch to other means of transportation and not be considered in the calculation of service quality function, and Criterion (RP) means that the refused passengers would walk to nearest checkpoints for expected service vehicle and be considered in the assessment of cost indicators. In various scenarios, where demand responsive requests pay additional money for personal deviation services and regular riders could expect a discounted fare for the imposed delay, optimal fare policies are derived based on the change of service quality after applying flex-route operating policy. Also, it is found that only fares of regular riders are susceptible to the choice between Criterion (NRP) and Criterion (RP).

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A methodology for choosing between fixed‐route and flex‐route policies for transit services

Cited by 48 publications

References 32 publications

A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services

A Methodology for Choosing between Route Deviation and Point Deviation Policies for Flexible Transit Services

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Fare Strategy for Flex-Route Transit Services: Case Study in Los Angeles

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