Congestion Pricing Research Articles

Parking pricing vs. congestion pricing: a macroscopic analysis of their impact on traffic

This paper focuses on parking pricing and congestion pricing and their short-term effects not only on traffic congestion but also on the potential revenue for a city. We develop a multimodal macroscopic traffic and parking search model based on aggregated data at the network level. Our methodology allows us to analyze how introducing parking pricing inside a network, or a congestion toll combined with a park and ride (P+R) scheme can affect the drivers’ decision between entering the network by car or using P+R. This decision directly influences the number of drivers using P+R, and this impacts, in turn, the traffic performance. We illustrate our proposed framework in a case study of an area with a high parking demand for public parking spaces within the city of Zurich, Switzerland. Results show that parking pricing combined with P+R is indeed a viable option compared to congestion pricing for improving traffic performance.

On the Net Neutrality Efficiency under Congestion Price Discrimination

In this paper, we study the extent to which net neutrality, defined as price non-discrimination, is welfare improving in comparison to non-net-neutrality. We consider a two-sided congested internet service provider (ISP) that acts as a monopoly platform. The congestion is basically caused by the overuse of the fixed ISP’s bandwidth by content providers. Unlike end-users, we allow content providers to be heterogeneous in their sensitivity to congestion. The analysis reveals that the ISP monopolist, by departing from the net neutrality regime, price-favors the most congestion sensitive providers. We argue that these providers play a crucial role in creating traffic and generating profit for the ISP platform. In our paper, whether net neutrality improves or harms social welfare depends on a critical threshold of the platform equilibrium congestion level. This threshold is an indicator or a proxy that indicates for a planner whether or not net neutrality rules should be repealed. When the platform congestion level lies below the threshold, we show that non-net-neutrality makes the society better-off. Exceeding the threshold, two effects are identified: profit-increase effect and consumers’ surplus-reduction effect. If the latter outweighs the former, net neutrality increases social welfare when compared to non-net-neutrality.

Electricity trading based on distribution locational marginal price

This paper presents a novel day-ahead power market for distribution systems. Based on the linearized AC power flow model, the distribution locational marginal price for coupled active and reactive power can be calculated and decomposed into five components, i.e. (1) energy price; (2) loss price caused by nodal active power; (3) loss price caused by nodal reactive power; (4) congestion price and (5) voltage support price, which can provide price signals for distributed generator and aggregator in a distribution system to respond. The energy hub at different nodes can trade with each other and optimize their profit based on distribution locational marginal prices. Game theory is applied to solve the energy trading payment problem. The energy trading problem is decomposed into two subproblems, i.e. operation cost minimization problem and trading payment bargaining problem. The effectiveness and validity of the proposed method are illustrated with a modified IEEE 33-bus system.

Modeling and managing ridesharing in a multi-modal network with an aggregate traffic representation: A doubly dynamical approach

This study models a multi-modal network with ridesharing services. The developed model reproduces the scenario where travelers with their own cars may choose to be a solo-driver, a ridesharing driver, a ridesharing rider, or a public transit passenger while travelers without their own cars can only choose to be either a ridesharing rider or a public transit passenger. The developed model can capture the (clock) time-dependent choices of travelers and the evolution of traffic conditions, i.e., the within-day traffic dynamics. In particular, the within-day traffic dynamics in a city region is modeled through an aggregate traffic representation, i.e., the Macroscopic Fundamental Diagram (MFD). This paper further develops a doubly dynamical system that examines how the within-day time-dependent travelers’ choices and traffic conditions will evolve from day to day, i.e., the day-to-day dynamics. Based on the doubly dynamical framework, this paper proposes two different congestion pricing schemes that aim to reduce network congestion and improve traffic efficiency. One scheme is to price all vehicles including both solo-driving and ridesharing vehicles (for ridesharing trips, the price is shared by the driver and rider), while the other scheme prices the solo-driving vehicles only in order to encourage ridesharing. The pricing levels (under each scheme) can be determined either through an adaptive adjustment mechanism from period to period driven by observed traffic conditions, or through solving a bi-level optimization problem. Numerical studies are conducted to illustrate the models and effectiveness of the pricing schemes. The results indicate that the emerging ridesharing platform may not necessarily reduce traffic congestion, but the proposed congestion pricing schemes can effectively reduce congestion and improve system performance. While pricing solo-driving vehicles only may encourage ridesharing, it can be less effective in reducing the overall congestion when compared to pricing both solo-driving and ridesharing vehicles.

