Congestion Pricing

Scientists and policymakers intend worldwide emissions reduction of up to 80 percent of carbon dioxide (CO2) and other greenhouse gases (GHGs) in the next four decades to stabilize atmospheric concentrations (TRB 2011). Henceforth, an immediate response from the transportation sector, one of the largest producers of GHGs (up to 30 percent in the U.S.), is critical for GHGs reduction. Possible long-term solutions towards cutting back on emissions from transportation are increasing supply-of/demand-for more energy/fuel efficient vehicles and to substantially improve the transit system (high-speed rail, passenger rail, metro) to reduce reliance on private vehicles and air travel for short trips. However, the markets are still struggling to produce supply-of/demand-for energy efficient vehicles and public debate on potential ridership of high speed rail is ongoing in the U.S. Another feasible strategy that can prove to be effective is emission pricing. Recent advancement in Intelligent ...

In a stochastic roadway congestion and pricing model, one scheme (omniscient pricing) relies on the full knowledge of each individual journey cost and of early and late penalties of the traveler. A second scheme (observable pricing) is based on observed queuing delays only. Travelers are characterized by late-acceptance levels. The effects of various late-acceptance levels on congestion patterns with and without pricing are compared through simulations. The omniscient pricing scheme is most effective in suppressing the congestion at peak hours and in distributing travel demands over a longer time horizon. Heterogeneity of travelers reduces congestion when pricing is imposed, and congestion pricing becomes more effective when cost structures are diversified rather than identical. Omniscient pricing better reduces the expected total social cost; however, more travelers improve welfare individually with observable pricing. The benefits of a pricing scheme depend on travelers' cost structures and on the proportion of late-tolerant, late-averse, and late-neutral travelers in the population.

This article provides an in-depth review of the state-of-the-art and describes methodological advances in the design and evaluation of road network pricing schemes. A number of paradigm shifts from the two polar cases of the marginal social cost pricing of road traffic congestion and revenuemaximizing road toll pricing are analyzed, as induced by the need to address realistic design complexities and constraints. The crucial role of the joint consideration of pricing strategies with optimal capacity provision and several network management measures is manifested and an integrated evaluation framework is suggested to incorporate a wide range of road pricing impacts into the scheme design process. Keywords Transport networks • Congestion pricing • Road pricing • Network pricing • Network design • Private toll road competition • Capacity investments • Evaluation of pricing schemes T. Tsekeris (B)

Specification tests using stochastic bottleneck models of airport congestion investigate whether dominant airlines internalize or ignore self-imposed delays at twenty-seven major US airports. Data on flight times determine the airport's landing and takeoff delays for every minute of operation during peak travel days. Dynamic congestion functions based on stochastic-queuing theory separately identify delays that aircraft experience directly, impose internally on their airline's other aircraft, or impose externally on other airlines. Specification tests largely reject internalization and fail to reject non-internalization by dominant airlines. Optimal pricing should value all time using non-dominant aircraft time values and treat all delays as external.

This paper describes the modeling of recurring congestion in a network. It is shown that the standard economic models of marginal cost cannot describe precisely traffic congestion in networks during time-dependent conditions. Following a macroscopic traffic approach, we describe the equilibrium solution for a congested network in the no-toll case. A dynamic model of cordon-based congestion pricing (such as for the morning commute) for networks is developed consistent with the physics of traffic. The paper combines Vickrey's theory with a macroscopic traffic model, which is readily observable with existing monitoring technologies. The paper also examines some policy implications of the cordonbased pricing to treat equity and reliability issues, i.e. in what mobility level a city should choose to operate. An application of the model in a downtown area shows that these schemes can improve mobility and relieve congestion in cities.

Manual order picking is considered as one of the costliest and time-consuming processes in a manual picker-to-order system. The process starts with customer orders release. After distributing the orders to multiple order pickers, order picking associates starts to fulfill customer demands. Picking is the process of collecting (picking) the order items from their storage locations. Finding the most efficient route to visit all items locations is the main goal of optimizing order picking routing path. Due to the fact that each warehouse runs its operations with multiple pickers, and the pickers may work in the same zone to pick items on customer orders, congestion may occur during the picking time. This can affect the order picking finishing time. The optimization solution obtained without considering the order picking congestion might not provide the most satisfaction result. Most of the studies focus on the single picker to order systems, where the effect of the congestion does not exist. However, in reality, multiple pickers are used. Therefore, this research will focus on the congested order picking problem, and solve for the best picking route. Literature will be reviewed to identify the studies that consider the congestion effect in multiple picker systems, and to review the models used to represent this problem.

