Congestion Tolls Research Articles

Joint Routing and Pricing Control in Bimodal Mixed Autonomy Networks with Elastic Demand and Three-Dimensional Passenger Macroscopic Fundamental Diagram

The interaction between mixed autonomy traffic and public transport vehicles competing for limited road space is a less explored area of research. To evaluate the traffic dynamics in bimodal networks, a three-dimensional (passenger) network fundamental diagram, known as 3D-NFD (3D-pNFD), can be estimated that relates the accumulation of cars (autonomous and human-driven) and buses to the network vehicular (passenger) travel production. In this study, we propose a 3D-pNFD-based congestion pricing scheme considering three vehicle classes of buses, system-optimal (SO) seeking connected and automated vehicles (CAVs), and user-equilibrium (UE) seeking human-driven vehicles (HVs). We develop an iterative tri-level modeling framework for mode choice, pricing, and route choice in a mixed autonomy network. The lower level generates mixed equilibrium traffic flow through an integrated mixed equilibrium simulation-based dynamic traffic assignment model and a transit assignment model. The mid-level finds the optimal toll rates through a 3D-pNFD feedback-based controller. A nested logit-based mode choice model is also applied to capture travelers’ preferences toward three available modes and incorporates elastic demand. To encourage CAVs to follow the SO routing mode, they are provided with a discount on the congestion toll whereas UE-seeking HVs are subject to full price toll. Buses are also entirely exempt from the toll. We explore three scenarios with different discount rates on SO-seeking CAVs to investigate the effect of the incentive plans on the mode choice behaviors of road users in the pricing zone. The performance of the proposed model is evaluated in a large-scale network in Melbourne, Australia.

Enhancing Resilience With Electric Vehicles Charging Redispatching and Vehicle-to-Grid in Traffic-Electric Networks

Electric vehicles (EVs) can be viewed as both electric loads and a type of mobile storage resource. Effective management and utilization of EVs can yield significant benefits for networks. This paper proposes a novel resilience enhancement method for coupled traffic-electric networks with a high penetration of EVs, incorporating two specific strategies in response to contingencies. The first strategy involves rerouting and reselecting charging stations for power-deficient EVs, while the second entails redispatching power-sufficient EVs to the most suitable nearby charging stations to provide grid support through vehicle-to-grid technology. A carefully designed pricing mechanism, which includes imposing additional road congestion tolls and charging station charging fees, is incorporated to facilitate rerouting and charging station reselection for EVs under the user equilibrium principle. Furthermore, a formulation incorporating the two proposed resilience enhancement strategies for coupled traffic-electric networks is presented. This formulation enables coordination between the two networks to capitalize on flexibility derived from sector coupling. A series of linearization techniques are then introduced to transform the original problem into a mixed-integer quadratically constrained programming model. Numerical results based on a coupled network with 20 traffic roads and 21 electric buses are presented to demonstrate the effectiveness of the proposed resilience enhancement method.

Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways

Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways

Green Vehicles’ Responses to an Expiring Congestion Toll Exemption: Findings from a Natural Experiment in Stockholm, Sweden

Stockholm established time-varying congestion pricing in 2007, and adopted a toll exemption as a temporary incentive for green vehicles (GVs) that ended in 2012. We examine the behavioral effects of phasing out the exemption by studying the change in cordon crossing events for GV morning commuters between May 2012 and May 2013, with a random sample of conventional vehicles (CVs) as control. The results suggest i) a significant drop in the total number of crossings; ii) a slight shift towards later journeys in the morning; and iii) a reduction in the ratio of peak-toll period crossings to other ones.

Productivity benefits of urban transportation megaprojects: A general equilibrium analysis of «Grand Paris Express»

The «Grand Paris Express» (GPE) reduces road congestion, a negative externality (Walters, 1961; Vickrey, 1963); while inducing job densification, which improves total factor productivity (TFP), the source of a positive externality (Marshall, 1890). To parse out the effects and interaction of these externalities empirically, we use a spatial general equilibrium model treating transportation, output, labor, real estate and land markets. The TFP externality reduces marginal costs and output prices, benefitting consumers, including those importing from the region. Wages and rents increase but only after normalization by an output price index. The unsubsidized TFP externality adds importantly to the GPE's social benefit-to-cost ratio, despite causing fiscal losses from nominal income tax, sales tax and fuel tax revenues. Pigouvian congestion tolling raises long run welfare, and although toll revenue exceeds thrice the GPE's direct cost, it recovers only 62% of the direct cost plus the fiscal losses in the short run, but only 54% in the long run when the fiscal losses are larger. In the presence of distortionary taxation, consumers elsewhere who import from the region, and the unsubsidized TFP externality, charging more than Pigouvian congestion tolls improves overall social welfare but reduces the welfare of the in-region consumers.

