Securitizing congestion: The congestion call option

Friesz, Terry L.; Mookherjee, Reetabrata; Yao, Tao

doi:10.1016/j.trb.2007.10.002

Cited by 23 publications

(15 citation statements)

References 7 publications

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“…Remark 1: This is a simplified version of networklevel two-point traffic dynamics presented at Friesz et al (2008Friesz et al ( , 2011. Hence, the proof of this proposition is omitted.…”

Section: Feasible Set Of Departure Rate Patterns ( )mentioning

confidence: 99%

Investigating boundary effects of congestion charging in a single bottleneck scenario

Stewart

Liu

et al. 2015

Transport

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Abstract. Many congestion charging projects charge traffic only within part of a day with predetermined congestion tolls. Demand peaks have been witnessed just around the time when the charge jumps up or down. Such peaks may not be desirable, in particular (a) when the resulting peaks are much higher than available capacities; (b) traffic speeding up to get into the charging zone causes more incidents just before the toll rises up to a higher level; or (c) traffic slowing down or parking on the roadside decreases road traffic throughput just before the toll falls sharply. We term these types of demand peaks 'boundary effects' of congestion charging. This paper investigates these effects in a bottleneck scenario and aims to design charging schemes that reduce undesired demand peaks. For this purpose, we observe and analyse the boundary effects utilising a bottleneck model under three types of toll profiles that are indicative of real charging schemes. The first type maintains a constant toll across the charging period, the second type allows the toll to increase from zero to a given maximum level and then decrease back to zero and the third type allows the toll to rise from zero to a given maximum level, remain at this level for a fixed period and then fall down to zero. This investigation shows that all three types of toll profiles can produce greater boundary peak demands than the bottleneck capacity. A significant contribution of this work is that instead of designing an optimal traffic congestion pricing scheme we analyse how existing sub-optimal congestion pricing schemes could be improved and suggest how observed problems may be overcome. Hence, we propose a set of extra requirements to supplement existing principles or requirements for design and implementation of congestion charging, which aim to reduce the adverse consequences of boundary effects. Concluding remarks are made on implications of this investigation for the improvement of existing congestion charging projects and for future research. Keywords: bottleneck models; congestion charging; boundary issues. Notes: Current paper is an entirely updated version of our earlier paper: Ge, Y.-E.; Stewart, K. 2010. Investigating boundary issues arising from congestion charging in a bottleneck scenario, in C. M. J. Tampère, F. Viti, L. H. Immers (Eds.). New Developments in Transport Planning: Advances in Dynamic Traffic Assignment, 303-327. http://dx.doi.org/10.4337/9781781000809.00025 In this new version, we have rewritten the introductory section. Secondly, we are proposing a set of extra requirements for road traffic congestion pricing design and implementation in a newly-added section. Thirdly, three new tables have been generated and the data in them are used to support our analysis while four new figures are added to show the advantages of the adopted bottleneck model over the existing ones. Besides, we significantly improved the presentation and analysis of numerical results as well as corrected the errors and typos in the earlier version througho...

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“…Remark 1: This is a simplified version of networklevel two-point traffic dynamics presented at Friesz et al (2008Friesz et al ( , 2011. Hence, the proof of this proposition is omitted.…”

Section: Feasible Set Of Departure Rate Patterns ( )mentioning

confidence: 99%

Investigating boundary effects of congestion charging in a single bottleneck scenario

Stewart

Liu

et al. 2015

Transport

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“…It is rather difficult to find examples of transportation papers that have followed such an approach, but one exception is that of Friesz et al (2008). This paper exploits the theory of stochastic differential equations to propose a model based on Brownian motion, which distinguishes separate notions of deterministic change and stochastic variation.…”

