Congestion Pricing Research Articles

An optimal control approach to day-to-day congestion pricing for stochastic transportation networks

Congestion pricing has become an effective instrument for traffic demand management on road networks. This paper proposes an optimal control approach for congestion pricing for day-to-day timescale that incorporates demand uncertainty and elasticity. Travelers make the decision to travel or not based on the experienced system travel time in the previous day and traffic managers take tolling decisions in order to minimize the average system travel time over a long time horizon. We formulate the problem as a Markov decision process (MDP) and analyze the problem to see if it satisfies conditions for conducting a satisfactory solution analysis. Such an analysis of MDPs is often dependent on the type of state space as well as on the boundedness of travel time functions. We do not constrain the travel time functions to be bounded and present an analysis centered around weighted sup-norm contractions that also holds for unbounded travel time functions. We find that the formulated MDP satisfies a set of assumptions to ensure Bellman’s optimality condition. Through this result, the existence of the optimal average cost of the MDP is shown. A method based on approximate dynamic programming is proposed to resolve the implementation and computational issues of solving the control problem. Numerical results suggest that the proposed method efficiently solves the problem and produces accurate solutions.

Legal Tools for Achieving Low Traffic Zones (LTZs): LEZ, ULEZ & Congestion Pricing in the U.S. Law Context

Cities around the world are looking to reduce greenhouse gas and other emissions from vehicles through the use of low emissions zones and congestion pricing. These strategies have been employed to great success abroad, including in central London, where both congestion pricing and fees and restrictions on higher-emitting vehicles are in effect. In the U.S. law context, these policy approaches give rise to significant legal issues that have not been well-explored. With an eye towards U.S. law considerations, Legal Tools for Achieving Low Traffic Zones (LTZs): LEZ, ULEZ & Congestion Pricing in the U.S. Law Context proposes that these policy approaches should be called “Low Traffic Zones,” or LTZs, and surveys those legal considerations. The areas of law explored herein are: (1) potential for preemption of LTZ policies by U.S. federal laws including the Clean Air Act (“CAA”), the Energy Policy and Conservation Act (“EPCA”) and the Federal Aviation Administration Authorization Act (“FAAAA”), (2) U.S. constitutional considerations including the dormant Commerce Clause, (3) federal tolling authority, (4) state enabling law, (5) laws to protect individual privacy and data security and (6) other claims that may be raised in litigation. The paper will conclude by outlining guidance U.S. law- and policy-makers may take into account in drafting LTZ policies to comport with U.S. and state law.

How does environmental concern influence public acceptability of congestion charging? Evidence from Beijing

ABSTRACT As a market-based instrument of transportation demand management, congestion charge can not only effectively reduce traffic congestion, but also improve air quality. However, due to its low public acceptability, this policy only has a few urban practices. As one of the fast-growing metropolises in emerging economies that are facing both traffic congestion and industrial pollution problems, Beijing is now considering the feasibility of implementing congestion charging. Some researchers address that though people with strong environmental concerns are more prone to support congestion charges, the associations between environmental concerns and support for congestion charges are context-dependent. A survey was conducted in Beijing in 2016 to understand how the pollution context in cities of emerging economies affects these associations. We find that the acceptability in Beijing is 33%, and expected policy effects and environmental concerns are the most important impact factors. Due to the influence of the regional industrial pollution context, most residents in Beijing do not consider congestion charge to be an effective way to tackle air pollution. Under these circumstances, even if the public environmental concerns, in general, are high and congestion charges are “marketed” as environmental policies, there is no guarantee that policy support will rise.

Can Tolling Help Everyone? Estimating the Aggregate and Distributional Consequences of Congestion Pricing

Abstract Economists have long advocated road pricing as an efficiency-enhancing solution to traffic congestion, yet it has rarely been implemented because it is thought to create losers as well as winners. In theory, a judiciously designed toll applied to a portion of the lanes of a highway can generate a Pareto improvement, even before using the toll revenue. This paper explores the practical relevance of this theoretical possibility by using survey and travel time data, combined with a structural model of traffic congestion, to estimate the joint distribution of agent preferences over three dimensions—value of time, schedule inflexibility, and desired arrival time—and evaluate the effects of adding optimal time-varying tolls. I find that adding tolls on half of the lanes of a highway yields a Pareto improvement. Further, the social welfare gains from doing so are substantial—up to $1,740 per road user per year.

