Distance-dependent congestion pricing for downtown zones

A growing literature exploits macroscopic theories of traffic to model congestion pricing policies in downtown zones. This study introduces trip length heterogeneity into this analysis and proposes a usage-based, time-varying congestion toll that alleviates congestion while prioritizing shorter trips. Unlike conventional trip-based tolls the scheme is intended to align the fees paid by drivers with the actual congestion damage they do, and to increase the toll’s benefits as a result.The scheme is intended to maximize the number of people that finish their trips close to their desired times. The usage-based toll is compared to a traditional, trip-based toll which neglects trip length. It is found that, like trip-based tolls, properly designed usage-based tolls alleviate congestion. But they reduce schedule delay more than trip-based tolls and do so with much smaller user fees. As a result usage-based tolls leave most of those who pay with a large welfare gain. This may increase the tolls’ political acceptability.     

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

In this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional–Integral type feedback controller, based on the level of vehicular traffic congestion and traveler’s behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.     

Optimal toll locations and toll levels in congestion pricing schemes: a case study of Stockholm

As congestion pricing has moved from theoretical ideas in the literature to real-world implementation, the need for decision support when designing pricing schemes has become evident. This paper deals with the problem of finding optimal toll levels and locations in a road traffic network and presents a case study of Stockholm. The optimisation problem of finding optimal toll levels, given a predetermined cordon, and the problem of finding both optimal toll locations and levels are presented, and previously developed heuristics are used for solving these problems. For the Stockholm case study, the possible welfare gains of optimising toll levels in the current cordon and optimising both toll locations and their corresponding toll levels are evaluated. It is shown that by tuning the toll levels in the current congestion pricing cordon used in Stockholm, the welfare gain can be increased significantly, and furthermore improved by allowing a toll on a major bypass highway. It is also shown that, by optimising both toll locations and levels, a congestion pricing scheme with welfare gain close to what can be achieved by marginal social cost pricing can be designed with tolls being located on only a quarter of the tollable links.     

Overcoming public aversion to congestion pricing

We have completed a survey of Southern California residents designed to examine whether the details of policy design can make congestion pricing more attractive to the motoring public. A congestion fee proposal is often regarded as simply a tax increase; also, especially in the US, motorists apparently regard the use of congestion fees as coercive, in that they often have few if any practical alternatives to paying the fee. Unlike most opinion surveys on congestion pricing, our survey was quite explicit about the fate of the collected revenues. For example, we presented respondents with policies that returned a substantial portion of the revenues to the public, either in the form of cash (through reductions in sales taxes and vehicle registration fees or through income tax credits) or in the form of coupons to be used for vehicle emissions equipment repair, transit, and the like. In addition, we examined whether the typically intense opposition to congestion pricing if applied only to a part of a roadway, leaving the motorist free to choose between free lanes and toll lanes. We find that a promise to offset the imposition of congestion fees by other taxes can result in a 7% point increase in support for congestion pricing policies, and the restriction of congestion pricing to a single lane on a freeway attracts from 9% to 17% points of additional support.     

Anticipating new-highway impacts: Opportunities for welfare analysis and credit-based congestion pricing

Pricing of roadways opens doors for infrastructure financing, and congestion pricing seeks to address inefficiencies in roadway operations. This paper emphasizes the revenue-generation opportunities and welfare impacts of flat-tolling schemes, standard congestion pricing, and credit-based congestion pricing policies. While most roadway investment decisions focus on travel time savings for existing trips, this work turns to logsum differences (which quantify changes in consumer surplus) for nested logit specifications across two traveler types, two destinations, three modes and three times of day, in order to arrive at welfare- and revenue-maximizing solutions. This behavioral specification is quite flexible, and facilitates benefit-cost calculations (as well as equity analysis), as demonstrated in this paper.The various cases examined suggest significant opportunities for financing new roadway investment while addressing congestion and equity issues, with net gains for both traveler types. Application results illustrate how, even after roadway construction and maintenance costs are covered, receipts may remain to distribute to eligible travelers so that typical travelers can be made better off than if a new, non-tolled road had been constructed. Moreover, tolling both routes (new and old) results in substantially shorter payback periods (5 versus 20 years) and higher welfare outcomes (in the case of welfare-maximizing tolls with credit distributions to all travelers). The tools and techniques highlighted here illustrate practical methods for identifying welfare-enhancing and cost-recovering investment opportunities, while recognizing multiple user classes and appropriate demand elasticity across times of day, destinations, modes and routes.     

