Congestion pricing under operational, supply-side uncertainty

Boyles, Stephen D.; Kockelman, Kara M.; Waller, S. Travis

doi:10.1016/j.trc.2009.09.006

Cited by 31 publications

(21 citation statements)

References 40 publications

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“…To do so, two categories of capacity constraintsphysical and environmental (emissions)-are introduced (Ferrari 1997; Yang and Bell 1997;Chen, Zhou, and Ryu 2011). A2 The travel demand between each origin-destination (OD) pair is a random variable with a known probability distribution that can be discretized as a finite set of demand scenarios or realizations (Gardner et al 2008;Yin et al 2009;Boyles, Kockelman, and Waller 2010). The objective of the road toll design model developed in this study is to minimize the linear bi-criteria combination of the expected value of the total system travel disutility (i.e., total user travel time plus total emissions) and its semi-deviation risk measure over all demand scenarios.…”

Section: Assumptionsmentioning

confidence: 99%

Environmentally Sustainable Toll Design for Congested Road Networks with Uncertain Demand

Lam

Wong

et al. 2012

International Journal of Sustainable Transportation

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This article proposes a new road toll-design model for congested road networks with uncertain demand that can be used to create a sustainable urban transportation system. For policy assessment and strategic planning purposes, the proposed model extends traditional congestion pricing models to simultaneously consider congestion and environmental externalities due to vehicular use. Based on analyses of physical and environmental capacity constraints, the boundary conditions under which a road user on a link should pay either a congestion toll or an extra environmental tax are identified. The sustainable toll design model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of the future travel demand aims to minimize a risk-averse objective by determining the optimal toll. The second stage after the uncertain travel demand has been determined is a scenario-based route choice equilibrium formulation with physical and environmental capacity constraints. A heuristic algorithm that combines the sample average approximation approach and a sensitivity analysisbased method is developed to solve the proposed model. The upper and lower bounds of the model solution are also estimated. Two numerical examples are given to show the properties of the proposed model and solution algorithm and to investigate the effects of demand variation and the importance of including risk and environmental taxation in toll design formulations.

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Section: Assumptionsmentioning

confidence: 99%

Environmentally Sustainable Toll Design for Congested Road Networks with Uncertain Demand

Lam

Wong

et al. 2012

International Journal of Sustainable Transportation

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“…These early works required a number of strong assumptions that later research has relaxed: more sophisticated pricing models can address reliability and uncertainty [5], [6], variations in value of time across the population [7], [8], real-time travel information [9], [10], and adaptive, dynamic pricing [11], [12]. The work presented here is distinctive in its focus on applying market forces at intersections, rather than roadway segments.…”

Section: Related Workmentioning

confidence: 99%

Auction-based autonomous intersection management

Carlino

Boyles

Stone

2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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206

138

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Abstract-Autonomous vehicles present new opportunities for addressing traffic congestion through flexible traffic control schemes. This paper explores the possibility that auctions could be run at each intersection to determine the order in which drivers perform conflicting movements. While such a scheme would be infeasible for human drivers, autonomous vehicles are capable of quickly and seamlessly bidding on behalf of human passengers. Specifically, this paper investigates applying autonomous vehicle auctions at traditional intersections using stop signs and traffic signals, as well as to autonomous reservation protocols. This paper also addresses the issue of fairness by having a benevolent system agent bid to maintain a reasonable travel time for drivers with low budgets. An implementation of the mechanism in a microscopic simulator is presented, and experiments on city-scale maps are performed.

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“…A2 The future urban population is assumed to be a random variable with a given continuous probability distribution, which can be approximately discretised as a finite set of population scenarios (see, e.g. Yin et al 2009, Boyles et al 2010, Li et al 2012b. A3 Each household is assumed to have one worker who makes one commuting journey per day.…”

Section: Basic Assumptions and Notations 21 Assumptionsmentioning

confidence: 99%

An integrated design of sustainable land use and transportation system with uncertainty in future population

Li¹,

Li²,

Lam³

2012

Transportmetrica A: Transport Science

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This article proposes a new model for integrated design of a sustainable land use and transportation system with uncertainty in future population. In the proposed model, the future population in the urban area is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to road capacity expansion, housing and employment supplies and environmental impacts is incorporated to consider the sustainability of urban land development and transportation infrastructure improvement. The proposed model is formulated as a two-stage robust optimisation problem. The first stage of the proposed model (before the future urban population is realised) is to optimise the land use and transportation system by maximising a robust riskaverse objective function subject to various chance constraints for consideration of the system sustainability. The second stage of the proposed model, after the future population has been determined, is a scenario-based stochastic location and route choice equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, simulated annealing method and Gauss-Seidel decomposition approach is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that the integrated design of the sustainable land use and transportation system depends very much on the level of uncertainty in future population, capital budget for urban development, and confidence levels of the chance constraints.

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Congestion pricing under operational, supply-side uncertainty

Cited by 31 publications

References 40 publications

Environmentally Sustainable Toll Design for Congested Road Networks with Uncertain Demand

Environmentally Sustainable Toll Design for Congested Road Networks with Uncertain Demand

Auction-based autonomous intersection management

An integrated design of sustainable land use and transportation system with uncertainty in future population

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