Land transportation remains one of the main contributors of noise and air pollution in urban areas. This is in addition to traffic congestion and accidents which result in the loss of productive activity. While there is a close relationship between traffic volumes and levels of noise and air pollution, transport authorities often assume that solving tragic congestion would reduce noise and air pollutant levels. Tight control over automobile ownership and use in Singapore has contributed in improving traffic flows, travel speeds and air quality. The adoption of internationally accepted standards on automobile emissions and gasoline have been effective in reducing air pollution from motor vehicles. Demand management measures have largely focused on controlling the source of tra5c congestion, i.e. private automobile ownership and its use especially within the Central Business District during the day. This paper reviews and analyzes the effectiveness of two measures which are instrumental in controlling congestion and automobile ownership, i.e. road pricing and the vehicle quota scheme (VQS). While these measures have been successful in achieving desired objectives, it has also led to the spreading of traffic externalities to other roads in the network, loss in consumer welfare and rent seeking by automobile traders.

This paper reviews the methods and technologies for congestion pricing of roads. Congestion tolls can be implemented at scales ranging from individual lanes on single links to national road networks. Tolls can be differentiated by time of day, road type and vehicle characteristics, and even set in real time according to current traffic conditions. Conventional toll booths have largely given way to electronic toll collection technologies. The main technology categories are roadside-only systems employing digital photography, tag and beacon systems that use short-range microwave technology, and in vehicle-only systems based on either satellite or cellular network communications. The best technology choice depends on the application. The rate at which congestion pricing is implemented, and its ultimate scope, will depend on what technology is used and on what other functions and services it can perform. Since congestion pricing calls for the greatest overall degree of toll differentiation, congestion pricing is likely to drive the technology choice.

This Article argues, using the case of responses to traffic congestion, that public choice provides a greater explanation for the emergence of property rights than does economic efficiency. While the traditional solution to traffic congestion is to provide new roadway capacity, that is not an efficient response in that it does not lead to internalization of costs. Moreover, over time new capacity may serve to exacerbate congestion problems: New roadway capacity may induce additional travel that would not have taken place but for the new construction. By contrast, congestion charges - that is, imposing tolls designed to force drivers to internalize the costs that their driving imposes on other drivers offer an efficient way to address the problem of congestion. The continued popularity, despite this, of providing new roadway capacity turns upon public choice theory. New roadway construction tends to be very attractive for politicians as a way to satisfy both constituents generally, a...

For several decades growth of traffic volumes has outstripped investments in road infrastructure. The result has been a relentless increase in traffic congestion. This paper reviews the economic principles behind congestion pricing in static and dynamic settings, which derive from the benefits of charging travellers for the externalities they create. Special attention is paid to various complications that make simple textbook congestion pricing models of limited relevance, and dictate that congestion pricing schemes be studied from the perspective of the theory of the second best. These complications include pricing in networks, heterogeneity of users, stochastic congestion, interactions of the transport sector with the rest of the economy, and tolling on private roads. Also the implications of congestion pricing for optimal road capacity are considered, and finally some explanations for the longstanding social and political resistance to road pricing are offered.

Unequivocally, it has become increasingly clear that the approach of Classical Modernist planning (CMP) that prevailed after World War II emphasizes huge permissivity for low-density sprawling suburban development and the meteoric rise of motorization in cities. The implicit “predict and provide” approach of building and expansion of roads to ease congestion continued to skew investments on transportation towards permitting private automobile ownership and use at the expense of public transportation. As a result, the inherent menaces of automobile dependence are continuing in cities especially in the Global South including Abuja, Nigeria.
This study has illustrated that the prevailing CMP system in Abuja, has continually spurred and fuelled the growth of suburbia. Consequently, the emerging automobile dependent mobility pattern is indeed plagued with the challenges of CO2 emissions, traffic congestion, and related man-hour and fuel wastage. This study reveals that by institutionalizing spatial planning strategies as BRT, TOD and congestion pricing it is possible to transform sprawling automobile dependent cities to smart compact transit dependent cities. Hence, the implicit CO2 emissions and traffic congestion challenges of man-hour and fuel wastage on the AYA route in Abuja is retrofitted, and the ecological and carbon footprints is dwarfed.