Price-based regulation of oligopolistic markets under discrete choice models of demand

We propose a framework to find optimal price-based policies to regulate markets characterized by oligopolistic competition and in which consumers make a discrete choice among a finite set of alternatives. The framework accommodates general discrete choice models available in the literature in order to capture heterogeneous consumer behavior. In our work, consumers are utility maximizers and are modeled according to random utility theory. Suppliers are modeled as profit maximizers, according to the traditional microeconomic treatment. Market competition is modeled as a non-cooperative game, for which an approximate equilibrium solution is sought. Finally, the regulator can affect the behavior of all other agents by giving subsidies or imposing taxes to consumers. In transport markets, economic instruments might target specific alternatives, to reduce externalities such as congestion or emissions, or specific segments of the population, to achieve social welfare objectives. In public policy, different agents have different individual or social objectives, possibly conflicting, which must be taken into account within a social welfare function. We present a mixed integer optimization model to find optimal policies subject to supplier profit maximization and consumer utility maximization constraints. Then, we propose a model-based heuristic approach based on the fixed-point iteration algorithm that finds an approximate equilibrium solution for the market. Numerical experiments on an intercity travel case study show how the regulator can optimize its decisions under different scenarios.

     

The Downs–Thomson paradox with imperfect mode substitutes and alternative transit administration regimes

The Downs–Thomson paradox (D–T paradox) occurs when expansion of a congested and untolled highway undermines scale economies of a competing transit service, leaving users of both modes worse off. The standard analysis of the D–T paradox is based on several stringent assumptions: fixed total travel demand, perfect substitutability between automobile and transit trips, and no transit crowding. This paper re-examines the paradox when these assumptions are relaxed while retaining the usual assumption that there is no congestion interaction between the modes. It also broadens consideration to alternative transit administration regimes. In the standard treatment the transit operator is obliged to cover its costs. In this paper we also study two other regimes: transit profit maximization, and system-wide welfare maximization with no financing constraint. We examine how the transit system operator responds to highway capacity expansion in each regime, and how this affects welfare for drivers and transit users. We show that in all regimes the full price of transit declines only if the full price of driving falls as well. Thus, drivers are more likely to benefit from highway expansion than transit riders. The D–T paradox cannot occur in the profit maximization or unconstrained welfare maximization regimes. In the traditional self-financing regime transit service deteriorates, but the D–T paradox is not inevitable. Numerical analysis suggests that it can occur only when automobile and transit trips are nearly perfect substitutes.     

Optimal congestion taxes in a time allocation model

The purpose of this paper is to study optimal congestion taxes in a time-allocation framework. This makes it possible to distinguish taxes on inputs in the production of car trips and taxes on transport as an activity. Moreover, the model allows us to consider the implications of treating transport as a demand, derived from other activities. We extend several well known tax rules from the public finance literature and carefully interpret the implications for the optimal tax treatment of passenger transport services. The main findings of the paper are the following. First, if governments are limited to taxing market inputs into transport trip production, the time-allocation framework: (i) provides an argument for taxing congestion below marginal external cost, (ii) implies a favourable tax treatment for time-saving devices such as GPS, and (iii) provides a previously unnoticed argument for public transport subsidies. Second, if the government has access to perfect road pricing that directly taxes transport as an activity, all previous results disappear. Third, in the absence of perfect road pricing, the activity-specific congestion attracted by employment centres, by shopping centres or by large sports and cultural events should be corrected via higher taxes on market inputs in these activities (e.g., entry tickets, parking fees, etc.).     

Introducing congestion pricing on a new toll road

This paper proposes a demonstration project to test the effectiveness of congestion pricing in an urban area. It reviews the general theoretical case for such pricing and summarizes recent international interest in congestion pricing. Next, it sets forth the reasons why demonstration projects are needed, both to add to our knowledge about how effective congestion pricing may prove to be, and to address political and other public-acceptance barriers to implementation of the concept. The paper then defines a specific proposed test site for congestion pricing: a new toll road being planned for Orange County, California. It is proposed that instead of charging flat-rate tolls, the transportation agency could charge peak and off-peak tolls, increasing the level of the peak charge each year over a period of up to 10 years unless or until toll revenues decline below the levels forecast under the flat-rate toll alternative. Measurements of traffic flow and ride-sharing behavior would be made, as well as calculations of emission-reduction effects. The paper concludes with a brief discussion of marketing and political considerations involved in conducting such a demonstration.Abbreviations ARB Air Resources Board - AVI Automatic Vehicle Identification - CDMG Corridor Design Management Group - HOV High-occupancy vehicle - SJHTC San Joaquin Hills Transportation Corridor - TCA Transportation Corridor Agency - VMT Vehicle miles traveled     

Taxis in road pricing zone: should they pay the congestion charge?