Tradable permit schemes for congestible facilities with uncertain supply and demand

It is well known that price and quantity regulation are not equivalent under uncertainty. This asymmetry has been a factor in the debate about whether to use taxes or Tradable Permit Schemes (TPS) for controlling greenhouse gas emissions. We analyze the allocative efficiency of a TPS for a congestible facility such as an airport, a road, a recreational area, or a museum that experiences supply and demand shocks. The number of permits issued cannot depend on the state. We compare the efficiency of a TPS and a congestion fee when the level of the fee is similarly constrained to be the same across states. When demand and cost curves are linear, a fee outperforms a TPS for several combinations of additive and/or multiplicative demand and cost shocks. More generally, the ranking depends on the nature and magnitude of demand and cost shocks, the elasticity of the cost function, and whether or not the permit requirement always binds. A TPS tends to perform well when first-best usage levels are similar across states. Analogously, a fee is relatively efficient if first-best fees are similar across states.

Influencing Factors in Congestion Pricing Acceptability: A Literature Review

Roads congestion pricing has been considered as an effective solution following the successful implementation of such programs by many cities such as Singapore, Stockholm, and London. In multiple cases, congestion pricing projects have not been implemented, and multitudinous industrialized countries’ governments are struggling to find an effective and satisfactory way of introducing congestion pricing schemes that will not be affected by the public’s negative opinion and resistance. The lack of political and public acceptability can, therefore, be blamed for the nonimplementation of many congestion pricing projects in many cities around the world. This paper reviews eight cases where congestion pricing schemes were implemented or rejected, as well as the major influencing factors that enable congestion pricing introduction and acceptability by road users, discusses public and political acceptance of urban road pricing, and provides a valuable guideline for policy and decision-makers.

Congestion-clearing payments to passengers

This paper reports on a project that considers whether the goals of (de)congestion pricing could be achieved in whole or in part by incentivizing mode-shift rather than using charging to force it: buying rather than selling decongestion.The project developed a method for estimating the net present value of the costs and benefits of a permanent ITS-enabled program of paying people to travel as passengers rather than as drivers – to reduce existing congestion in a target corridor to a target maximum level of delay – taking into account the mix of the traffic and the potential impact of latent demand and induced trips. This is relevant for making better use of existing infrastructure (a “build nothing” alternative to expansion, but not a “do nothing” one), for decarbonizing transport, and in the run up to automated vehicles where the possibility exists that new infrastructure investments in the 1 – 20-year timeframe will become stranded assets under some future scenarios.The project incorporated: a thorough review of the literature; focus groups; and a survey in a case study corridor in California to test the theory, develop the method, and determine the likely costs and benefits. The main insights include 1) the significance of an ‘intra-peak demand shift’ that would occur if congestion was removed; 2) the need for four major components in a congestion-clearing payments program: a) incentives to switch from driving to being a passenger, b) incentives to travel at less preferred times, c) park and ride/pool facilities near the bottleneck to ease the passenger switch, and d) some limitation on single-occupant vehicle travel in the peak-of-the-peak in order to reserve space for vehicles carrying passengers; and 3) the possible need for different land-use regulations in a successful “payments to passengers” environment where the amount of traffic might no longer be an obvious constraint for expanding the local economy. The case study benefit cost analysis delivers a benefit cost ratio of 4.5 to 1.

Congestion and Incentives in the Age of Driverless Cars

Following the development of autonomous vehicles (AVs) and GPS systems, fleets will gain prominence over private vehicles. We analyze the welfare effects of the transition from a fully decentralized regime, in which all travelers are atomistic and do not internalize the congestion externality, to a centralized regime, where all travelers are supplied by a fleet of AVs controlled by a monopolist. In our model, heterogeneous individuals differing in the disutility from congestion may travel on one of two lanes, which may endogenously differ in the level of congestion, or they may not travel. We show that the monopolist sorts travelers across the two lanes differently than the decentralized regime. Moreover, depending on the severity of congestion costs, it may also exclude some travelers. We find that centralization is always welfare detrimental when the monopolist does not ration travel. If instead rationing occurs, centralization may be welfare beneficial, provided that congestion costs are sufficiently high. We then analyze how to restore first best with road taxes. While congestion charges are optimal under decentralization, taxes differ markedly in a centralized regime, where restoring first best may require subsidizing the monopolist.

Estimating Congestion Cost for Ring Road of Delhi

The study uses relevance of three empirical elements vis-a-vis speed-flow relationship, generalised cost and demand curve in constructing cost curves to estimate congestion cost, marginal external congestion cost (MECC), congestion tax in peak and non peak hours for the inner ring road of Delhi. The research takes an existing model (Prud’homme and Bocarejo, 2005) as starting point and develops cost models for the study area. The application differs from the original model in that it captures costs at the link level rather than at zonal level and computes post charge quantity of road usage by varying elasticity of demand from -0.27 to -0.7. While considering individual links as a homogenous section the results do not show any coherence and thus not a plausible option for analysis of the present study. The link wise analysis seems to be a likely option to predict road pricing at entry and exit links in peak hours as a long term measure in mitigating traffic congestion. The study also predicts elastic behaviour at an individual link level and negative externality burden that motorist imposes on the society. The main result is a tabulation of the MECC’s and congestion charging for the six sections of the ring road of Delhi. It shows interesting differences between sections in terms of not only the averages but also between average and marginal cost values during peak and non peak hours confirming the importance of the approach.

