Congestion Pricing

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.

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.

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.

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.

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.

Pre-charge and post-charge data (particularly on speed and road usage) in the London congestion charge zone is used to estimate demand and cost curves for road usage. Pre-charge congestion costs are estimated, and shown to be small (0.1% of the area GDP). They are largely (90%) eliminated by the charge, which produces an economic benefit. Charge proceeds are about three times larger than the value of the congestion. Unfortunately, the yearly amortisation and operation costs of the charge system appear to be significantly higher than the economic benefit produced by the system. The London congestion charge, which is a great technical and political success, seems to be an economic failure. It could be defined as mini Concorde. q

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).

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.

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

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.

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.

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.

A number of studies have examined the feasibility of temporal variations in tolls. However, spatial variation in tolls has not received much attention, especially in practice. Spatial variation could effectively reduce congestion and increase profits. To fill this gap, we conduct an empirical application on 3 different road segments using the Fresno, California’s transportation planning model. Our modeling results in a number of interesting insights. First, the derived optimal flat toll values are very close to the average variable tolls, but the effects of applying spatially variable tolls on improving total revenues (from 4% to 24%) and total improved travel time (from 18% to 1083%) measures are significant. Second, spatially variable tolls are more effective, but more costly, particularly for arterials, which can be attributed to the higher number of access points for arterials. Third, spatial variations in tolls are more effective for peak hours than for off-peak hours and for social optimization than for profit maximization. Fourth, to improve throughputs for both profit maximization and social optimization, the prevalent tolling pattern along a corridor induces lower final volumes per capacity (V/Cs) (after pricing) at the mainline flow sections and relatively higher final V/Cs at the entrance and exit (boundary) points. Finally, optimal toll patterns are not dependent on vehicle miles traveled (VMTs) or volumes but, rather, are related to targeted V/Cs. Therefore, flow-dependent charges along a corridor should be based on V/Cs rather than on volumes or VMTs.

Public-private partnerships (P3s) are likely to impact entire transportation systems in fundamental ways. However, few studies have examined the potential impact of P3s on large-scale transportation networks. These studies have focused on modeling rather than on policy analysis. The literature thus does not offer guidance for designing and administering P3s to improve transportation system performance while maintaining profitability. Using Fresno, California’s transportation network as a laboratory, we consider the effects of alternative P3 tolling approaches on profit maximization and system performance optimization at full urban transportation network scale. Based on system modeling results, we offer the following recommendations for policy makers to design and promote successful P3s in urban settings: (i) to promote a profitable and a socially beneficial system, toll rates should be set examining both profit-maximizing and system-optimal rates; (ii) even though tolls (i.e., higher travel costs) on a few roads help reduce travel demand they may, counter-intuitively, lead to higher total travel cost for the overall transportation system because of users’ decision to travel longer distances to avoid tolls, especially when high toll rates are applied; (iii) lower limit(s) on tolls (in addition to upper limits) may be required to enforce system-optimal tolling and avoid undercutting by private owners; (iv) a variable tolling approach (i.e., temporally- and spatially-varying tolls) significantly reduces congestion and increases profits relative to flat tolls; and (v) public officials should provide a comprehensive plan regarding past, current, and future P3 projects along with a detailed system-wide impact analysis to promote a more sustainable transportation system.

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 provides a brief overview of the concept of value of time (VOT), in the context of toll road schemes. VOT analysis determines the tradeoffs travelers make between time and tolls. The analysis is very important when considering the choice between tolled and un-tolled alternatives. Using travel demand model of Fresno, CA, I provide a sensitivity analysis showing how the outcomes of tolling schemes can change with varying VOT levels.

Studies examining the social cost of driving usually ignore the opportunity cost of having roads in place: the associated land rents. Especially for geographic regions where land is valuable, including the rent costs may even lead governments to even close some roads. By using the London congestion charging zone case, a more general long-run social cost curve is calculated with the addition of the rents. Based on the optimal road usage concept, this study found that including the rents in the cost/benefit analysis significantly affects the results and can increase the social cost by up to 200% and decrease the optimal road usage by 40%.

