A survey on planning semi-flexible transit systems: Methodological issues and a unifying framework

Errico, Fausto; Crainic, Teodor Gabriel; Malucelli, Federico; Nonato, Maddalena

doi:10.1016/j.trc.2013.08.010

Cited by 94 publications

(50 citation statements)

References 24 publications

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“…More specifically, the route deviation systems are much more constrained than those allowed for point deviation; they must operate along a well-defined path and deviate to serve curb-to-curb requests within a service area around the path [9]. On the other hand, route deviation systems have a lower administrative/dispatch requirements and are easier to operate than point deviation services.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For this condition, the expected walking time is equal to the result from (8). The expected waiting of the type I, type II, and flag request type III passengers can be derived by (9).…”

Section: At the Expected Demand Levelmentioning

confidence: 99%

“…At unexpectedly high demand levels, the expected waiting of the type I, type II, and flag request type III passengers can be calculated by replacing with in (9). The expected waiting time of curb-to-curb type III passengers can be expressed as…”

Section: At the Expected Demand Levelmentioning

confidence: 99%

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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%

“…For this condition, the expected walking time is equal to the result from (8). The expected waiting of the type I, type II, and flag request type III passengers can be derived by (9).…”

Section: At the Expected Demand Levelmentioning

confidence: 99%

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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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“…The introduction of HT systems has been demonstrated to overcome the shortcomings of pure DRT, such as relatively high operational cost and lack of flexibility in route design with long pre-booking time (Westerlund et al 2000). HT operation types can be classified into six major groups: route deviation, point deviation, demand-responsive connector, request stops, flexible-route segments and zone route (Errico et al 2013). They are depicted in Figure 2.1 and are briefly described as follows:…”

Section: Htmentioning

confidence: 99%

Optimization of demand-responsive transit systems using zonal strategy

Lin

2018

International Journal of Urban Sciences

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In this thesis, two mathematical models were developed and applied to optimize demandresponsive transit systems using zonal strategies. Demand-responsive transit systems provide services between a residential area and a terminal. The first model considers a scenario where the terminal is located outside the service area, which optimizes the area of zones and bus capacity by minimizing the costs occurring within the entire service area; while the second model designs the transit system with its terminal sitting within the service area by minimizing the costs generated in service zones separately. Case studies for the application of both models were conducted for a presumptive demand-responsive transit system operating in northwest Calgary,showing that the models can successfully assist in designing demand-responsive transit systems.Furthermore, sensitivity analysis was conducted to identify the sensitivity of the model output to each model parameter.iii Acknowledgements

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“…A succinte review on taxi and urban demand-responsive system are given in [1,2,4,3,6,5,8] where Multi-agent-based model of simulation has been build for urban dynamic traffic services to addressing the problem of traffic congestion, CO 2 emissions, air pollution, accidents financial costs, and other environmental damages.…”

Section: Sky-car Network -Notion Of Maglev-graphmentioning

confidence: 99%

Dynamic Model for Assignment in a ‘Sky-Car’ Transit System: Spatial Interactions with Other Common Transport Modes

Sossoe

Lebacque²

2016

Traffic and Granular Flow '15

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This chapter provides Lagrangian dynamic fluid model of the traffic of personal rapid maglev transporters or personal rapid transit (PRT). The transport system using these maglev transporters -named sky-cars or sky-podcars -operate in the style of demand-responsive system. The dynamical evolution of sky-podcar travelers' demand is modelled and the problem of relocation of podcars is addressed. In a multimodal transport mobility, we describe assignment in such transit system, and its spatial interactions with other common transportation systems.

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A survey on planning semi-flexible transit systems: Methodological issues and a unifying framework

Cited by 94 publications

References 24 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

Optimization of demand-responsive transit systems using zonal strategy

Dynamic Model for Assignment in a ‘Sky-Car’ Transit System: Spatial Interactions with Other Common Transport Modes

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