This study aims at investigating the impact and feasibility of charging taxis with toll fee in the pricing zone when designing congestion pricing scheme. A bi‐level programming model is developed to compare the maximum social welfares before and after the congestion charge is imposed on taxis. The lower level is a combined network equilibrium model formulated as a variational inequality program, which considers the logit‐based mode split, route choice, elastic demand, and vacant taxi distributions. The upper level is to maximize the social welfare when toll rates vary. The bi‐level problem can be solved by the genetic algorithm, whereas the lower level is solved by the block Gauss–Seidel decomposition approach together with the method of successive averages and diagonalization algorithm. An application with numerical examples is conducted to demonstrate the effectiveness of the proposed model and algorithm and to reveal some interesting findings. Copyright © 2014 John Wiley & Sons, Ltd.     

Taxi services with search frictions and congestion externalities

Built upon the previous studies, this paper incorporates both bilateral taxi–customer search frictions and congestion externalities into the economic analyses of the equilibrium properties of taxi markets. We take account of congestion externalities by adopting a realistic distance‐based and delay‐based taxi fare structure. We first investigate comparative static effects of regulatory variables of taxi fare and fleet size on the market and then examine the properties of the Pareto‐efficient solutions for simultaneous maximization of social welfare and taxi profit in the congested market. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust optimization of distance-based tolls in a network considering stochastic day to day dynamics

This paper investigates the nonlinear distance-based congestion pricing in a network considering stochastic day-to-day dynamics. After an implementation/adjustment of a congestion pricing scheme, the network flows in a certain period of days are not on an equilibrium state, thus it is problematic to take the equilibrium-based indexes as the pricing objective. Therefore, the concept of robust optimization is taken for the congestion toll determination problem, which takes into account the network performance of each day. First, a minimax model which minimizes the maximum regret on each day is proposed. Taking as a constraint of the minimax model, a path-based day to day dynamics model under stochastic user equilibrium (SUE) constraints is discussed in this paper. It is difficult to solve this minimax model by exact algorithms because of the implicity of the flow map function. Hence, a two-phase artificial bee colony algorithm is developed to solve the proposed minimax regret model, of which the first phase solves the minimal expected total travel cost for each day and the second phase handles the minimax robust optimization problem. Finally, a numerical example is conducted to validate the proposed models and methods.     

Labour market effects in assessing the costs and benefits of road pricing

Traffic congestion and the policies used to combat it have been studied extensively. One area which has received less attention is the secondary impacts of such policies. This paper uses a micro-simulation framework to study the effect on labour markets of road pricing. The key benefit of our chosen methodology is that it allows a simultaneous consideration of both commuting and migration decisions. We show that while welfare gains can be achieved through optimal charging, this may come at the price of decreased integration. This may manifest through either greater centralisation tendencies in population, or through unemployment disparities between regions.     

Road Pricing models with maintenance cost

According to the Federal Highway Administration of the United States, maintenance expenditure takes up more than 25% of road revenue disbursement and this percentage has been increasing gradually. The reason for the increment in maintenance cost is that there lacks incentives for road users to take this cost component into their driving behavior. That is, different classes of vehicles should be levied different levels of congestion tax due to the different degrees of damage on the highway if a road pricing policy is implemented. This paper intends to incorporate this concept into road pricing literature by introducing two types of vehicles. After the analysis of the problem, we find that different types of vehicles should be charged different tolls. The toll includes not only the travel delay cost of one's own vehicle and the other types of vehicles, but also the marginal maintenance cost that is dependent on the traffic flow. A set of numerical examples is provided to demonstrate the theoretical analyses. The result shows that both the welfare and cost coverage rate will increase when the road pricing mechanism takes the maintenance cost factor into account.     

Congestion relief toll tunnels

Changing urban land-use patterns have reduced the importance of traditional downtowns as the origin and destination of numerous vehicular trips. Much traffic on downtown-area freeways seeks merely to get past downtown, thereby worsening the level of congestion for those seeking access to downtown.A number of European cities have begun to develop a new type of transportation facility: congestion-relief toll tunnels in downtown areas. These projects appear to be economically feasible largely or entirely from premium-price tolls paid by users. Hence, they are being developed by private consortia, operating under long-term franchises from government. Other keys to the feasibility of such projects are peak/off-peak pricing structures (congestion pricing), nonstop electronic toll collection, and restriction of use to auto-size vehicles only (to reduce tunnel dimensions and therefore capital investment).Preliminary analysis indicates that congestion-telief bypass runnels for downtown Los Angeles and San Francisco would be economically feasible as private business ventures, if developed along European lines. Similar approaches might be applied to other controversial freeway projects in both cities, and to restructuring Boston's huge and controversial Central Artery/Tunnel project.Congress has already authorized public-private partnerships of this type, permitting private capital and private owner/operation to be used, both for new projects and to rebuild existing highway, bridge, and tunnel facilities. Six states and Puerto Rico have enacted private-tollway legislation under which such projects could be developed and operated.This type of project should be politically feasible, since it offers a way to make significant transportation improvements in impacted downtowns with little or no public funding. While transit proponents may oppose the construction of toll tunnels, highway users are likely to support such projects, and some environmental groups may support this method of implementing congestion pricing in urban areas, because of its potential for reducing air emissions.     