Trial-and-Error Congestion Pricing Scheme for Morning Commute Problem with Day-to-Day Dynamics

A trial-and-error congestion pricing scheme finds the optimal toll based only on observable information (e.g., travel time) without information on travelers’ personal preferences that are often unobservable in practice (e.g., value of time, scheduling preference). This paper proposes a trial-and-error pricing scheme for the morning commute problem, also known as the departure time choice problem and Vickrey’s bottleneck model, with day-to-day dynamics. The proposed scheme is guaranteed to find the social optimal congestion toll under somewhat restrictive assumptions. We numerically confirm that the proposed scheme converges to the social optimal toll regardless of the parameter setting, and it decreased the social cost fairly quickly.

Accident Externality of Driving: Evidence from the London Congestion Charge

This paper estimates the marginal accident externality of driving in Central London by exploiting variation in traffic flow induced by the London Congestion Charge Zone using an instrumental variable approach. The charge attributed to a 9.4% reduction in traffic flow, which resulted in a less than proportional 6.0% and 7.6% decrease in accidents and slight injuries, and a 6.5% increase in serious injuries/fatalities. Our preferred estimates indicate that the accident, slight injuries, and serious injuries/fatalities rate elasticities with respect to traffic flow are -0.36, -0.19 and -1.65 respectively. These estimates imply that the marginal external benefit of road safety from an additional kilometre driven is approximately £ 0.16. The marginal accident externality is positive, as the marginal driver along congested roads decreases the risk and severity of traffic collisions for other road users by slowing others down and increasing awareness.

Accident Externality of Driving: Evidence from the London Congestion Charge

This paper estimates the marginal accident externality of driving in Central London by exploiting variation in traffic flow induced by the London Congestion Charge Zone using an instrumental variable approach. The charge attributed to a 9.4% reduction in traffic flow, which resulted in a less than proportional 6.0% and 7.6% decrease in accidents and slight injuries, and a 6.5% increase in serious injuries/fatalities. Our preferred estimates indicate that the accident, slight injuries, and serious injuries/fatalities rate elasticities with respect to traffic flow are -0.36, -0.19 and -1.65 respectively. These estimates imply that the marginal external benefit of road safety from an additional kilometre driven is approximately £ 0.16. The marginal accident externality is positive, as the marginal driver along congested roads decreases the risk and severity of traffic collisions for other road users by slowing others down and increasing awareness.

A Sample Scheme of Cordon-Based Congestion Charge: Erzurum, Cumhuriyet Street

A Sample Scheme of Cordon-Based Congestion Charge: Erzurum, Cumhuriyet Street

Costly Commuting and the Job Ladder

Even though workers in the UK spent just 1,000 pounds on commuting in 2017, the economic loss may be far higher because of the congestion externality arising from the way in which one worker's commute affects the commuting time of others. I provide empirical evidence that commuting time affects job acceptance, pointing to large indirect costs of congestion. To interpret the empirical facts and quantify the costs of congestion, I build a model featuring a frictional labor market within a metropolitan area. By endogenizing commuting congestion in a labor search model, the model connects labor market responses to urban policies. Workers evaluate job offers based on their productivity and commuting costs, taking congestion as given, but by accepting and commuting to distant jobs, affect other workers' labor market outcomes. Through this mechanism, equilibrium moving decisions, housing rent, and wages are tightly linked to congestion. Calibrating the model to the local labor market around London, I show that the effect of the congestion externality is to significantly decrease welfare and increase wage inequality. I quantify the effects of a congestion tax on labor market outcomes, and show that the welfare-maximizing tax has substantial negative effects on inequality, but comes at a cost of higher unemployment.

To Pool or Not to Pool: Equilibrium, Pricing and Regulation

We study a monopoly transportation network company (TNC) in an aggregate market that offers on-demand solo and pooling e-hail services, while competing with transit for passengers. The market equilibrium is established based on a spatial driver-passenger matching model that characterizes the passenger wait time for both solo and pooling rides. We prove, under mild conditions, this system always has an equilibrium solution. Built on the market equilibrium, three variants of pricing problems are analyzed and compared, namely, (i) profit maximization, (ii) profit maximization subject to regulatory constraints, and (iii) social welfare maximization subject to a revenue-neutral constraint. A comprehensive case study is constructed using TNC data collected in the city of Chicago. We found pooling is desirable when demand is high, but supply is scarce. However, its benefit diminishes quickly as the average en-route detour time (i.e., the difference between the average duration of solo and pooling trips) increases. Without regulations, a mixed strategy—providing both solo and pooling rides—not only achieves the highest profit and trip production in most scenarios, but also gains higher social welfare. The minimum wage policy can improve social welfare in the short term. However, in the long run, the TNC could react by limiting the size of the driver pool, and consequently, render the policy counterproductive, even pushing social welfare below the unregulated level. Moreover, by maintaining the supply and demand of ride-hail at an artificially high level, the minimum wage policy tends to exacerbate traffic congestion by depressing the use of collective modes (transit and pooling). A congestion tax policy that penalizes solo rides promotes pooling, but consistently harms social welfare. However, it promises to increase both social welfare and pooling ratio, when jointly implemented with the minimum wage policy.