How Do Organizational Capabilities Sustain Continuous Innovation in a Public Setting?

Just as private organizations rely on dynamic capabilities to sustain their innovative capacity and competitive advantage, the public sector may resort to them to improve its ability to address citizens’ needs. But how do innovation and organizational capabilities interact in a public setting? This analysis of the Congestion Charge Zone implemented by the Municipality of Milan in Italy explores this issue, and highlights the role played by interorganizational and cross-sector collaborative innovation. Results show that multi-actor engagement within a multilevel collaborative environment enhances the system’s ability to understand the problems to be addressed, to create and implement appropriate solutions, and to foster ownership of the innovation. They confirm that sharing knowledge and engaging in interorganizational learning are central to the development of innovation; however, they also highlight that these dynamics strengthen collective capabilities at the organizational and system’s level, thereby producing a reinforcing effect on innovative capacities at both levels. Based on these findings, a framework for continuous public innovation through collaboration is proposed which, first, provides a tool for mapping the factors and dynamics that shape collaborative innovation in a public setting and, second, explains how the process of collaborative innovation fosters organizational dynamic capabilities that, in turn, sustain the organizations’ capacity to innovate in the longer run.

THE TRANSITION FROM PIGOU’S IDEAS ON ROAD PRICING TO THEIR APPLICATION

A century ago Arthur Pigou published The Economics of Welfare. Within this volume are a few lines relating to the pricing of traffic congestion. Over the years, these lines have attracted the attention and thoughts of some of the leading economists of their day. These have included Knight, Clapham, and Robertson in the 1920s; Kahn and Viner in the 1930s; Ellis and Fellner in the 1940s; and Buchanan, Vickrey, Solow, Friedman, Walters, Demsetz, Newbery, and Allais in the post-World War II period. Here, I look at the academic arguments from the 1920s concerning how roads should be priced and by whom. I then move to consider the continuation of the intellectual debates after World War II and their implications for policy design and implementation. Finally, I briefly look at the extent to which some of the existing road congestion pricing systems meet the requirements of the economic theory.

Urban Congestion Charging Acceptability: An International Comparative Study

The congestion charging scheme is regarded as a successful measure to reduce traffic-related problems. However, low general acceptability of the public for implementing such a scheme is a barrier against its success. In this research, an online pre-designed survey was conducted in five capitals (Budapest, Tunis, Amman, Ulaanbaatar, and Damascus) to define the factors that affect congestion charging acceptability the most. The results of relationships between the studied factors like travel behavior and acceptance of the congestion charging scheme show an irregular pattern in each city. It indicates that the identity of each city and its general policy implications determine which factors significantly affect the public acceptability of congestion charging scheme. In Amman and Budapest, most of the predictors have no statistical effect on the schemes’ public acceptability. Consistent with previous researches, on the other hand, the results demonstrate that the schemes’ effectiveness is crucial and affects the acceptability significantly in all cities. At the same time, it shows that the “prior scheme knowledge” factor has a significant direct effect on the acceptability level in three cities (Damascus, Tunis, and Ulaanbaatar).

A passenger-to-driver matching model for commuter carpooling: Case study and sensitivity analysis