User Equilibrium (UE) method is the most widely used trip assignment method for auto trips. In UE condition, no driver can unilaterally reduce his/her travel time by shifting to another route. That means travel time on each used path between any Origin-Destination (O-D) is the same under this condition. Therefore, UE condition exists naturally in every road network. However, the total system travel time under this condition may not be the minimum. The total system travel time can be found minimum under System Optimum (SO) condition. In this research, UE and SO methods for trip assignment are compared. First, the methodologies are compared; and then link flows and travel times under both conditions are compared. As SO is not a natural process, mechanism to achieve SO is also shown in this paper. 
Arterial highway network of Sioux Falls, South Dakota consisting of 24 nodes and 76 links with 13 origins and destinations is analyzed for both UE and SO conditions. The network is analyzed by GAMS optimization software. It is found that the system travel time is much less under SO condition than under UE condition.

to help develop a framework and advise on methods and approaches for integrating CO2 concerns into urban transportation in Latin America and the Caribbean (LAC 1 ). The UC Berkeley team conducted an analysis of the current portfolio of World Bank transport projects in the region and carried out interviews with Bank staff working in the region. The review of the World Bank's work was followed by a four-day workshop, held at UC Berkeley and attended by 17 members of the World Bank's staff. At the workshop, UC faculty presented information on greenhouse gas (GHG) science, issues, and impacts, other regions' responses to the GHG challenge, LAC urban transport problems and their GHG consequences, and opportunities for intervention to reduce GHG emissions in the LAC context. Presentations were interspersed with group discussions and commentary. Then, drawing upon the literature on GHG reduction strategies, LAC transport issues, the review of the World Bank portfolio and staff interviews, and the workshop discussions, the UC Berkeley team developed a framework for consideration of GHG emissions reduction strategies in the Latin America and Caribbean region. The UC Berkeley team also prepared guidance on methods and procedures that could be used to analyze GHG emissions, and developed recommendations on ways to enhance or strengthen the interventions proposed to the World Bank from the client countries.

Almost all road infrastructure is treated as a public good and seen as a governmental obligation. But roads differ from other public goods such as national defense in both non-rivalry and nonexclusiveness features. Moreover, Financing construction and maintenance of road infrastructure is challenging because in most countries, government revenues for road construction and maintenance are insufficient. Here, the idea of road privatization is introduced as a possible alternative. Although there are many political and societal hindrances in  implementing this idea, its potential to solve problems in transportation is indisputable. The road owner pays the government for the externalities produced from his property (pollutions or accidents) but can make money by charging users (passing the externalities burden to users, while easing congestion and free rider problems) and because the road is privately constructed and owned, the opportunity cost of the road construction and maintenance is better accounted for. By assigning the road’s property to private sectors, the supply side might become more efficient based on the transformation from a publicly subsidized market to an open market framework. The equity problem of the new pricing scheme can be partially solved with a rebate policy similar to credit-based congestion pricing (CBCP).