Persistent oscillations in a traffic model with decision-making

This work explores the nonlinear behaviour in a congestion charge model, which emphasizes the correlation between drivers’ response and optimal traffic flow. The model assumes that all drivers follow the same common rules of rational thinking to avoid the congestion. There are two regimes in the model system. In free flow regime, the system has only one branch. In congested regime, the system bifurcates into two branches. Counter-intuitive behaviour of the model is caused by the oscillatory instability between two branches. Persistent oscillations reflect the intrinsic properties of decision-making process. Rational thinking provides limited adaptation capabilities to reach the optimal traffic flow. More past experiences and current options provide only marginal increase in capabilities to adapt to traffic situations. The idealized situations are also discussed.

Airport airside congestion pricing considering price discrimination between aircraft type under a Stackelberg game

ABSTRACTThis paper considers flight price discrimination between different aircraft types in an analysis of airport congestion under a Stackelberg game. In addition, we introduce a method to determine the specific total flight volume under which there should be no congestion toll because there is no congestion when total flight volume is low. Furthermore, congestion tolls should be levied on all airlines when total real flight production is between the equilibrium flights in a joint-profit maximization scenario and equilibrium flights in a self-profit maximization scenario.

An Undergraduate Primer on Quality Differentiated Demand

The paper provides a brief exposition on the logic underlying demand for quality-differentiated products. The argument builds and extends on basic constructs from undergraduate microeconomics followed by a brief critique of market responses to consumer preferences for quality variation. Potential extensions are noted, including policy applications in utility pricing tied to quality variations in service reliability, congestion pricing, as well as microeconomic insights into industrial disruption caused by lower quality producers invading markets controlled by higher quality monopolies and the potentially disproportionate impact on lower income households of quality distortions created by monopoly practices.

Simulation-based joint optimization framework for congestion mitigation in multimodal urban network: a macroscopic approach

Travel demand management (TDM) is an important measure that will aid in the realization of efficient and sustainable transportation systems. However, in cities where the most serious traffic congestion occurs, implementation of a single TDM measure might not be enough to reduce congestion, because the congestion mechanism in this case is highly complex and involves different transportation modes interacting with each other. Implementation of multiple TDM measures has rarely been discussed in the literature. Therefore, in this study, we propose a simulation-based joint optimization framework composed of dedicated bus lanes and vehicular congestion pricing. The objective of the optimization process is to minimize the congestion cost based on an advanced macroscopic flow theory called the multimodal macroscopic fundamental diagram (mMFD), which can capture the macroscopic traffic dynamics of multimodal transportation systems. In the proposed framework, we develop mMFD-based congestion pricing scheme and incorporate traveler’s behavioral model (i.e. joint departure time and mode choices) with the microscopic traffic simulator. We consider the Tokyo central area as a case study. The simulation results indicate that space allocation of 4.7% for the dedicated bus lanes would be optimal for Tokyo’s network, while the optimal congestion pricing scheme indicates that charges of 900 JPY between 7:30 and 8:00 AM and 300 JPY between 8.00 and 8:30 AM should be levied.

Public acceptability of congestion charging in Beijing, China: How transferrable are Western ideas of public acceptability?

Public acceptability is a major concern for road pricing schemes in Western countries but has not yet been sufficiently studied in the context of Chinese cities, a number of which are considering the introduction of such travel constraint measures. This study explores factors influencing public acceptability of a proposed congestion charge in the City of Beijing. In so doing, the study focuses on understanding the appropriateness of Western frameworks for assessing public acceptability in the Chinese context.Through literature review and focus groups a survey to test different public acceptability constructs was developed (N = 1104). A Structural Equation Model was used to analyze relationships that exist among the different aspects of public acceptability. The results demonstrate that public acceptability is dominantly influenced by the level of trust toward the Government and experts. Various determinants in the Western context, such as access to information and perceived effectiveness were not found to have a significant impact on public acceptability. The results imply that public acceptability of congestion charging in the Chinese context has a stronger resonance with wider social issues such as equity than more specific transport problems such as congestion. As such, attempting to present evidence on the anticipated effectiveness of the policy in alleviating congestion and smog may not make the policy more acceptable to the public. The overall inference of the study is that contextual factors are more important than has been previously considered within public acceptability studies.