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.trpro.2019.05.031

Cited by 7 publications

(4 citation statements)

References 23 publications

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“…Therefore, from the perspectives of passengers and agencies, fare is a key factor in transit system design and needs to be taken into account. As discussed in previous works (e.g., Chien and Tsai, 2007;Kim and Schonfeld, 2015;Tang et al, 2017;Yang and Lim, 2017;Palma et al, 2017;Tang et al, 2019;Sun and Szeto, 2019;Tang et al, 2020;Verhoef, 2020;, transit fares generally have different fare structures, such as flat fare, distance-based fare, and time differentiated fare. A time differentiated fare structure is related to the operation time and usually charges a higher fare for peak periods.…”

Section: Demand Elasticitymentioning

confidence: 78%

Bimodal transit design with heterogeneous demand elasticity under different fare structures

Yang

Jiang

Yan

et al. 2023

Transportmetrica A: Transport Science

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Bimodal transit systems (e.g., rail-bus system) have the potential to better cater to passenger demand than conventional unimodal transit systems (e.g., bus-only system).However, the optimal design of bimodal transit systems considering heterogeneous demand elasticity has received little attention in the literature. The study attempts to develop a new optimization model to design a bimodal transit system from a microeconomic view to maximize the profit of a transit agency considering different fare structures. Transit network and service characteristics, such as route and stop densities and headways, can be modified to provide a better service considering the heterogeneous demand elasticity in real-world situations. An elastic demand function is devised to include various time components and incorporate flat, distance-based, and hybrid fares. A nested iterative procedure is developed to find the optimal or near-optimal solution.Numerical experiments reveal some interesting findings. First, the increase in elasticity parameters has a knock-on effect on financial performance, consequently leading to a net profit reduction. Second, a distance-based fare scheme brings in the least actual demand but makes the most profit compared with the flat and hybrid fare schemes. Third, passengers prefer using a rail-bus system to a BRT-bus system, especially at a higher demand level. Meanwhile, bimodal systems can bring the transit agency a higher profit except in an extremely low latent demand scenario. A rail-bus system is the most profitable form when the potential demand exceeds 58,009 pass/h. Thus, bimodal transit systems are generally preferred for cities with a high demand density as opposed to unimodal transit systems.

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Section: Demand Elasticitymentioning

confidence: 78%

Bimodal transit design with heterogeneous demand elasticity under different fare structures

Yang

Jiang

Yan

et al. 2023

Transportmetrica A: Transport Science

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“…e economic bottleneck model [51], which is elaborated by [52,53], is extensively used as a common approach in economic analysis to model the boarding congestion (crowding) and fare incentive schemes [5,6,34,54,55]. ere are five main types of fare incentive methods that reduce the boarding or crowding congestion in metro systems, including the flat fare scheme [56,57], the step fare scheme [58], the time-varying fare [2,59], the trialand-error fare scheme (e.g., [34,35], the fare reward scheme [5], and the hybrid fare scheme [55,60]. Over the past decades, the initial measures of the flat fare scheme developed by [61,62] is prevalent in the early development of metro demand management due to its low-cost characteristic.…”

Section: Approaches To Modeling Boarding Congestion In Metromentioning

confidence: 99%

“…e optimal fare differentials and the optimal reward ratio were determined by an analytic solution under demands. Considering the heterogeneity of the preferred schedules of passengers, the study of [60] proposed a hybrid metro fare scheme by mixing the fare-reward and uniform fare scheme. e analytical results (including UE and SO solutions) and numerical simulation show that this novel fare scheme can significantly reduce travel cost.…”

Section: Approaches To Modeling Boarding Congestion In Metromentioning

confidence: 99%

Hybrid Scheduling Model Based on Fare Incentives for Peak Time Interval of the Metro: The Harbin Metro System