Strategies, models, and algorithms facilitating such models are explored to provide transportation network managers and planners with more flexibility under uncertainty. Network design problems with non-stationary stochastic OD demand are formulated as real option investment problems and dynamic programming solution methodologies are used to obtain the value of flexibility to defer and re-design a network. The design premium is shown to reflect the opportunity cost of committing to a “preferred alternative” in transportation planning. Both network option and link option design problems are proposed with solution algorithms and tested on the classical Sioux Falls, SD network. Results indicate that allowing individual links to be deferred can have significant option value. A resource relocation model using non-stationary stochastic variables as chance constraints is proposed. The model is applied to air tanker relocation for initial attack of wildfires in California, and results show that the flexibility to switch locations with non-stationary stochastic variables providing 3-day or 7-day forecasts is more cost-effective than relocations without forecasting. Due to the computational costs of these more complex network models, a faster converging heuristic based on radial basis functions is evaluated for continuous network design problems for the Anaheim, CA network with a 31-dimensional decision variable. The algorithm is further modified and then proven to converge for multi-objective problems. Compared to other popular multi-objective solution algorithms in the literature such as the genetic algorithm, the proposed multi-objective radial basis function algorithm is shown to be most effective. The algorithm is applied to a flexible robust toll pricing problem, where toll pricing is proposed as a strategy to manage network robustness over multiple regimes of link capacity uncertainty. A link degradation simulation model is proposed that uses multivariate Bernoulli random variables to simulate correlated link failures. The solution to a multi-objective mean-variance toll pricing problem is obtained for the Sioux Falls network under low and high probability seasons, showing that the flexibility to adapt the Pareto set of toll solutions to changes in regime – e.g. hurricane seasons, security threat levels, etc – can increase value in terms of an epsilon indicator.

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / t r a toll ratio found in the numerical experiments. This suggests that the tolls for large trucks are set on the basis of revenue generation principles while the passenger car tolls are being set based on a mild form of welfare maximization. This leads to a suboptimal cross-subsidization of passenger car traffic in detriment of an important sector of the economy.

Little is known about how accurately individuals perceive externalities and how their perception affects bargaining behavior. This paper uses the setting of an unregulated taxi system in Lima, Peru to analyze taxi drivers’ ability to transfer congestion costs into higher fares. In unregulated taxi systems, taxi drivers and customers bargain over trip fares. When congestion increases, travel times also increase. In this context, parties bargain over who pays the larger share of the uncertain congestion costs. The experiment involved professional commuters hailing taxis and negotiating fares at different times of day between specific locations with randomly assigned alternative route treatments. A total of 1100 trips were conducted following the same bargaining protocol, from which taxi fares, travel times, and routing decisions were collected. Results show that taxi drivers increase fares according to route expected travel times, but they do not increase fares enough to prevent earnings per minute from decreasing. Fares for congested trips are one-third lower than metered fare constructed estimates. Experienced drivers learn to avoid congested routes by detouring to longer but speedier ones made out of smaller streets. These results highlight that unregulated taxi systems are successful at generating incentives for taxi drivers to make optimal routing decisions, but do not at improve drivers’ ability to transfer congestion costs into higher fares.

This article adopts a family of surrogatebased optimization approaches to approximate the response surface for the transportation simulation inputoutput mapping and search for the optimal toll charges in a transportation network. The computational effort can thus be significantly reduced for the expensive-toevaluate optimization problem. Meanwhile, the random noise that always occurs through simulations can be addressed by this family of approaches. Both one-stage and two-stage surrogate models are tested and compared. A suboptimal exploration strategy and a global exploration strategy are incorporated and validated. A simulationbased dynamic traffic assignment model DynusT (Dynamic Urban Systems in Transportation) is utilized to evaluate the system performance in response to different link-additive toll schemes implemented on a highway in a real road transportation network. With the objective of minimizing the network-wide average travel time, the simulation results show that implementing the optimal toll predicted by the surrogate model can benefit society in multiple ways. The travelers gain from the 2.5% reduction (0.45 minutes) of the average travel time.

A unified model of accident and travel-delay costs describes the role that defensive driving effort plays in balancing these costs, and the costs of effort itself. This motivates a simple method for jointly estimating risk, effort, and travel-delay externalities, which exploits ordinary travel-demand modeling to directly value the congestion that generates these costs. A unique empirical setting also allows for decomposing the joint externality into its travel-delay and accident-related components, with results suggesting that together risk and effort externalities are nearly on par with travel-delay externalities. It is also demonstrated that traditional value-of-time estimates substantially reflect risk and effort costs.

