A Pareto-improving and revenue-neutral scheme to manage mass transit congestion with heterogeneous commuters

Tang, Yili; Yang, Hai; Wang, Bo; Huang, Jian; Bai, Yunyun

doi:10.1016/j.trc.2019.05.016

Cited by 37 publications

(11 citation statements)

References 27 publications

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“…On the theoretical front, promising new findings by Tang et al. ( 2020a , b ) indicate that the integration of fare-reward schemes with non-rewarding uniform fares may achieve demand management goals revenue neutrally.…”

Section: Practical Demand Management Methodsmentioning

confidence: 99%

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Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis

2021

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Dense urban areas are especially hardly hit by the Covid-19 crisis due to the limited availability of public transport, one of the most efficient means of mass mobility. In light of the Covid-19 pandemic, public transport operators are experiencing steep declines in demand and fare revenues due to the perceived risk of infection within vehicles and other facilities. The purpose of this paper is to explore the possibilities of implementing social distancing in public transport in line with epidemiological advice. Social distancing requires effective demand management to keep vehicle occupancy rates under a predefined threshold, both spatially and temporally. We review the literature of five demand management methods enabled by new information and ticketing technologies: (i) inflow control with queueing, (ii) time and space dependent pricing, (iii) capacity reservation with advance booking, (iv) slot auctioning, and (v) tradeable travel permit schemes. Thus the paper collects the relevant literature into a single point of reference, and provides interpretation from the viewpoint of practical applicability during and after the pandemic.

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Section: Practical Demand Management Methodsmentioning

confidence: 99%

“…This version of the tradeable credit scheme is in fact equivalent to a revenue neutral monetary surcharge-reward scheme proposed by Kalmanje and Kockelman ( 2004 ) for road pricing, and more recently adapted to public transport by Tang et al. ( 2020b ). Moreover, Bao et al.…”

Section: Practical Demand Management Methodsmentioning

confidence: 99%

Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis

2021

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“…On the other hand, some studies in recent years have also found that, in addition to reasonable bus line design, the differentiated fares can also improve the efficiency of the traffic system; compared with the traditional fare scheme, differentiated bus fares strategy often has more advantages [9,10]. The differentiated fares system can effectively reduce travelers' time cost and alleviate traffic congestion during peak hours [11,12]. The implementation of differentiated fares based on comfort level can reduce social costs and is more conducive to the public transport system than charging congestion fees [13].…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Optimization of Differentiated Urban Ring Road Bus Lines and Fares Based on Travelers’ Interactive Reinforcement Learning

Zhu

2021

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This paper proposes a new multi-objective bi-level programming model for the ring road bus lines and fare design problems. The proposed model consists of two layers: the traffic management operator and travelers. In the upper level, we propose a multi-objective bus lines and fares optimization model in which the operator’s profit and travelers’ utility are set as objective functions. In the lower level, evolutionary multi agent model of travelers’ bounded rational reinforcement learning with social interaction is introduced. A solution algorithm for the multi-objective bi-level programming is developed on the basis of the equalization algorithm of OD matrix. A numerical example based on a real case was conducted to verify the proposed models and solution algorithm. The computational results indicated that travel choice models with different degrees of rationality significantly changed the optimization results of bus lines and the differentiated fares; furthermore, the multi-objective bi-level programming in this paper can generate the solution to reduce the maximum section flow, increase the profit, and reduce travelers’ generalized travel cost.

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“…To implement B.1 and B.2, the same amount of demand-side information would be required when setting the credit price of capacity segments as what differentiated pricing requires (see Section 4.2), to ensure that demand never exceeds the critical occupancy rate. This version of the tradeable credit scheme is in fact equivalent to a revenue neutral monetary surcharge-reward scheme proposed by Kalmanje and Kockelman (2004) for road pricing, and more recently adapted to public transport by Tang et al (2020b). Moreover, Bao et al (2019) show that option B.1 might lead to an unstable equilibrium in the standard bottleneck model, and therefore the welfare gain it provides is also uncertain.…”

Section: Practical Applicabilitymentioning

confidence: 99%

Social Distancing in Public Transport: Mobilising New Technologies for Demand Management under the COVID-19 Crisis

2020

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A Pareto-improving and revenue-neutral scheme to manage mass transit congestion with heterogeneous commuters

Cited by 37 publications

References 27 publications

Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis

Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis

Multi-Objective Optimization of Differentiated Urban Ring Road Bus Lines and Fares Based on Travelers’ Interactive Reinforcement Learning

Social Distancing in Public Transport: Mobilising New Technologies for Demand Management under the COVID-19 Crisis

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