Feng

2022

Journal of Advanced Transportation

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Considering the operation efficiency of the metro system, the boarding queuing problem is a complex and intractable dilemma caused by the security and ticket checking process in urban metro stations, especially for the mass-transit metro system in China. In this study, a novel scheme of fare differentials based on demand control and congestion management for reducing congestion in the metro boarding process was proposed. In addition, we extended Vickrey’s point-queue model into a boarding congestion model incorporating the bidesired departure time considering the security and ticket checking process in stations as a continuum bottleneck. The train-run and departure time choosing behaviors of passengers under different schedule gaps of the adjacent train runs are explored when the boarding system achieves user equilibrium in the proposed model. Then, we examined the demand regulatory mechanisms of fare incentives (fare differentials) in reducing the queuing boarding time in metro stations when the optimization of the schedule gaps is ineffective in the pattern of mass-scale travel demand. The analytical solutions of these two optimal methods (schedule gaps and fare differentials) for boarding congestion management are presented. After comparing the two congestion-reduced methods, the fare incentive rule has a better regulation effect on the smoothing of travel demand. The results of the sensitivity analysis using numerical simulations reveal the regulatory mechanism of fare differentials in reducing the queuing time and increasing the incremental revenue. (1) The demand threshold is only related to the boarding capacity and schedule gaps (i.e., the greater the boarding capacity and schedule gaps, the greater the passenger capacity of the metro station). (2) The effect of fare incentives in reducing the boarding congestion is better if the lower fare is implemented in the later train runs. (3) A lower fare differential between two adjacent metro runs can be used to regulate the proportion of staggered passengers in the queuing line to reduce the crowd gathering in the metro station hall when travel demand is high, meanwhile, a higher fare differential between two adjacent metro shuttles can increase incremental revenue effectively. (4) The measure of fare differentials causes worse results in both the reduction of the queuing time and the increase of the incremental revenue when the metro travel demand is lower than the demand threshold. This conclusion is consistent with the pattern of reality and experience. Therefore, the definition and judgment conditions of demand thresholds, introduced in this study, can provide theoretical guidance when implementing fare incentive policies in aviation and metro networks.

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“…Moreover, Yang and Tang (2018) proposed a novel fare-reward scheme for rail transit that aims to shift commuters from central peak to shoulder peak periods, thereby reducing the waiting time at stations without reducing the revenue of transit operators. A hybrid fare scheme (HFS) is further considered, which integrates a fare-reward scheme and a nonrewarding uniform fare scheme considering commuters' heterogeneous schedules, and it is shown that the proposed HFS is revenue preserving and Pareto-improving (Tang et al, , 2018. Besides, and Tang (2021) proposed a surcharge-reward scheme to reduce crowded conditions and queue congestion in mass transit systems by considering commuters' choice of departure times and equilibrium properties.…”

Section: Incentive Strategies In Transportationmentioning

confidence: 99%

Modeling, equilibrium, and demand management for mobility and delivery services in Mobility‐as‐a‐Service ecosystems

Tang

Waller

et al. 2022

Computer aided Civil Eng

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Mobility-as-a-Service (MaaS) is an emerging business model integrating various travel modes into a single mobility service accessible on demand. Besides the ondemand mobility services, instant delivery services have increased rapidly and particularly boomed during the coronavirus (COVID-19) pandemic, requiring online orders to be delivered timely. In this study, to deal with the redundant mobility resources and high costs of instant delivery services, we model an MaaS ecosystem that provides mobility and instant delivery services by sharing the same multimodal transport system. We derive a two-class bundle choice user equilibrium (BUE) for mobility and delivery users in the MaaS ecosystems. We propose a bilateral surcharge-reward scheme (BSRS) to manage the integrated mobility and delivery demand in different incentive scenarios. We further formulate a bilevel programming problem to optimize the proposed BSRS, where the upper level problem aims to minimize the total system equilibrium costs of mobility and delivery users, and the lower level problem is the derived twoclass BUE with BSRS. We analyze the optimal operational strategies of the BSRS and develop a solution algorithm for the proposed bilevel programming problem based on the system performance under BSRS. Numerical studies conducted with real-world data validate the theoretical analysis, highlight the computational efficiency of the proposed algorithm, and indicate the benefits of the BSRS in managing the integrated mobility and delivery demand and reducing total system equilibrium costs of the MaaS ecosystems. INTRODUCTIONThe coronavirus (COVID-19) outbreak has significantly impacted people's daily lives worldwide. To save lives and prevent the spread of COVID-19, more and more people have to stay home because of social distance guidelines, directives to stay home, and working from home. More than 3.9 billion people in over 90 countries or territories © 2022 Computer-Aided Civil and Infrastructure Engineering.have been asked or ordered to remain at home by their governments by April 2020. Meanwhile, those at home remain in need of essentials, such as medicine, meal, and food, therefore inducing a significant increase in the demand for online shopping and instant delivery services. 11 We use "instant delivery" in this study for the emphasis of the time emergency of the delivery, which is widely used in literature.

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

Cited by 7 publications

References 23 publications

Bimodal transit design with heterogeneous demand elasticity under different fare structures

Bimodal transit design with heterogeneous demand elasticity under different fare structures

Hybrid Scheduling Model Based on Fare Incentives for Peak Time Interval of the Metro: The Harbin Metro System

Modeling, equilibrium, and demand management for mobility and delivery services in Mobility‐as‐a‐Service ecosystems

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