In order to abate the negative consequences of traffic congestion, implementation of congestion pricing is a matter of time demand nowadays. Congestion pricing will help to encourage the use of public transportation facilities. This paper conducted a comprehensive overview of congestion charging systems in different countries and reviewed its benefits. The study considered congestion charging experiences in Central London, Singapore, Stockholm and Hong Kong. According to our review across the developed countries it is found that congestion price can reduce congestion by 15 to 25% and increase public transportation ridership by 20 to 40%. Travel speed is almost same as the percentage of reduced traffic volume. It is also seen that car trips in city centres are dropped by 20 to 70%. Implementation of congestion pricing reduces the emission of greenhouse gases more than 15%. In developed cities implementation of congestion pricing is easy because of proper funding and well organized political environment. But for developing countries like Bangladesh it is a challenging issue due to insufficient funding, political restriction and lower socio economic condition. Although there are many difficulties in Bangladesh, congestion pricing is one of the potential solutions to alleviate traffic congestion problems. After evaluating worldwide congestion pricing success congestion charge is a reality based project to overcome congestion problem and promote public transportation facilities.

Keywords: Congestion pricing, Traffic congestion, Public transportation.

The ability to realistically capture trip-makers' responses to time-varying road charges is essential for network equilibrium assignment models typically applied to predict network flows in the presence of dynamic road (congestion) pricing. User responses to pricing are governed by individual trip-makers' preferences, such as their value of time (VOT), and the cost they attach to late vs. early arrival relative to the destination. These behavioral characteristics vary across users. This paper presents a joint route and departure time network equilibrium assignment model explicitly considering heterogeneous users with different preferred arrival times at destinations, VOT, and values of early and late schedule delays (VOESD and VOLSD). The model is formulated as an infinite-dimensional variational inequality and solved by a column generation-based algorithmic framework that embeds: (i) an extreme non-dominated alternative-generating algorithm to obtain combinations of VOT, VOESD, and VOLSD subintervals (or breakpoints) that define multiple user classes, and the corresponding least trip cost alternative (joint departure time and path) for each user class, (ii) a traffic simulator to capture traffic flow dynamics and determine experienced travel costs; and (iii) a multi-class alternative flow updating scheme to solve the reduced multi-class simultaneous route and departure time user equilibrium problem defined by a subset of feasible alternatives. Application to an actual network illustrates the properties of the algorithm, and underscores the importance of capturing user heterogeneity and temporal shifts in the appraisal of dynamic pricing schemes.

In this article, we modeled the economic impacts of congestion pricing policies on micro and macro levels of the economy. On the consumer side of the market, we ran a discrete choice model and examined how travelers behave differently in response to higher driving costs caused by road congestion. While on the macro level, we defined the congestion pricing policy as an exogenous shock on economy and simulated the impacts of this stimulator on several sectors of economy.
Results for the case study of the Greater New York Metropolitan area shows that a congestion pricing policy on three designated freeways, with a daily flow over 3.5 million vehicles will induce around $0.55 bln increase in GDP. This growth is caused not only by the expansion of value added items, but also by the direct impact on GDP due to less fuel consumption and consequently less oil imports.

The analysis reported here was prompted by a realization that there was little reliable and consistent information on what proportion of household income is spent on urban public transport. The information available uses inconsistent definitions of what costs are included and how income is measured, making comparisons between cities difficult. The authors report here on about a dozen studies that have addressed the issue of affordability. Though different measures are used in different countries, making it difficult to compare the results between cities, from the studies in South America, South Asia, Eastern and Western Europe, Africa, East Asia and Australasia summarized here, the authors make clear that the affordability of urban transport is considered an issue of importance throughout the developing world. There is also evidence that the high cost of urban transport is having a negative impact on the lives of the urban poor - either through restricting their access to jobs that ...

The problems faced by today's public managers are often too large to be solved by a single entity and require collaboration across government, nonprofit, and business sectors. As new technologies and systematic approaches transform the transportation field, cross-sector collaboration has become an increasingly important policy development and implementation approach. Particularly within the transportation field, an assemblage of technologies is often critical to implementing system-wide strategies aimed at, for example, mitigating traffic congestion. In many cases, designers and implementers of effective transportation policies must combine a variety of technologies with deft relationship building and management. Through the development of comparative case studies of three of the Urban Partnership Agreement initiatives, this research study will examine how technology and collaborative processes may be combined to achieve important transportation goals and create public value more generally.