Railway liberalization, airport congestion toll, and infrastructure pricing: Modelling and numerical analysis for European and Chinese markets

Regulation on infrastructure pricing affects various aspects, including demand, social welfare, and investment in transport management, as well as intramodal and intermodal competition. This study develops a game theoretic model that derives the charges (set by the infrastructure operators) and fare prices (set by the transport operators) as well as the associated profit and welfare in equilibrium. Key analytical insights concern the joint effect of the product differentiation by the transport operators and profit/welfare orientation of the infrastructure operators. If the transport operator implements more differentiation between air and HSR, or the infrastructure operators are more profit-oriented, the transport mode becomes less sensitive to the access charge from the competing mode, but more sensitive to the access charge from the same mode. Furthermore, using publicly available data for European and Chinese markets, we investigate the effects of introducing HSR on-track competition and congested infrastructures through numerical studies. Key findings are that entry by an incumbent-owned compared to a privately-owned HSR generates more industry benefits but leads to a significant reduction in consumer surplus. A more profit-oriented airport operator leads to increased total welfare if congestion is sufficient high. Theoretical and policy insights are provided.

How does trip frequency distort time value to impact congestion charging schemes?

Abstract A notable feature of a city or region with close economic and social connections with its neighbours is its highly mixed local and external traffic, and in some cases the external traffic volume is almost as high as that of local traffic. Whilst local traffic volume may be largely made up of the same regular local commuters making frequent trips, external traffic from outside of the city (region) may not be the same people making regular trips to/from the city. However, from a large pool of people making infrequent trips to/from the city, the existence of external traffic is proven by data from the licence plate recognition system of road vehicles in Changde, China. The function of value of time correlated with the income/wage rate and trip frequency is exploited and verified statistically. The time value distorted by trip frequency is defined as perceived time value (PTV), which also influences the way travellers perceive any travel impedance such as congestion delay and toll charges. This paper analyses the price of anarchy (POA) when explicitly considering the travel frequency of the trip-makers and their PTV, and compares with previous analysis without considering travel frequency. We show that when travel frequency is considered, the optimal toll of congested road pricing schemes which converts road traffic flow from user equilibrium into system optimization is much lower than that without considering travel frequency. The cost of licence plate auction cannot be treated as a congestion toll, which is only a threshold of vehicle ownership. That travellers choose routes by PTV rather than TV (time value) is proven by an example of Heishipu Bridge in Changsha, Hunan Province, China.

Collaborative Pricing in a Power-Transportation Coupled Network: A Variational Inequality Approach

This paper proposes a new collaborative pricing scheme for a power-transportation coupled network based on the variational inequality (VI) approach. In the proposed scheme, nodal electricity prices and congestion tolls on roads and at charging stations are considered to coordinate the coupled networks in order to minimize the operational cost of the whole system. The prices are determined by a second-order cone-based AC power flow model and a mixed user equilibrium model, respectively. A collaborative pricing model (CPM) is then built based on the two models and the interactions between them. In order to avoid the intractability of the developed non-convex model, the CPM is transformed into the VI formulation. With proven existence and uniqueness of solutions of the VI formulation, a new prediction-correction algorithm is proposed to accelerate the solution of the CPM problem, which is guaranteed to converge to the optimal solution. The proposed models and algorithm are verified using case studies on a real-world test system. The results show that the proposed pricing scheme can reduce the operational cost and the proposed algorithm shows improved convergence and higher computation efficiency compared with the existing algorithms.

Electric‐bus charging stations multi‐objective optimization planning on coupled power and traffic networks

AbstractThe electrification of public transportation is one significant step towards the sustainability of modern society. Both power networks and traffic networks are influenced by the optimal allocation of electric‐bus (e‐bus) charging stations. In this paper, the optimal operation cost of e‐bus charging stations is first designed based on the charging price and congestion toll. Charging price and congestion toll are used to guide charging behavior to reduce total traveling and waiting time. Second, the e‐bus charging station allocation method is proposed. The planning costs are optimized to locate e‐bus charging stations on coupled power and traffic networks. Third, a non‐dominated sorting genetic algorithm‐II (NSGA‐II) is adopted to solve the multi‐objective optimization problem, which maximizes the captured traffic flow and minimizes infrastructure investment at the same time. The effectiveness of NSGA‐II is proved compared with the enumeration method. Finally, based on a 33‐node power distribution network and a 77‐node traffic network, simulation results demonstrate the feasibility of the e‐bus charging station allocation method.

