Road Pricing Research Articles

Potential Application of Electronic Road Pricing (ERP) on Bandung City Roads

This research investigates the potential implementation of Electronic Road Pricing (ERP) in Bandung City, Indonesia, focusing on its effectiveness in reducing traffic congestion. The study employs a quantitative approach using a survey method, experiments, and statistical analyses to evaluate ERP's impact on road traffic performance and cost efficiency. The research design includes traffic volume analysis, vehicle operating costs, and data collection through questionnaires from Bandung residents selected randomly. The research subjects include frequent road users in congested areas, and the study was conducted in 2023. Using binary logistic regression, the results show significant shifts in road user behavior, with reductions in traffic volumes of 33% on Jalan Sukajadi, 38% on Jalan Dr. Djunjunan, and 23% on Jalan Terusan Jakarta. Additionally, ERP was found to improve cost efficiency in traffic management. The study concludes that ERP is a promising solution for managing congestion in Bandung, with broader implications for other congested cities in Indonesia.

Analysis Best Practice Policy Road Pricing to Overcome Negative Externalities of Motorized Vehicles in West Java

This research analyzes best practice policy road pricing in overcoming the negative externalities caused by motorized vehicles in West Java. Negative externalities, such as traffic congestion and air pollution, are major challenges for urban areas in West Java. Through implementation policy studies on road pricing in Singapore and London, this research analyzes the effectiveness of these policies in reducing congestion and improving air quality. The research methods used include literature reviews, policy analysis, and in-depth interviews. The research results show that road pricing can be an effective tool in reducing congestion and air pollution, if there is collaboration with the transportation department, police, and raharja services, adequate technology, effective outreach, and integration with improved public transportation. This policy must be designed holistically by taking into account related opportunities and issues. The role of communication, transparency and an inclusive approach is very important in increasing public acceptance of this policy.

Modeling of Applying Road Pricing to Airport Highway Using VISUM Software in Jordan

Road congestion in Amman City has been increasing yearly, due to the increase in private car ownership and traffic volumes. This study aims to (a) evaluate the toll road’s effects on society and the economy in Amman, Jordan, through a survey questionnaire using statistical software (SPSS), (b) assess the impact of the toll road on reducing congestion and delays using micro-simulation (VISUM), (c) identify the optimal toll price for a selected road using VISUM and (d) validate the simulated models with the optimal revenue. Traffic, geometric, and cost data about the toll technique of two sections on the Airport Highway (from the Ministry of Foreign Affairs to the Madaba Interchange; and from the Madaba Interchange to the Queen Alia International Airport (QAIA) Interchange) were used for simulation purposes. The toll road (across seven different scenarios at different prices) was evaluated for optimal revenue. The survey questionnaire was made based on all scenarios, including the AM peak hour. The operation cost for the toll road was determined based on the Greater Amman Municipality (GAM). The best scenario was determined based on the value of revenue (JOD). The results indicate that higher acceptance is achieved when applying road pricing during the AM peak hour and that users prefer the charging method based on travelled distance (54.02%). Additionally, the total cost of the manual toll collection (MTC) method is 126,935 JOD. Road pricing can reduce traffic delay (or speed up traffic flow) by 4.61 min in the southbound direction and by 9.52 min in the northbound direction. The optimal toll value is 0.25 JOD (34.08%), with revenues of 1089.6 JOD for 2024 and 1122.6 JOD for 2025. Eventually, applying road pricing on the airport road is shown to be effective and economically feasible only when using the manual method.

An environmentally-friendly optimization framework for road pricing and pavement management under public-private-partnership

Vehicular emissions and the unsustainable development of transportation systems have received increasing attention in recent years. On one hand, transportation emissions increase as car ownership increases. On the other hand, construction of the new transportation infrastructure and maintenance of the existing transportation facilities are needed as travel demand increases. Thus there is a growing market for Public-Private Partnership (PPP), which aims to overcome existing deficiencies of traditional approaches while stimulating the sustainable development of transportation systems. This paper proposes an environmentally-friendly multi-objective optimization framework to derive dynamic toll pricing strategies and pavement maintenance and rehabilitation (M&R) activities for road networks containing PPP projects. A case study of a road network containing toll and toll-free highways in Florida, United States is used to verify the performance of the proposed approach. The results show that the public and private sectors could coordinate their actions to guarantee profits for the private sector while alleviating negative externalities for society.

Assessing Survey Data to Study Traffic Flow Characteristics: An in-depth analysis of King Fahad Road, Al-Ahsa, Saudi Arabia

Traffic volume studies are crucial for understanding vehicle quantity, movements, and classifications at specific sites. This study aims to establish a correlation between flow rate and density, providing in-sights into traffic flow characteristics such as density, velocity, and flow, essential for effective road design. The proposed method combines automated (mobile phones and cars) and manual counts on separate sheets, offering a compelling alternative to traditional traffic study methods. The collected da-ta can be utilized for various purposes including estimating fuel consumption, road pricing, road user cost, and planning road network improvements. Acquiring precise traffic data using cost-effective, low-tech solutions is vital for comprehending urban traffic dynamics. Evaluating collected data, which encompasses traffic parameters like flow, density, and speed, is crucial for informing urban road de-sign and planning. For instance, traffic flow indicates throughput, density reflects traffic conditions, and speed is essential for calculating travel times. This investigation focused on King Fahad Road in Al-Ahsa, Saudi Arabia, chosen among three alternative urban roads based on varying traffic condi-tions. Smartphones and cars were used to collect traffic data during weekday evening peak hours, ana-lyzing the interrelation between traffic flow, density, and vehicle speed. Manual traffic counts were conducted to determine measured density and speed, which were then used to estimate calculated den-sity. Additionally, a statistical t-test was performed to validate measured density against calculated den-sity at a 5% significance level. The data collection systems utilized in this research provide a cost-effective solution, considering capital, operational, and maintenance expenses, while remaining por-table and non-intrusive to road users during surveys. These characteristics make the system a practical choice for implementation in developing nations where resources are constrained, rendering costlier al-ternatives economically unfeasible.