Capturing value of reliability through road pricing in congested traffic under uncertainty

Empirical studies showed that travel time reliability, usually measured by travel time variance, is strongly correlated with travel time itself. Travel time is highly volatile when the demand approaches or exceeds the capacity. Travel time variability is associated with the level of congestion, and could represent additional costs for travelers who prefer punctual arrivals. Although many studies propose to use road pricing as a tool to capture the value of travel time (VOT) savings and to induce better road usage patterns, the role of the value of reliability (VOR) in designing road pricing schemes has rarely been studied. By using road pricing as a tool to spread out the peak demand, traffic management agencies could improve the utility of travelers who prefer punctual arrivals under traffic congestion and stochastic network conditions. Therefore, we could capture the value of travel time reliability using road pricing, which is rarely discussed in the literature. To quantify the value of travel time reliability (or reliability improvement), we need to integrate trip scheduling, endogenous traffic congestion, travel time uncertainty, and pricing strategies in one modeling framework. This paper developed such a model to capture the impact of pricing on various costs components that affect travel choices, and the role of travel time reliability in shaping departure patterns, queuing process, and the choice of optimal pricing. The model also shows the benefits of improving travel time reliability in various ways. Findings from this paper could help to expand the scope of road pricing, and to develop more comprehensive travel demand management schemes.     

An assessment of the political acceptability of congestion pricing

There is renewed interest in implementing congestion pricing in metropolitan areas throughout the US. This paper reviews changes in the transportation policy environment that have led to this renewed interest and identifies the major interest groups that support congestion pricing. A case study is used to demonstrate that significant barriers to congestion pricing implementation continue to exist. The paper concludes with some suggestions for developing politically acceptable pricing alternatives.     

Economic analysis of collecting parking fees by a private firm

The purpose of this paper is to show the possibility of a co-existence of public and private parking management systems even when all the parking spaces are owned by the government. This study focuses on the issue of collecting parking fees by a private firm that has been used by some local governments in Taiwan. We assume that the government behaves as a leader and a private firm as a follower in a Stackelberg three-stage game. At stage 1, the government selects its parking space. At stage 2, the government and the firm set their parking fees simultaneously. At the final stage, consumers (drivers) choose the parking lot between the space of the government and that of the firm by considering the full costs, consisting of the parking fee and the searching (with congestion) time cost. The objective of the government is to maximize welfare and that of the firm is to maximize profit. The model is constructed at first and a simulation analysis is then made. The result supports the strategy of adopting the franchise of collecting parking fees if the private firm is more efficient than the government. Moreover, the government may keep fewer parking spaces and release more parking spaces to the firm under the goal of maximizing welfare.     

Time-dependent congestion pricing system for large networks: Integrating departure time choice,dynamic traffic assignment and regional travel surveys in the Greater Toronto Area

Congestion pricing is one of the widely contemplated methods to manage traffic congestion. The purpose of congestion pricing is to manage traffic demand generation and supply allocation by charging fees (i.e., tolling) for the use of certain roads in order to distribute traffic demand more evenly over time and space. This study presents a framework for large-scale variable congestion pricing policy determination and evaluation. The proposed framework integrates departure time choice and route choice models within a regional dynamic traffic assignment (DTA) simulation environment. The framework addresses the impact of tolling on: (1) road traffic congestion (supply side), and (2) travelers’ choice dimensions including departure time and route choices (demand side). The framework is applied to a simulation-based case study of tolling a major freeway in Toronto while capturing the regional effects across the Greater Toronto Area (GTA). The models are developed and calibrated using regional household travel survey data that reflect the heterogeneity of travelers’ attributes. The DTA model is calibrated using actual traffic counts from the Ontario Ministry of Transportation and the City of Toronto. The case study examined two tolling scenarios: flat and variable tolling. The results indicate that: (1) more benefits are attained from variable pricing, that mirrors temporal congestion patterns, due to departure time rescheduling as opposed to predominantly re-routing only in the case of flat tolling, (2) widespread spatial and temporal re-distributions of traffic demand are observed across the regional network in response to tolling a significant, yet relatively short, expressway serving Downtown Toronto, and (3) flat tolling causes major and counterproductive rerouting patterns during peak hours, which was observed to block access to the tolled facility itself.     

Urban highway congestion

This article examines urban highway congestion pricing in the instance in which it is not possible to levy a congestion toll on a major portion of the urban road system. This case is pertinent because of technical and/or political constraints. The article uses economic theory and numerical examples to show that the optimum second-best toll can vary appreciably from the optimal tolls in a regime in which efficient tolls can be imposed on all routes.