Quantifying diurnal changes in NO2 due to COVID-19 stay-at-home orders in New York City

IntroductionPolicy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 – June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day. MethodsHourly nitrogen dioxide (NO2) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agency's Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO2 concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification. ResultsNO2 concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval [CI]: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO2 at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7). ConclusionNY on Pause's impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.

Ship lock management and dynamic congestion toll for ships

Water transportation occupies the most proportion in transportation industry, as it is superior to other transportation modes in terms of economic scale. This paper focuses on a management problem of ship lock, which is quite common when ships pass a channel or a canal with a lock. Poor ship lock management will cause ship congestion and increase the cost of ships. Therefore, this paper formulates the problem as an activity-based bottleneck model, discusses the selection and decision of ship's departure time by taking container ships as examples with the constraints of ship lock service time window. And this paper also proposes a dynamic toll scheme for ships, with the aim at eliminating the waiting and stopping of container ships at lock, which can effectively reduce the social and economic losses. In addition, with the toll scheme, the waiting cost of ships at lock is converted into the congestion fee charged by the government, which is used to serve for locks and ships. Finally, a numerical experiment is used to illustrate the applicability of our proposed model.

Congestion tolling — Dollars versus tokens: Within-day dynamics

Tradable credit schemes (or tolling in tokens) are a form of quantity control, which promise to be an appealing alternative to congestion pricing (or tolling in dollars) owing to considerations of revenue neutrality, equity, reduced infrastructure costs, and political acceptability. The comparative performance of the two instruments under uncertainty in demand and supply has only recently received attention in the transportation setting, despite being widely studied for emission markets. In this paper, we add to this literature by considering a tradable credit scheme in a departure time context wherein users are provided an initial endowment of tokens by the regulator and incur a token charge (determined prior to all departures) to travel in a specific time-period. Tokens can be bought and sold within a marketplace at a price determined endogenously by token demand and supply. Two key features of the market model are: (1) the time-of-day dynamics of price is explicitly modeled through a smooth market clearing mechanism in each period, and (2) the selling decisions of users, which determine the distribution of token supply in the market over the day are explicitly modeled. This enables us to study the impact of selling behavior on performance of the credit system. Travel demand is modeled using a logit mixture model and supply consists of static congestion.Extensive experiments under stochastic demand show that when the tolls (in dollars and tokens) are not day-to-day adaptive, tolling in tokens outperforms tolling in dollars when congestion effects are more severe (e.g., realistic BPR models and steep congestion functions, high demand levels and high day-to-day variability). Importantly, we find that this result is robust with respect to selling behavior in the market, although there can be welfare losses in the quantity control system when selling behavior in the market is excessively irrational. These findings underscore the importance of examining disaggregate market behavior when designing tradable credit schemes. Moreover, when the supply of tokens can be adapted from day to day, the credit system was found to be superior in all tested scenarios, provided the selling behavior of individuals is rational. Finally, even in the case when toll revenues in the price instrument are equally redistributed (often difficult in practice), tolling in tokens (when tokens are equally distributed) is marginally more equitable in scenarios where congestion effects are more severe. These findings make a case for tolling in tokens.

Guardrails on priced lanes: Protecting equity while promoting efficiency

We examine the fairness of congestion pricing from two perspectives. First, using data from California’s six largest urban areas, we empirically estimate the share of the population that is both economically vulnerable and likely to be impacted by freeway congestion charges. Our estimates suggest that 13 % of households would fall into this category. Second, we consider ways to mitigate burdens for this group. In particular, we compare freeway use to use of other metered network infrastructure, like electricity grids and water systems. We suggest that assistance programs from these utilities provide useful lessons for protecting low-income drivers from road prices, and argue that policymakers would be less constrained in progressively redistributing congestion toll revenue than they would be in redistributing utility revenue.

Cost-effective reduction of fossil energy use in the European transport sector: An assessment of the Fit for 55 Package

This paper surveys climate and energy policy in the EU transport sector covering the road, aviation, and shipping sectors. We summarise current policies, focusing on the Fit for 55 Package, and link the different instruments being used (e.g. cap-and-trade, tax, mandate, performance standard, or subsidy) to different sources of market failure. Next, we analyse the static and dynamic cost-efficiency of the policies and instruments. We find that they address a range of market inefficiencies, but that there are still a number of aspects that can further improve the cost-effectiveness of current EU climate policies in the transport sector. For example, higher taxes and emission performance standards for aviation and shipping, the right combination of research and innovation investments and learning-by-doing policies, and balancing implicit carbon prices by revising the road tax system and adding congestion tolls and charges. Finally, European policy has important side effects on the rest of the world that need to be taken into account in the selection of policies. This improved set of policies can support a sustainable recovery and reach the European Union's climate targets at the lowest cost.

