Toll Prices Research Articles

The effect of freeway toll pricing on travel mode changes, route changes, and departure time changes.

This study critically examines the influence of freeway toll pricing on the travel behavior of intercity commuters in Iran, focusing on mode choice, route selection, and departure times. A survey of 921 commuters was conducted to gather data, which was then analyzed using a mixed logit model. The key findings reveal that a one percent increase in toll prices leads to a 1.5101 percent decrease in the likelihood of commuters maintaining their usual travel mode. Conversely, the probability of selecting alternative travel options rises by 2.5129 percent. A notable change is observed in route choice, with a 1000 toman increase in tolls raising the likelihood of route change by 0.320 percent. Furthermore, increased tolls are associated with a higher probability of changes in travel mode (0.1188%) and departure time (0.1078%). This research highlights the significant behavioral shifts among commuters in response to toll pricing adjustments and underscores the need for strategic toll management in transportation planning.

An equilibrium approach for compensating public–private partnership concessionaires for reduced tolls during roadway maintenance

This study considers the possibility of exploiting excess capacity along concurrent tolled roadway facilities operating in a public–private partnership for the purpose of alleviating traffic congestion during improvement action execution on a public roadway facility. Increased access to the tolled facility is enabled by reducing or suspending tolls during periods of roadway improvement action and appropriately compensating the tolled facility concessionaire for expected losses. The problem of determining an optimal reduced toll pricing strategy and compensation level is referred to as the Maintenance Timing and Price Discovery (MTPD) problem. A multi-level optimization model and iterative solution method are proposed to solve this problem. As toll prices often depend on traffic levels, the model also determines the optimal timing and time-of-day and day-of-week for executing the set of required improvement actions over the planning horizon to ensure a lowest total cost. The multi-level model consists of two bilevel models. Solution of the greater model is attained at a Stackelberg equilibrium between these two bilevel models. An additional Stackelberg equilibrium is sought between upper and lower levels of each of these two bilevel models individually. The MTPD formulation and general solution methodology are applied on an illustrative example from which computational results are obtained. Insights from the results show that this strategy for alleviating traffic congestion during roadway maintenance or other improvement activities can lead to substantial savings in total agency and user costs.

Erroneous High Occupancy Vehicle Lane Data: Detecting Misconfigured Traffic Sensors With Machine Learning

Quality data are vital to the planning and operation of traffic systems. High occupancy vehicle (HOV) lanes, for instance, must comply with federal performance standards. If an agency fails to meet the standards, the facility is considered to be “degraded” and the agency is required to undertake actions that would return the facility to satisfactory operation. This could include removing exempted vehicles (e.g., low-emission vehicles) or increasing toll prices and passenger occupancy limits. Such policy changes may be costly, and may affect related policy goals, such as promoting clean air vehicles. Owing to constant changes in the system (e.g., roadwork, system upgrades), some of the thousands of HOV sensors in California’s transportation system are misconfigured, such as being labeled as general-purpose lanes. In this situation, HOV lane data may be mistakenly aggregated with general-purpose lane data and vice versa, causing a HOV facility to be erroneously reported as degraded and requiring unnecessary policy action. Detecting these misconfigurations is challenging and labor-intensive to accomplish manually. The purpose of this research was to utilize machine learning techniques to detect sensor misconfigurations and to understand the extent to which they affect performance reporting of HOV lanes. The results for Caltrans District 7 (Los Angeles and Ventura counties) showed that about 5% to 8% of Performance Measurement System HOV sensors are misconfigured. Therefore approximately 27 to 44 mi of HOV lanes are erroneously measured, with approximately 10 to 16 mi (38%) of those reporting an erroneously high degradation rating.

A multi-class toll-based approach to reduce total emissions on roads for sustainable urban transportation

High toll charges force trucks to avoid quality roads, leading to increased emissions. We propose a model in this study to find an effective toll charging scheme to minimize total network vehicular emissions while maintaining reasonable revenue for investors. A bi-level modeling approach is used, where toll prices for multi-class vehicles are decided in the upper level and user response to toll charges are predicted using user equilibrium conditions with multi-class traffic assignment in the lower level. The model takes into consideration both toll revenue and total vehicle operating costs to produce an acceptable solution for both investors and road users. All major components of hazardous emissions were considered and estimated using secondary data, quantifying their impact on human health and the environment. The application of the model was illustrated using two networks considering different toll charging scenarios and near-optimal solutions were found for each toll-charging scenario. The results revealed that commonly used toll schemes are inefficient with respect to multi-stakeholder objectives. The optimized toll charging scheme was able to reduce the total emission costs of the network by 12 % compared to the toll scheme currently used by a toll facility in a real network in Melbourne, Australia.