Dhanmondi is one of the most affluent
residential areas in Dhaka city was planned and
developed by the Public Works Department (PWD)
according to the order Dhaka No. 11413 requ.-9th
December 1952. In 1984 about 28 percent of the houses
in this area were used for non-residential purpose
although the area was planned as a residential area.
Since 1984 to 2006 the residential purpose of land use
has decreased from 71.86% to 46.09% whereas
commercial use has increased from 28.35% to 52.91%.
Residents of this area own nearly 25,000 private cars.
That is 209 cars per thousand populations. Numerous
schools, hospitals, private universities, business
institutions lead an enormous volume of traffic into and
out of the area every day. Study showed that through
traffic in this area is dominated by autos and smaller
sized vehicles, which is one of the major causes of
congestion. To reduce this congestion in this paper the
prospects of introducing cordon pricing in Dhanmondi
residential area is elaborately discussed. Among the
various technology and scheme available a suitable
scheme with a feasible technology is advised. It will cost
government a total of 213.05 million taka capital and in
return it is expected to earn minimum revenue of about
288.32 million taka with a profit of 75.27 million taka in
the base year. It is estimated that the average traffic
speed inside the Dhanmondi residential area will
increase by 30%. This will increase the peak hour speed
of 14.4km/hr to 18.72km/hr. It is expected to save travel
time cost of 101.89 million taka, fuel cost of 23.56 million
taka every year. Also it will reduce emission the monetary
value of which is estimated to be 1.31 million taka.

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.

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 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.

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.

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.

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 chapter discusses congestion pricing as a neoliberal spatial mobility proposal in London, Stockholm, and New York City, and examines its relationship to complete streets. Supporters of congestion pricing are also supporters of complete streets, because the two schemes are viewed as ways to reverse a planning commitment that favors the automobile, so that cities can become more livable and sustainable. In the process, progressive proponents of these initiatives ally with holders of power whose priority is to financially benefit from the remaking of urban space. These alliances end up reproducing existing social injustices in the name of sustainability and environmentalism, which are transformed into market-based initiatives that favor the affluent and displace lower income people.

Imposition of airport congestion pricing redistributes welfare among commercial, regional, and general aviation. This article extends Daniel's [Econometrica63, 327–370 (1995)] stochastic-bottleneck model with dynamically adjusting traffic rates, queuing delays, and congestion fees to include elastic demand, heterogeneous operating time preferences, and heterogeneous layover and queuing time values. Using parameters from Minneapolis-St. Paul airport, simulations of congestion pricing determine its effects on equilibrium traffic patterns, queuing delays, schedule delays, airport revenues, and social welfare. Gains by commercial aviation, common travelers, and airport authorities exceed losses by general and regional aviation. The article evaluates several price-and-rebate programs and proposes several that are self-financing and Pareto improving.

Perhaps the greatest technological innovation of the next several decades will be universal access and utilization of the Internet. Already congestion is becoming a serious impediment to efficient utilization. We introduce a stochastic equilibrium concept for a general mathematical model of the Internet, and demonstrate that the efficient social welfare maximizing stochastic allocation of Internet traffic can be supported by optimal congestion prices. We further demonstrate that approximately optimal prices can be readily computed and implemented in a decentralized system by constructing a large computer simulation model. We also address the alternative of building excess capacity to avoid congestion.

Given that the cumulative prospect theory provides a well-supported descriptive paradigm for decision making under risk or uncertainty, previous studies applied the theory to model travelers' route choice behaviors in stochastic networks and developed prospect-based user equilibrium models. The models rely on exogenous inputs of reference points and thus the resulting reference-dependence could be regarded as an ad hoc assumption. This paper proposes a conjecture on travelers' determination of reference points and encapsulates it into the prospect-based user equilibrium conditions. The conditions are formulated as an equivalent variational inequality and a heuristic solution algorithm is proposed to solve it. Both the model and the solution algorithm are demonstrated in two numerical examples. As one application, this paper further develops an optimal pricing model in which the proposed user equilibrium model is adopted to capture travelers' response to pricing signals under risk. The pricing model is formulated as a mathematical program with complementarity constraints, solved by a derivative-free algorithm. Another numerical example is presented to illustrate the pricing model and the solution algorithm.