Section: Example 8: Capturing Stochasticity Through Brownian Motionmentioning

confidence: 99%

“…As noted above, we maintain the focus of the present paper on discrete-time (day-to-day) systems in which the state variables are simple variables rather than functions of (within-day) time, and so modify and the continuous-time approach of Friesz et al (2008). Thus we suppose that within-day time is divided into n discrete time periods, with travellers assumed to make a joint choice of route and departure time among the 2n alternatives therefore possible in our two-route network.…”

Section: Example 8: Capturing Stochasticity Through Brownian Motionmentioning

confidence: 99%

Model Representation & Decision-Making in an Ever-Changing World: The Role of Stochastic Process Models of Transportation Systems

Watling

Cantarella

2013

Netw Spat Econ

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We review and advance the state-of-the-art in the modelling of transportation systems as a stochastic process. The conceptual and theoretical basis of the approach is explained in detail. A variety of examples are given to motivate its use in the field. While the examples cover a wide range of modelling philosophies, in order to provide focus they are restricted to modelling a special class of problems involving driver route choice in networks. Our overall objective is to establish the applicability of this approach as a unifying framework for modelling approaches involving dynamic and stochastic elements, developing further the ideas put forward in Cantarella & Cascetta (1995). Directions for further development and research are identified.

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“…As explained in Section 2, the additional travel cost imposed on link 1 is calculated following the first part of Equation (84), to be more specific, the integral R t a t ð Þ t a s ð Þds in this example. As the environmental capacity constraint is greater than the access control restriction for link 2, 8 t 2 [0, T], no pollution pricing should be implemented on this link, which is reflected by Figure 6(b) 6 wherein the additional travel cost (integral of the corresponding Lagrange multiplier) caused by the environmental capacity constraint is zero throughout the entire planning horizon. As the access control is activated, an amount of access price is charged to maintain the traffic volume on the link.…”

Section: The Deterministic Queuing Model Casementioning

confidence: 99%

“…As the access control is activated, an amount of access price is charged to maintain the traffic volume on the link. For link 1, the access pricing is first activated because the access control constraint is smaller than the 6 In the legend of this figure, "AC" means the access control, whereas "AP" means the air pollution control.…”

Section: The Deterministic Queuing Model Casementioning

confidence: 99%

Dynamic marginal cost, access control, and pollution charge: a comparison of bottleneck and whole link models

Zhong

Sumalee

Maruyama

2012

J of Advced Transportation

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SUMMARY In this paper, we investigate theoretical constructions and properties of three interrelated travel demand management measures including marginal cost pricing, access control, and pollution charge under dynamic traffic assignment framework. For congested traffic networks modeled by the two vertical queue models, that is, the whole link model and the deterministic queuing model, on which flows are controlled, we derive dynamic marginal costs for paths and users' external costs for controlled links. As a strategy to implement the access control, the access pricing is formulated as a dynamic system optimal assignment with access (e.g., traffic volume, queue) control problem, wherein the access constraints represent the restrictions on the traffic volumes and/or environmental constraints. For the whole link model case, an optimal control problem formulation is adopted to investigate the dynamic traffic equilibrium. We derive and discuss the necessary condition for operating the transportation system with capacity/environmental constraints optimally. For the deterministic queuing model case, the inflow to a bottleneck is saturated such that no queue would be formed. The dynamic externalities of the two models are compared. It is found that different externality structures of the two models result in different tolling structures to achieve dynamic system optimal assignment. On the basis of this access pricing analysis and an “equivalent” environmental capacity that converts the environmental constraint into traffic volume restriction, we investigate the traffic‐induced air pollution pricing scheme. Copyright © 2012 John Wiley & Sons, Ltd.

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Securitizing congestion: The congestion call option

Cited by 23 publications

References 7 publications

Investigating boundary effects of congestion charging in a single bottleneck scenario

Investigating boundary effects of congestion charging in a single bottleneck scenario

Model Representation & Decision-Making in an Ever-Changing World: The Role of Stochastic Process Models of Transportation Systems

Dynamic marginal cost, access control, and pollution charge: a comparison of bottleneck and whole link models

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