Socioeconomic and Political Issues in Transportation Public–Private Partnership Failures

Transportation public–private partnership (PPP) projects are long-term projects that usually break the status quo of public ownership. In fact, opposition to PPP projects stems from a variety of factors, such as political influence to favor certain interest groups and high toll prices. Close examination reveals that vulnerability to societal and political domains originates at certain individual points and creates a complex web of problems as it propagates through different socioeconomic and political levels and project stages. This article attempts to unveil such complex and problematic trends by analyzing ten failed transportation PPP projects to identify critical socioeconomic and political failure factors. Employing questionnaire surveys and path analysis, a failure-mechanism model is developed to depict all possible transportation PPP project vulnerabilities to the socioeconomic and political domains. This article's failure-mechanism model could act as a vulnerability-prediction model for transportation PPP practitioners in the public and private sectors, and it can help better understand socioeconomic and political issues’ impacts to transportation PPP projects.

Route choice preferences: insights from Portuguese freight forwarders and truck drivers

ABSTRACTExploring route choice in the context of tolled alternatives can support road operators to achieve better utilization of the infrastructure, as well as maximizing revenue collection. The research presented in this paper is conducted in the context of OPTIMUM, a European Union-funded project. The research objectives include a two-component system of models that proactively calculates commercial vehicles’ toll prices. The component presented in this paper rests on the development of a route choice model that estimates the probabilities of using two alternative routes (toll road vs. national road), based on route attributes and user characteristics. To explore the usefulness of the proposed methodology a case study involving 50 truck drivers and 25 freight operators was conducted in Portugal between January 2016 and November 2017. Results from the route choice model reveal interesting insights about the role of incentives in the choice of toll roads, the perspectives of the different decision-makers and produce Values of Time for the study area.

Novel Big Data-supported dynamic toll charging system: Impact assessment on Portugal’s shadow-toll highways

Traffic congestion is a huge problem in many countries. It affects not only the inner workings of cities but also the quality of life of the people that endure it. In Portugal, traffic congestion happens mainly on national/urban roads, and this phenomenon has increased since the introduction of the so called shadow-toll systems in highways that were free to use. This work proposes a toll charging system that relies on a novel dynamic congestion charging scheme, supported by state of the art Big Data technologies, in order to shift traffic from national/urban roads to tolled highways, taking into account not only the Quality of Service of the highways and national roads, but also the competitiveness of toll prices for users. This Intelligent Transportation System was tested and validated in a real-world scenario with one of the biggest freight logistics companies in Portugal and with the Portuguese public road infrastructure operator.

Transactive Control in Smart Cities

One of the important goals of a smart city is to increase the quality of urban mobility. This paper will explore the use of dynamic tariffs for this purpose. Transactive control, the concept of feedback through economic transactions, is a promising concept for accomplishing such dynamic tariffs, and is the focus of this paper. Two specific examples of transactive control are considered in this paper, the first of which is the synthesis of dynamic toll prices with the goal of reducing traffic congestion in highways. We examine how a model-based approach can result in optimal toll pricing schemes. Sociotechnical models that combine behavioral models of drivers and traffic flow models, together with real-time traffic information obtained from on-road sensors are used to determine the transactive control strategies. The overall pricing strategy is evaluated using real traffic data from an existing dynamic toll-pricing framework. The second example of transactive control is in the context of Mobility on Demand (MoD), where new modes of transportation other than private and public are being proposed, providing a smorgasbord of options for passengers. We investigate a dynamic routing concept for multipassenger transport, and propose a transactive control strategy to regulate the achievable performance around desired values. Numerical simulations using actual passenger data are carried out to demonstrate the advantages of the proposed concept.

The effects of concession period structures on BOT road contracts

Under the build-operate-transfer (BOT) approach, the private firm builds and operates a road within the concession period and transfers the project at no cost to the government at the end of the concession period. Based on whether the construction period and the private operation period are defined together or separately, there are two concession period structures: single-period concession structure (SPCS) and two-period concession structure (TPCS). This paper simultaneously compares socially optimal toll prices in both private and public operation periods, road quality, and concession period under SPCS and TPCS, respectively. We find that if the marginal social welfare with respect to toll price in private operation period is sufficiently more responsive than to road quality, then the optimal road capacity and toll prices under SPCS are higher than those under TPCS. Otherwise if marginal social welfare in public operation period is sufficiently more responsive to road quality, then the optimal toll prices under SPCS are lower while the optimal road quality under SPCS is higher. We also find that the optimal concession periods are independent of concession period structures. This paper has made three extensions to further investigate the effects of concession period structures (1) when the toll price is determined by the private firm; (2) when renegotiation takes place; and (3) when government support policies are present. Based on our model results, this paper derives several policy implications regarding BOT road contract design under different concession period structures.