This paper describes an evolutionary game-theoretic learning model for dynamic congestion pricing in urban road networks, taking into account route choice stochasticity and reliability considerations, and the heterogeneity of users, in terms of their value of travel time and real-time information acquisition. The learning model represents the dynamic adjustments of users to travel cost changes which may take place in the day-to-day as well as the within-day timescales. The implementation into a simplified and a real urban road network signifies the important implications of modeling the dynamic and stochastic learning components of users’ behavior for accommodating the efficient deployment of congestion pricing schemes.

The presence of distortive taxation and agglomeration benefits in the labour market means that there are benefits and losses not captured by standard costbenefit analyses of transport policy measures. Recent theoretical analyses have raised concerns that the labour market effects of congestion charges may constitute considerable losses in the form of reduced aggregate labour income, over and above what is captured by the consumer surplus in the standard analysis of congestion charges -possibly to the extent that congestion charges may reduce aggregate social welfare, contrary to conventional wisdom in transport economics. The sign and size of these effects are an empirical question, however. We investigate this issue by estimating the labour income effects of the Stockholm congestion charges, using an estimated relationship between workplace accessibility and labour income. Results show positive effects on labour income, meaning that the "wider economic benefits" of this system are in fact benefits, not losses. It turns out to be crucial that the model accounts for value-of-time heterogeneity in the income/accessibility relationship and in the calculation of generalized travel costs.

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of energy efficient vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (±0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008, i.e., 519 privately owned, exempt EEVs.

In the paper, we summarize the results of a project that was motivated by the expiration of the "High Density Rule," which defined the slot controls employed at New York's LaGuardia Airport for more than 30 years. The scope of the project included the analysis of several administrative measures, congestion pricing options and slot auctions. The research output includes a congestion pricing procedure and also the specification of a slot auction mechanism. The research results are based in part on two strategic simulations. These were multi-day events that included the participation of airport operators, most notably the Port Authority of New York and New Jersey, FAA and DOT executives, airline representatives and other members of the air transportation community. The first simulation placed participants in a stressful, high congestion future scenario and then allowed participants to react and problem solve under various administrative measures and congestion pricing options. The second simulation was a mock slot auction in which participants bid on LGA arrival and departure slots for fictitious airlines.

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. (J.I. Daniel).

This paper reports the estimation of several discrete choice models describing reactions of individuals to congestion pricing scenarios. The models were estimated on data obtained in a stated adaptation experiment that was administered through the Internet and designed to examine how individuals adjust their activity-travel patterns. An activity-based approach is used meaning that all choice facets of activity patterns are taken into account as well as a complete set of activities. Estimates of price elasticities of travel demand are in line with other findings reported in the literature. Results of the stated adaptation experiment suggest that changing route or departure time is the most important way of adapting work trips, whereas public transport and working at home play a more limited role. For non-work activities changing route and switching to bike are the dominant responses.

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.

The city of Milan, one of the most car-dependent and polluted in Europe, is also among the few to have introduced a road pricing measure. The story of how this happened is of great interest, for it shows how EU regulations, scientific evidence and political action at the local level have concurred to bring about change in the city’s transport policy. Unlike the well-known cases of London and Stockholm, it is concerns for the levels of pollution (rather than congestion) that have led to the introduction of the “Ecopass” scheme in 2008. Accordingly, in the following years the public debate has focused on the effectiveness of this pollution charge in reducing PM10 – a pollutant with adverse health impacts. Based on the analysis of media coverage and official reports, this paper argues that EU regulations had a crucial role in determining the newsworthiness of PM10 in Milan. Media and public concerns have then put increasing pressure on politicians to find a solution to the “emergency”. The dubious effectiveness of Ecopass in reducing PM10 levels then has had two kinds of consequences. First, the scheme was upgraded to a congestion charge in 2012, following the results of a bottom-up referendum in which a large majority of voters demanded both an upgrade and an extension of the Ecopass area: this stands in stark contrast with the experience of other cities, where voters have turned down charging schemes (e.g. Edinburgh, Manchester). Second, the new city administration has recently implemented a monitoring system for Black Carbon, a new PM metric that is more suitable to prove the effectiveness of traffic restrictions. Overall, the paper shows how all actors involved in the process (politicians, media and civil society groups) made strategic use of scientific evidence on pollution, in order to bring forward their own agendas.