For the transport sector, promoting carpooling to private car users could be an effective strategy over reducing vehicle kilometers traveled. Theoretical studies have verified that carpooling is not only beneficial to drivers and passengers but also to the environment. Nevertheless, despite carpooling having a huge potential market in car commuters, it is not widely used in practice worldwide. In this paper, we develop a passenger-to-driver matching model based on the characteristics of a private-car based carpooling service, and propose an estimation method for time-based costs as well as the psychological costs of carpooling trips, taking into account the potential motivations and preferences of potential carpoolers. We test the model using commuting data for the Greater London from the UK Census 2011 and travel-time data from Uber. We investigate the service sensitivity to varying carpooling participant rates and fee-sharing ratios with the aim of improving matching performance at least cost. Finally, to illustrate how our matching model might be used, we test some practical carpooling promotion instruments. We found that higher participant role flexibility in the system can improve matching performance significantly. Encouraging commuters to walk helps form more carpooling trips and further reduces carbon emissions. Different fee-sharing ratios can influence matching performance, hence determination of optimal pricing should be based on the specific matching model and its cost parameters. Disincentives like parking charges and congestion charges seem to have a greater effect on carpooling choice than incentives like preferential parking and subsidies. The proposed model and associated findings provide valuable insights for designing an effective matching system and incentive scheme for carpooling services in practice.

Flight-Based Congestion Pricing Considering Equilibrium Flights in Airport Airside

Most of the previous works ignore the fact that equilibrium flights in self-profit maximization scenario are totally different from that in joint profit (social welfare) maximization scenario and take price difference (flight fare difference) between the two scenarios as congestion price, which is a passenger-based method. Most of all, the function of congestion pricing is to alleviate congestion by making airlines reduce flights at peak time. Therefore, the equilibrium flights under self-profit maximization should be the same as the ones under joint profit maximization after congestion prices are tolled. Flight-based congestion pricing method is provided in our paper. The analysis suggests no role for congestion pricing when total real flight production of all airlines is less than the equilibrium flights under joint profit maximization scenario. Otherwise, congestion tolls should be levied to all airlines. Furthermore, congestion price can be determined by solving the corresponding equations system.

Drivers’ intentions toward green transport in China: Understanding associations between demographic and policy factors

This study aimed on how demographic and scenario analysis can be used to assess the drivers’ intentions toward green transport in China. The special scale was constructed and the survey data was collected from 1090 car drivers in three cities in China. Binary logistic analysis was applied to evaluate the respondents’ demographic and intentional differences when different policies and price scenarios were constructed and provided. Three policy options of parking charge, fuel tax, and congestion charge were considered in this study. The results showed that demographic variables including gender, age, education, residence type, children status, family numbers, and household income could predict in varying degrees the drivers’ intentional changes toward green transport in different policy scenarios. And the three policy options had different impacts on different types of population. Finally, we outlined the high and low policy objectives for the urban transport planning. This study will provide empirical evidence and suggestions for the policy-makers to manage different social and demographic groups when considering the effects of transport policies in the implementation of sustainable urban transportation.

Understanding Public Acceptability of Congestion Charging in Beijing

AbstractBeijing, the capital city of China, currently experiences serious traffic congestion and extreme air pollution. To mitigate these issues, Beijing Municipality is currently considering imple...

Segmenting travellers based on day-to-day variability in work-related travel behaviour

Travel needs for commute and business trips are complex and choices are not made based on the characteristics of individual trips, but instead based on the needs over weeks and months. For example, the cost per trip of commuting by bus varies depending upon the frequency of travel, and the cost of a monthly subway pass depends upon the number of zones visited during that period. Intrapersonal variability, namely the variation in an individual's travel behaviour from day to day, therefore shapes our transport choices and should influence service provision. Changes in working patterns such as increases in part time working, self-employment and tele-commuting challenge the traditionally held assumptions that work activities are fixed in time and space, thus making intrapersonal variability increasingly relevant. This research uses a data-driven approach to segment workers based on their work-related travel behaviour, including frequency of travel and both spatial and time of day intrapersonal variability. The analysis uses survey and seven day travel diary data for over 110,000 people collected over a 19 year period in England. Four groups of workers were identified: infrequent, spatially variable, temporally variable and regular travellers. These groups do not align closely with self-reported working arrangements such as self-employment or part time working. The group of regular travellers has decreased in size between 1998 and 2016 but remains the largest group, containing just under 60% of workers in 2016. Both the infrequent and spatially variable groups have grown over the same period. For a small but growing group of workers, a seven day diary is insufficient to understand their work-related transport needs as little or no work travel is recorded. These findings have implications for the design of public transport ticketing, the design of mobility as a service packages and the appraisal of congestion charging schemes.

