A hybrid implementation mechanism of tradable network permits system which obviates path enumeration: An auction mechanism with day-to-day capacity control

Wada, Koh; Akamatsu, Takashi

doi:10.1016/j.tre.2013.05.008

Cited by 45 publications

(12 citation statements)

References 52 publications

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“…Travelers choose their departure times to minimize individual travel cost including travel delay cost and schedule delay cost. Based on this model, various issues have been studied, e.g., existence and uniqueness of user equilibrium solution at a single bottleneck (Smith, 1984;Daganzo, 1985;Lindsey, 2004); road pricing, tradable credits, and tradable permits to manage traffic congestion (Arnott et al, 1990;Laih, 1994;Xiao et al, 2012;Tian et al, 2013;Nie and Yin, 2013;Wada and Akamatsu, 2013); stochastic bottleneck capacity and travel demand (Arnott et al, 1999;Lindsey, 2009;Xiao et al, 2015); morning commute with heterogeneous travelers (Arnott et al, 1994;van den Berg and Verhoef, 2011;Liu and Nie, 2011;Liu et al, 2014b;Liu et al, 2015a;Liu et al, 2015c); integrated problem of parking and morning commute (Arnott et al, 1991;Zhang et al, 2008;Qian et al, 2011;Qian et al, 2012;Yang et al, 2013;Liu et al, 2014a;Xiao et al, 2016); capacity drop and/or hypercongestion (Arnott, 2013;Liu et al, 2015b;Liu and Geroliminis, 2016); complementarity formulation or ordinary differential equation formulation (Ramadurai et al, 2010;Wu and Huang, 2015;Wang and Xu, 2016).…”

Section: ! Introductionmentioning

confidence: 99%

Modeling and managing morning commute with both household and individual travels

Liu

Zhang

Yang

2017

Transportation Research Part B: Methodological

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This study investigates the morning commute problem with both household and individual travels, where the household travel is a shared ride of household (family) members. In particular, it considers the situation when a proportion of commuters have to drive their children to school first and then go to work (household travel). For household travel, departure time choice is a joint decision based on all household membersÕ preferences. Unlike the standard bottleneck model, the rush-hour dynamic traffic pattern with mixed travelers (household travelers and individual travelers) varies with the numbers of individual travelers and households, as well as the schedule difference between school and work. Given the numbers of individual travelers and households, we show that by appropriately coordinating the schedules of work and school, the traffic congestion at the highway bottleneck can be relieved, and hence the total travel cost can be reduced. This is because, departure/arrival of individual and household travels can be separated by schedule coordination. System performance under schedule coordination is quantified in terms of the relative proportions of the two classes of travelers and is compared with the extreme case when the same desired arrival time applies to both schooling and working. Furthermore, the efficiency of work and school schedule coordination in reducing travel cost is bounded. This efficiency is also compared with that at the system optimum where queuing is fully eliminated and schedule delay cost is minimized (achieved by a joint scheme of first-best pricing and schedule coordination).

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Section: ! Introductionmentioning

confidence: 99%

Modeling and managing morning commute with both household and individual travels

Liu

Zhang

Yang

2017

Transportation Research Part B: Methodological

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“…This study focuses on the equilibrium state realized by applying TBP, not on the process of trading the permits. One example of the process is discussed by Wada and Akamatsu (2013).…”

Section: Congestion Pricingmentioning

confidence: 99%

Pareto-improving social optimal pricing schemes based on bottleneck permits for managing congestion at a merging section

Sakai

Liu

Kusakabe

et al. 2017

International Journal of Sustainable Transportation

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“…One such a scheme is the tradable credit scheme (Verhoef et al 1997;Viegas 2001;Yang and Wang 2011;Wu et al 2012;Nie and Yin 2013) and another is the tradable permit system (Akamatsu 2007;Wada and Akamatsu 2013). In tradable mobility credit scheme, the government sets a predetermined congestion reduction goal and tries to achieve it by creating a market for mobility credits.…”

Section: Related Workmentioning

confidence: 99%

Analysis of dynamic decision-making in a bicycle-sharing auction using a dynamic discrete choice model

Hara

Hato

2017

Transportation

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For clarifying the usefulness and practical issues of a tradable permit system empirically, we implemented a tradable permit system for a bicycle-sharing service in Yokohama city, Japan. We analyzed both travel and transaction behavior within this system. Many activity factors, such as the amount of free time in each day, home location and travel mode to the bicycle port, were shown to affect the transaction of tradable permits. The results of the pilot program indicated that inefficient allocation of tradable permits occurred when participants postponed their decision-making because of uncertainty. To determine the reason for this effect and the contributing factors, we created a dynamic discrete choice model to describe the choice results and timing. The estimation result indicated that the option value of postponing decision-making caused the transactions to be performed at the last minute, and that this effect blocked the liquidity of the permits trade. In addition, because the result reveals that there was heterogeneity in the time discount factor, the initial allocation of permits was found to be important for efficient allocation.

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A hybrid implementation mechanism of tradable network permits system which obviates path enumeration: An auction mechanism with day-to-day capacity control

Cited by 45 publications

References 52 publications

Modeling and managing morning commute with both household and individual travels

Modeling and managing morning commute with both household and individual travels

Pareto-improving social optimal pricing schemes based on bottleneck permits for managing congestion at a merging section

Analysis of dynamic decision-making in a bicycle-sharing auction using a dynamic discrete choice model

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