Proportional-Switch Adjustment Process with Elastic Demand and Congestion Toll in the Absence of Demand Functions

Proportional-Switch Adjustment Process with Elastic Demand and Congestion Toll in the Absence of Demand Functions

Departure time choice equilibrium and tolling strategies for a bottleneck with continuous scheduling preference

This paper develops a bottleneck model with continuous scheduling preference (CSP), which assumes that the unit cost of schedule delay penalty functions have continuously linear forms. In particular, the unit cost of schedule delay early is non-increasing with respect to arrival time, while the unit cost of schedule delay late is non-decreasing with respect to arrival time. We analyze the departure time choice equilibrium of commuters and find that the proposed bottleneck model with CSP is capable of eliminating the discontinuity of the departure rate curve, which occurs in the bottleneck model with discontinuous scheduling preference (DSP). In addition, the first-best and second-best congestion tolling strategies are designed in the bottleneck model with CSP. The analytical closed-form solutions of the bottleneck model with CSP under the time-varying toll, single-step coarse toll and multi-step toll are obtained and their effects on system performance are investigated. Finally, numerical examples are developed to illustrate the properties of the proposed models. Results shed light into the necessity of considering CSP in travel behavior analysis and congestion management. The ignorance of CSP can lead to overestimate of commuters’ bottleneck queuing time and the total system travel cost (TSTC), which finally reduces the efficiency of congestion tolling strategies.

Effectiveness of carbon tax and congestion cost in improving the airline industry greening level and welfare: A case of two competing airlines

In this paper, we examine the combined impact of carbon-tax policy, congestion cost and greening investment decisions of airlines. We model a Bertrand duopoly sequential move game to analyze the impact of airlines' decisions on ticket fare and greening effort, as they contemplate upon the cost option of greening investment and carbon tax. We model a duopoly market where incumbents and new entrant airlines compete in similar market. Our findings suggest that marginal utility of flight frequency decreases with ‘congestion toll’. In its absence, airlines have the opportunity to operate smaller aircrafts with high frequency. Secondly, our findings also suggest that airlines have higher ‘greening interest’ when emission taxes are imposed; without which, airlines are reluctant to invest in green technology. Additionally, our numerical simulations suggest that carbon tax, combined with congestion cost, may be used as an effective instrument to improve an airline's social welfare, and drive it towards green development. In fact, an efficient investment strategy can guide an airline to use greening services for their competitive advantage.

Congestion Toll Is Insane

Congestion Toll Is Insane

The long-run effects of congestion tolls, carbon tax, and land use regulations on urban CO2 emissions

CO2 emissions caused by urban residents' energy consumption arise from 1) transportation and 2) housing energy consumption. This energy consumption depends on the spatial population distribution of the city. The current study quantitatively examines the effectiveness of i) congestion tolls, ii) carbon tax, and iii) land use regulations on the social welfare and the reduction of urban CO2 emissions. Results show that the congestion tolls can increase the social welfare by about 85% of the increase in the first-best scenario, which is the best result among the three policies, and can reduce CO2 emissions from commuting and housing energy by about 22% and 3%, respectively. These results suggest that congestion tolling, which is primarily the Pigovian tax for congestion, not only internalizes congestion externalities, but also effectively reduces CO2 emissions through downsizing commuting distances and housing sizes. Nevertheless, we show that because any spending, including consumption of goods, generates CO2, how tax revenues are used is important for determining total CO2.

Strategic behavior under tradeable driving permits and congestion tolls: A political economy model

This paper develops a political economy model to study strategic behavior related to the introduction of congestion policies. Our main focus is on tradeable permits, although we also study results under a congestion toll. We first study a two-period model where, in the first period, a majority decides whether or not to introduce a permit system in the next period. The model setup is such that tolls and permits can be made perfectly equivalent, both in terms of welfare effects and voting outcomes. We find that anticipatory behavior after the policy is announced but prior to its introduction induces people to drive more; the overall effect may be welfare reducing. Moreover, drivers oppose the policies even when they receive all permits for free, or toll revenues are distributed to drivers only. Consequently, strategic behavior makes it more difficult to get a political majority to support these congestion policies. We further show that, in an infinite horizon setting, tradable permits and congestion tolls are no longer equivalent. Permits are superior to congestion tolls in that they avoid strategic behavior once the system is implemented. In contrast, with congestion tolls the steady-state equilibrium implies continuing strategic behavior. One consequence is that it is easier to get a political majority for permits than for tolls: we find that drivers will always oppose congestion tolls, but they support permits if they receive a sufficient share of the permits for free.