The two-mode problem with bottleneck queuing and transit crowding: How should congestion be priced using tolls and fares?

This paper proposes a bi-modal bottleneck model with time-varying scheduling preferences for investigating the two-mode problem with bottleneck queuing and transit crowding. In the proposed model, the activity scheduling utilities of commuters at home and at work vary by the time of day, and two kinds of congestion externalities (i.e., traffic congestion among vehicles at the bottleneck and in-bus passenger crowding discomfort) are considered. Commuters choose their travel modes and departure times from home to work during the morning commute to minimize their own generalized travel cost. The properties of the proposed bi-modal bottleneck model are analytically explored. Particularly, the relationship between the departure intervals of auto and bus commuters is revealed. The time-varying charging schemes and step charging schemes for reducing the congestion externalities are also investigated. A critical condition for passenger shift from one mode to the other mode with congestion charging schemes is identified, and the effects of congestion charging schemes with and without internalizing the bus-related congestion externalities (including the bottleneck congestion externality induced by auto and bus interaction and the in-bus passenger crowding externality) on the bottleneck system are compared.

Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network

To study the guidance method of driverless travel mode choice from the perspective of traffic supply-demand, we assume that all vehicles are driverless and establish a multimodal travel market model to depict the supply-demand relationship of multimodal driverless transportation network. To regulate the disequilibrium multimodal travel market, an optimal price regulation law is proposed, which aims to minimize the supply-demand deviation and the amplitude of price regulation. Then, the existence, uniqueness, and stability of the optimal price regulation law are confirmed. In the calculation process of a numerical example, the travel prices of driverless car and driverless subway are realized by congestion fee and subway fare, respectively. The results indicate that the optimal price regulation law can reduce the supply-demand deviation of the multimodal travel market and guide travelers to choose a reasonable travel mode to travel in the driverless transportation network.

Traffic congestion pricing via network congestion game approach

<p style='text-indent:20px;'>This paper investigates the optimization of traffic congestion systems via network congestion game approach. Firstly, using the semi-tensor product(STP) of matrices, the matrix expression of network congestion game is obtained. Secondly, a necessary and sufficient condition is proposed to guarantee that the traffic systems can be transformed into network congestion game with given performance criterion as its weighted potential function. Then an algorithm is provided to design the traffic congestion price in the case that conversion can be established. Thirdly, by designing proper learning rule, the optimization of traffic systems can be achieved when individuals optimize their own utility function. Moreover, two special cases which make our results more accord with reality and rich. Finally, an example is exploited to demonstrate the effectiveness of our obtained results.

Area-based equitable pricing strategies for multimodal urban networks with heterogeneous users

Abstract Equity issues among travellers are critical in congestion pricing. Failure to treat equity can lead to low acceptability towards pricing. In this paper, we develop congestion pricing schemes to improve both equity and traffic performance, for multimodal networks. We consider the equity issue by the existence of heterogeneous population, with respect to income level and value-of-time (VOT). An optimization framework is formulated for obtaining optimal toll schemes. We apply an aggregated network-level traffic flow model to reproduce congestion dynamics and mode choice behavior. The gain and loss for VOT-based user groups are investigated and discussed. We carry out simulation analysis over two pricing schemes: a unified toll and a VOT-based toll. In particular, we allow during the optimization process the VOT-based toll to obtain negative values for some users if it meets some system objectives. Our results confirm that significant differences in behavior and cost savings exist among groups, which justifies the need for a VOT-based pricing. It also demonstrates that properly-designed VOT-based tolls can improve the inequity in savings, e.g. users whose VOT values are lower may receive larger travel cost savings. Furthermore, a policy-oriented discussion on the design and implementation of the proposed equitable pricing schemes is provided.