PROMOTING SUSTAINABLE TRAVEL BEHAVIOR THROUGH TRANSPORT POLICY MEASURES

This paper examines how transport policy measures have influenced travel behaviour to promote sustainable transportation. Data were collected through a survey on 384 vehicle users to represent the 36 sections of Shah Alam, Selangor. This paper also studied the readiness of an urban population to reduce car usage. Maj ority of the respondents stated that the increase in petrol and toll prices would be the key factors to reduce car use, and more provision of public transport would encourage them to use public transport. However, Chi-square test showed that the willingness of the respondents to use public transport has a strong relationship with the frequency of driving a vehicle. The level of willingness to use public transport is lower when a car is used more frequently. Results also suggested that the majority of the respondents were not ready to consider cycling and walking as alternatives.

PROMOTING SUSTAINABLE TRAVEL BEHAVIOR THROUGH TRANSPORT POLICY MEASURES

This paper examines how transport policy measures have influenced travel behaviour to promote sustainable transportation. Data were collected through a survey on 384 vehicle users to represent the 36 sections of Shah Alam, Selangor. This paper also studied the readiness of an urban population to reduce car usage. Maj ority of the respondents stated that the increase in petrol and toll prices would be the key factors to reduce car use, and more provision of public transport would encourage them to use public transport. However, Chi-square test showed that the willingness of the respondents to use public transport has a strong relationship with the frequency of driving a vehicle. The level of willingness to use public transport is lower when a car is used more frequently. Results also suggested that the majority of the respondents were not ready to consider cycling and walking as alternatives.

PROMOTING SUSTAINABLE TRAVEL BEHAVIOR THROUGH TRANSPORT POLICY MEASURES

This paper examines how transport policy measures have influenced travel behaviour to promote sustainable transportation. Data were collected through a survey on 384 vehicle users to represent the 36 sections of Shah Alam, Selangor. This paper also studied the readiness of an urban population to reduce car usage. Maj ority of the respondents stated that the increase in petrol and toll prices would be the key factors to reduce car use, and more provision of public transport would encourage them to use public transport. However, Chi-square test showed that the willingness of the respondents to use public transport has a strong relationship with the frequency of driving a vehicle. The level of willingness to use public transport is lower when a car is used more frequently. Results also suggested that the majority of the respondents were not ready to consider cycling and walking as alternatives.

Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

Network pricing serves as an instrument for congestion management, however, agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand, which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context, but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly, interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear, and the set of equilibrium paths is constant. These assumptions are restrictive, so three larger networks are considered numerically, and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases, optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.

Integrating congestion pricing and transit investment planning

This paper develops a mathematical model and solution procedure to identify an optimal zonal pricing scheme for automobile traffic to incentivize the expanded use of transit as a mechanism to stem congestion and the social costs that arise from that congestion. The optimization model assumes that there is a homogenous collection of users whose behavior can be described as utility maximizers and for which their utility function is driven by monetary costs. These monetary costs are assumed to be the tolls in place, the per mile cost to drive, and the value of their time. We assume that there is a system owner who sets the toll prices, collects the proceeds from the tolls, and invests those funds in transit system improvements in the form of headway reductions. This yields a bi-level optimization model which we solve using an iterative procedure that is an integration of a genetic algorithm and the Frank–Wolfe method. The method and solution procedure is applied to an illustrative example.

Design of income-equitable toll prices for high occupancy toll lanes in a single toll facility

ABSTRACTIncome inequity potentially exists under high occupancy toll (HOT) lanes whereby higher-income travelers may reap the benefits of the facility. An income-based multi-toll pricing approach is proposed for a single HOT lane facility in a network to maximize simultaneously the toll revenue and address the income equity concern, while ensuring a minimum level-of-service on the HOT lanes and that the toll prices do not exceed pre-specified thresholds. The problem is modeled as a bi-level optimization formulation. The upper level model maximizes revenue for the tolling authority subject to pre-specified upper bounds on tolls. The lower level model solves the stochastic user equilibrium problem. An agent-based solution approach is used to determine the toll prices by considering the tolling authority and commuters as agents. Results from numerical experiments indicate that a multi-toll pricing scheme is more equitable and can yield higher revenues compared to a single toll price scheme across travelers.