Prices signal the scarcity of resources on the market and produce their efficient allocation. Given the level of high fixed costs characterising most public utilities (electricity and transport are no exemption to this) there is a strong case for a discriminating use of prices. The demand for public utility service varies periodically and its management constitute the core of the peak load pricing problem. A fundamental aspect of peak load theory is the specific object of pricing. We assume that peak load implies pricing for the use of scarce resource capacity in production, whereas peak load for the use of a network, that is congestion charging, is aimed at the internalisation of external costs. In the case of transport we might adopt, for example, peak load pricing for the management of excessive bus demand and use congestion charging to internalise the external costs imposed by private transportation. In the electricity sector peak load pricing might be used to manage the excessive power demand while congestion pricing is just a part of the transmission pricing mechanism that has to be complemented by electricity losses charging. In the case of transport the two problems overlap since production and transmission coincide.

This paper uses analytical and numerical models to illustrate how the presence of other distortions within the transport system changes the overall welfare effect of a congestion tax. These other distortions include a transit fare subsidy, congestion on competing (unpriced) routes, accident externalities, gasoline taxes, and pollution externalities.

Scientists and policymakers intend worldwide emissions reduction of up to 80 percent of carbon dioxide (CO2) and other greenhouse gases (GHGs) in the next four decades to stabilize atmospheric concentrations. Henceforth, an immediate response from the transportation sector, one of the largest producers of GHGs (up to 30 percent in the U.S.), is critical for GHGs reduction. Recent advancement in Intelligent Transportation Systems (ITS) offers a technical solution to implement emission pricing effectively in a reasonable period of time. Further, this strategy can foster demand for efficient vehicles and high transit ridership while reducing GHGs emission and generating revenue. Therefore, in this study, we propose models for understanding the reduction of GHGs emission and shifts of private vehicle trips to transit by implementing ITS based optimal emission pricing to reduce GHGs emission by a certain percentage in a composite transportation network (transit and highway network). The bi-level models presented in this study take into account the planner's policy decision and the road user's response to such policies in a simple and methodologically robust framework. The complex decision of choosing transit over private vehicle and road user behavior in the study has been studied by mode split functions and the classical user equilibrium principle. The performance of proposed models is compared to the base-case (do-nothing); reductions in total GHGs emission by optimal emission pricing shows efficacy of the models. The presented methodology in this paper is generalizable and can be applied to any transportation network.

This article simulates the effects of congestion pricing on emissions of carbon monoxide, nitrogen oxide, and hydrocarbons for an actual metropolitan highway network. Traffic is assigned to the network assuming elastic travel demand and endogenous route selection to minimize private or social travel costs. Simulations price all or part of the network. Delaware's household travel demand and highway traffic count data calibrate the simulations. EPA's Mobile 5a model predicts that vehicle emissions decrease as much as 10% in aggregate and 30% in highly congested areas. Benefits from reduced emissions are 15᎐30% of those from reduced congestion. ᮊ

The purpose of this study was to explore travellers' responsiveness to congestion pricing (cordon pricing) and parking attributes (especially parking pricing) in deciding whether to drive and park in the central business district (CBD). Employing the stated-preference method, data were collected by personal interviews in Mashhad City CBD. The respondents were requested to report their current trip to the CBD by answering a set of questions and scenarios to consider five alternatives, including two parking locations in the CBD: park inside the cordon-pricing zone or outside and access the cordon area by walking or public transport, shift to public transport (taxi and bus), or cancelling of their trip to the CBD. The two parking locations were categorised by cordon and parking tariff schedule, search and queue time for a parking space, and access time from the parking space to the final destination. The preferences regarding mode of transportation and parking choices were determined using a multinomial logit model, which was used to estimate elasticity values and the willingness-to-pay among attributes. The results indicate that drivers are highly sensitive to cordon charge ( À 1.145), significantly more than to parking cost, search and egress times in switching mode and parking choice. Furthermore, respondents' reactions suggest that drivers' willingness to pay for parking fees is higher than their tendency to pay for cordon tolls.