The cost of congestion and the benefits of congestion pricing: A general equilibrium analysis

The benefits of congestion pricing are examined with a spatially detailed computable general equilibrium model of the Greater LA region. The model treats choices of roads on a network, of driving or public transit, of residence and job location, of non-work trip patterns, of housing type and size; vacancies and new construction, production, interindustry trade and exports. The aggregate benefit of pricing LA County road congestion increases 2.7 fold when the toll revenue is recycled to cut the income tax of the poorer LA County workers while maintaining region-wide tax revenue neutrality. Consumers get 66% of the aggregate benefit and landlords 41%, while importers suffer losses equal to 7% of the aggregate benefit. Gross regional product increases by 1.34%. The aggregate benefit changes negligibly when the toll revenue is recycled to cut sales taxes instead of the income tax, but gross product still rises by 0.6%. Under the sales tax cut, consumers, importers and landlords benefit more evenly than under the income tax cut, but with the property tax cut nearly all of the cut is capitalized into property values.

Evaluating the Traffic and Emissions Impacts of Congestion Pricing in New York City

Traffic congestion is a major challenge in metropolitan areas due to economic and negative health impacts. Several strategies have been tested all around the globe to relieve traffic congestion and minimize transportation externalities. Congestion pricing is among the most cited strategies with the potential to manage the travel demand. This study aims to investigate potential travel behavior changes in response to cordon pricing in Manhattan, New York. Several pricing schemes with variable cordon charging fees are designed and examined using an activity-based microsimulation travel demand model. The findings demonstrate a decreasing trend in the total number of trips interacting with the central business district (CBD) as the price goes up, except for intrazonal trips. We also analyze a set of other performance measures, such as Vehicle-Hours of Delay, Vehicle-Miles Traveled, and vehicle emissions. While the results show considerable growth in transit ridership (6%), single-occupant vehicles and taxis trips destined to the CBD reduced by 30% and 40%, respectively, under the $20 pricing scheme. The aggregated value of delay for all vehicles was also reduced by 32%. Our findings suggest that cordon pricing can positively ameliorate transportation network performance and consequently, improve air quality by reducing particular matter inventory by up to 17.5%. The results might facilitate public acceptance of cordon pricing strategies for the case study of NYC. More broadly, this study provides a robust framework for decision-makers across the US for further analysis on the subject.

Easing Off the Gas: Efficient and Equitable Policy for Passenger Vehicle Emissions Reduction

With GHG emissions and atmospheric concentrations of harmful chemical particles continuing to increase, it is imperative today that destructive social and economic tendencies of allowing these levels of pollution to occur must be halted and reversed. A significant contributor to this air pollution globally, and particularly in the United States, are passenger vehicles. Reducing the emissions levels of passenger vehicles in the United States and the resulting pollution costs immediately must be addressed. Various possible policy alternatives to be implemented federally exist, with raising passenger vehicle emissions standards, increasing subsidies for alternative fuel vehicles, and implementing congestion charging zones representing three prominent alternatives. It is suggested in the paper after consideration of effectiveness, efficiency, social equity, financial cost, and organizational and political feasibility that a combination of increased passenger vehicle emissions standards and subsidies for alternative fuel vehicles be implemented. Putting these policy programs in place is shown not only to be feasible, but to be effective and efficient at addressing the goal of reducing passenger vehicle emissions in the United States in a socially equitable manner. By achieving this, we can provide a safer, cleaner country for all residents across the United States of America regardless of geographic location and economic class.

Explaining public acceptance of congestion charging: The role of geographical variation in the Bergen case

Controversial policies introduced to improve public goods - such as the environment, mobility and public health - have shown patterns of initial opposition followed by broad acceptance once the public experiences positive effects of the policies. In transport policy, congestion charging is one area where such a pattern has been observed, particularly in some high-profile cases like Stockholm and London. However, existing research tends to focus on success cases and aggregate outcomes, and geographical variation in support and opposition is often overlooked. This is problematic because the public opinion on congestion charging appears highly differentiated between different areas of cities, possibly corresponding to perceived misdistribution of costs and benefits. We present a before-after study conducted in connection with the introduction of time-differentiated congestion charging rates in Bergen, Norway, in 2016. We find a substantial reduction of congestion and travel times after the policy’s implementation, but our survey data show no overall increase in policy support after implementation. There is, however, a tendency toward higher support for congestion charging in boroughs with greater delay reductions. We conclude that in securing and maintaining public support for transport measures, the intra-city distribution of costs and benefits is of critical importance.