Assessment of the effectiveness of fuel and toll pricing policies in motorway emissions: An ex-post analysis

In this paper the environmental impacts of fuel and toll pricing policies were evaluated for eight Portuguese motorways for the period between 2008 and 2011. To perform such study, firstly the analysis of the elasticity was done to assess the sensitive of traffic demand. Then emission costs were estimated considering an integrated approach of environmental and human health impacts. Two motorway groups were analyzed: one originally built with both conventional and electronic toll systems (G1); and another recently equipped with non-stop electronic tolls (G2). The results show that the elasticity of the system changes with the fluctuation prices, particularly influenced by toll prices variation. During the analysis period, traffic volumes decreased (8–11% in G1, and 15–41% in G2). About 75% of traffic flow shows a high statistical significance correlation (p < 0.05) with toll prices, which highlight the impact of toll prices. Differences between emission costs can be close to 50% in those motorway groups. Nevertheless, due the absence of data in alternative routes, the obtained results show only the potential maximum environmental gains of these policies in motorways. This limitation is very important in the quantification of the environmental global impacts. Non-toll roads are usually characterized by slower speeds and higher emissions. Therefore the above mentioned gains can be converted, in these cases, in losses.

Managed Lane Toll Prices

This research involved a simulation that compared 3 days of actual traffic data for the I-95 Express Lanes and general purpose lanes in Miami, Florida, with a hypothetical scenario in which all transportation demand management (TDM) activities and toll exemptions were eliminated. The purpose of the research was to quantify the extent to which carpooling, vanpooling, and transit use contribute to better traffic flow in the I-95 corridor. In the hypothetical scenario there was a slight degradation in express lane level of service (LOS) and a slight increase in tolls in the southbound direction. Conversely, there was a slight improvement in express lane LOS and a slight decrease in tolls in the northbound direction. In the hypothetical scenario, many inherently low emission vehicles (ILEVs), which are toll exempt, opted out of the express lanes. The increase in express lane volume from former carpoolers, vanpoolers, and transit riders reverting to single-occupant status was often offset by even larger volumes of ILEVs leaving the express lanes. Although the traffic effect on the express lanes was mild, the effect on the general purpose lanes was more severe. In the hypothetical scenario, the general purpose lanes operated at LOS F 22% more of the time in the southbound direction and 8% more of the time in the northbound direction.

HOT or not: Driver elasticity to price on the MnPASS HOT lanes

The Minnesota Department of Transportation (MnDOT) has added MnPASS High Occupancy Toll (HOT) lanes on two freeway corridors in the Twin Cities. While not the first HOT lanes in the country, the MnPASS lanes are the first implementation of road pricing in Minnesota and possess a dynamic pricing schedule. Tolls charged to single occupant vehicles (SOVs) are adjusted every 3 min according to HOT lane vehicle density. Given the infancy of systems like MnPASS, questions remain about drivers' responses to toll prices. Three field experiments were conducted on the corridors during which prices were changed. Data from the field experiments as well as two years of toll and traffic data were analyzed to measure driver responses to pricing changes. Driver elasticity to price was positive with magnitudes less than 1.0. This positive relationship between price and demand is in contrast with the previously held belief that raising the price would discourage demand. In addition, drivers consistently paid between approximately $60–120 per hour of travel time savings, much higher than the average value of time. Reasons for these results is discussed as well as the implications these results have on the pricing of HOT lanes.

Dynamic Road Pricing for Revenue Maximization

A modeling framework and a solution methodology are presented for the toll problem of dynamic revenue maximization. The problem requires determining the optimal time-varying toll prices for a multigantry toll road facility so that total revenue is maximized subject to agency-mandated constraints on average speed and average traffic volume. The framework extends a real-time traffic network state estimation and prediction system to provide dynamic pricing capabilities. The presented framework overcomes limitations of most existing approaches by considering two factors: consistency between the toll value and drivers’ willingness-to-pay behavior and drivers’ route choice dynamics in regard to competition between the toll facility and alternative routes. The paper presents the results of a set of simulation-based experiments that were conducted to examine the robustness of the proposed prices under several operational scenarios.

Willingness to Pay for High-Occupancy Toll Lanes

This research examined the willingness of travelers to pay for travel time savings (TTS) on the I-394 MnPASS express lanes in Minneapolis, Minnesota, and the I-15 express lanes in San Diego, California. The findings from both facilities indicate that many travelers are willing to pay a toll for a small TTS. The revealed preference values of time for the I-394 paying customers averaged $73/h in the morning and $116/h in the afternoon. Travelers on the I-15 express lanes received slightly higher TTS than on the I-394 and typically had a lower willingness to pay. Their revealed preference values of time averaged $49/h in the morning and $54/h in the afternoon. On the basis of the magnitude of these values, it is likely that travelers are paying for more than just TTS, possibly travel time reliability also. This finding means that these lanes likely have added value to travelers beyond time savings. The variability of the dynamic toll prices on the I-394 MnPASS express lanes in Minnesota and the I-15 express lanes in San Diego was also examined. Toll rates during the morning and afternoon peak hours varied considerably, with tolls ranging from $0.50 to $8.00. Conversely, off-peak times showed little to no variation. These trends were similar for different days of the week, and even from year to year. These trends were common across both I-394 and I-15 express lanes, although more variation was found on I-15. Tolls varied little during off-peak periods.