This paper studies the optimal pricing of a two-sided monopoly platform when one side is affected by congestion. We show that the divide-and-conquer pricing strategy (or skewed pricing) depends not only on the relative magnitude of the sides’ price elasticities of demand but it also depends on the marginal congestion cost that an agent imposes on the others. Compared with the no-congestion case, this pricing strategy gives rise to some interesting features that violate the results of Rochet and Tirole (J Eur Econ Assoc 1:990–1029 in 2003, Rand J Econ 37:645–667 in 2006). In the case of equal price elasticities of demand, the no-congested side is charged the highest price. On the other hand, in the case of different price elasticities, the platform congestion pricing depends on a certain threshold of the marginal congestion cost. We show, under some conditions, that the divide-and-conquer pricing strategy is reversed. In the social context, the Rochet and Tirole’s (J Eur Econ Assoc 1:990–1029 in 2003) cost allocation condition is modified by the congestion cost. We show that the congestion does not only affect the buyers’ contribution to the sellers’ surplus, but it also affects the sellers’ contribution to the buyers’.

We study the problem of a city with access to two firms or subcentres (restaurants, airports) selling a differentiated product and/or offering a differentiated workplace. The first subcentre is easily congested (near city centre, access by road), the second less prone to congestion but further away. Both need to attract customers and employees and need to make profits to cover their fixed costs. This is an asymmetric duopoly game that can be solved for a Nash equilibrium in prices and wages. This solution involves excessive congestion for the nearby subcentre. Three stylised policies are studied to address this congestion. The first policy is to widen the congested road to the nearby subcentre. The second policy option is to add congestion pricing (or parking pricing etc.) for the congested subcentre. The third policy is to provide a direct subsidy to the remote subcentre so that it can reduce its price. We illustrate the theory using a numerical model applied to the two Brussels airports.

This article examines the debates and contradictions that surrounded the promotion of congestion pricing proposals in London, Stockholm, and New York City. On the one hand, congestion pricing is a neoliberal urban proposal that seeks to reduce motor traffic in a cordoned area by pricing out certain drivers. On the other hand, the political authorities believe that the success of congestion pricing proposals depends on the degree of redistributive elements regarding spatial mobility that are built into them. Redistribution in the form of improved mass transit provision was proposed in all three cities and was implemented in Stockholm and London. The problem with this political gesture is that neoliberals are lukewarm to redistributive politics and consider spatial mobility to be a matter of capacity and not a right. This means that neoliberal political parties because of their skepticism of redistributive politics, have more difficulties in imposing congestion pricing schemes than Left Parties. The congestion pricing proposal of the New York City failed because it was proposed by a neoliberal city administration without a credible redistributive spatial mobility plan.

This paper offers a general overview of the road pricing concept. It first examines the common objectives used in road pricing, namely (a) congestion reduction; (b) raising profits; (c) social welfare maximization; etc. Then, it explores various types of road pricing, including two major ones: (1) road tolls and (2) congestion pricing charges. Next, general modeling approaches used for estimating the impacts of road pricing are discussed. Finally, the paper concludes with a checklist explaining how to promote a successful road pricing scheme.

The derived nature of transportation demand implies that enhancement of mobility per se is not a reasonable goal for transportation policy; instead, improved mobility is desired to the extent that it furthers accessibility—a goal that can be achieved through a variety of measures. The paper uses the mobility-accessibility distinction to distinguish different implementations of congestion pricing. A mobility-based congestion pricing promises to alleviate congestion but threatens to deteriorate from overall regional accessibility as it accelerates metropolitan deconcentration. In contrast, accessibility-based congestion pricing avoids acceleration of sprawl by incorporating policies to ensure that drivers tolled off roads are replaced with residents and travelers arriving at previously congested areas by other means.

A discussion of an article with the aforementioned title, published in this issue of this journal, is presented. The aim of the author of this comment is to raise some issues as a contribution to the debate on the economic success of the London congestion charge. The author questions the worth of time savings as calculated by Prud'homme and Bocajero.

This paper reviews the methods and technologies for congestion pricing of roads. Congestion tolls can be implemented at scales ranging from individual lanes on single links to national road networks. Tolls can be differentiated by time of day, road type and vehicle characteristics, and even set in real time according to current traffic conditions. Conventional toll booths have largely given way to electronic toll collection technologies. The main technology categories are roadside-only systems employing digital photography, tag & beacon systems that use short-range microwave technology, and in-vehicle-only systems based on either satellite or cellular network communications. The best technology choice depends on the application. The rate at which congestion pricing is implemented, and its ultimate scope, will depend on what technology is used and on what other functions and services it can perform.