Private Electronic Road Pricing Using Bulletproofs With Vector Commitments

Private Electronic Road Pricing Using Bulletproofs With Vector Commitments

Multi-gated perimeter flow control for monocentric cities: Efficiency and equity

A control scheme for the multi-gated perimeter traffic flow control problem of monocentric cities is presented. The proposed scheme determines feasible and optimally distributed input flows for various gates located at the periphery of a protected network area. A parsimonious model is employed to describe the traffic dynamics of the protected network. To describe traffic dynamics outside of the protected area, the basic state-space model is augmented with additional state variables to account for vehicle queues at store-and-forward origin links at the periphery. The multi-gated perimeter flow control problem is formulated as a convex optimisation problem with finite horizon, and constrained control and state variables. This scheme aims to equalise the relative queues at origin links and to maintain the vehicle accumulation in the protected network around a desired set point, while the system’s throughput is maximised. For real-time control, the optimal control problem is embedded in a rolling-horizon scheme using the current state of the whole system as the initial state as well as predicted demand flows at origin/entrance links. Furthermore, practical flow allocation policies for single-region perimeter control strategies without explicitly considering entrance link dynamics are presented. These policies allocate a global perimeter-ordered flow to a number of candidate gates at the periphery of a protected network area by taking into account the different geometric characteristics of origin links. The proposed flow allocation policies are then benchmarked against the multi-gated perimeter flow control. A meticulous study is carried out for a 2.5 square mile protected network area of San Francisco, CA, including fifteen gates of different geometric characteristics. The results showed that the proposed approach is able to manage excessive queues outside of the protected network area and to optimally distribute the input flows, which confirms its efficiency and equity properties. Similar policies are expected to be utilised for dynamic routing and road pricing.

Beyond traffic jam alleviation: evaluating the health and health equity impacts of New York City’s congestion pricing plan

New York City (NYC) is slated to be the first jurisdiction in the USA to implement a cordon-based congestion tax, which will be levied on vehicles entering its Central Business...

Optimization of regulation and fiscal policies for urban residential land use and traffic network management

Residential land use density regulation is an important policy instrument for reducing the local external diseconomies caused by concentration of population and buildings in urban areas. But density regulation also affects the distribution of population across the whole urban space, which determines the travel demands hence traffic flows over the transportation network in the city. In this paper, we formulate a model integrating the residential location choice equilibrium, traffic network equilibrium and the housing market equilibrium, subject to floor area ratio (FAR) regulation, a representative practical strategy for density regulation. The restriction of FAR regulation on housing supply is formulated as a development coordination cost function dependent on the level of FAR that is actually realized under the designated upper FAR limit. Complementary location-specific tax/subsidy policies, and road pricing schemes, are also addressed in a unified manner.The mathematical structure of the model is explored, and efficient algorithms are developed for solving the equilibrium equations, and for the optimization of FAR regulations and the pecuniary strategies.

Effect of road pricing on the spatial distribution of traffic flow in a grid network

This paper develops a continuous approximation model for analyzing the effect of road pricing on the spatial distribution of traffic flow. The traffic flow density, which describes traffic flow as a function of position, is derived for a rectangular city with a grid network. The analytical expression for the traffic flow density demonstrates how the toll level, the size and shape of the toll area, and the shape of the city affect the spatial distribution of traffic flow. As the size of the toll area increases, reducing the traffic flow density at the city center becomes difficult. As the aspect ratio of the toll area increases, the traffic flow density at the city center increases. The shape of the city has less impact on the traffic flow density than the shape of the toll area.

Kesiapan Pemerintah DKI Jakarta Dalam Agenda Setting Rancangan Peraturan Pengendalian Lalu Lintas Secara Elektronik

The Electronic Road Pricing (ERP) policy or paid road policy is here as the newest innovation from the Regional Government of DKI Jakarta to solving the problem of Jakarta's traffic jams which are getting out of control every day. After going through a long journey, this ERP policy is contained in the legal basis for the Draft Regional Regulation (Raperda) for Electronic Traffic Control (PL2SE). The Raperda, which has entered the early stages of review by the DPRD, will be reviewed for its readiness in the study of the literature on this research as well as the agenda setting of the policy. The results obtained include the Regional Government of DKI Jakarta which has prepared regulations and a legal basis, determining road sections, and the time of implementation. However, the government still has many things to consider, including the tariffs that will be imposed on this ERP, the technology that will be used, the condition and quality of public transportation services and facilities to the management of the ERP policy that will be carried out. The agenda setting for this policy has a problem flow (policy stream) in Jakarta congestion which is already very difficult to control, where the contributing factors are the community's preference for private vehicles, the road capacity factor, the human (community) awareness factor for traffic order, and also the factor of unfinished infrastructure development.

Minimize population exposure to vehicle-generated emissions by road pricing

Vehicular emissions, as a major source of urban air pollution, are threatening public health. With a goal to regulate population exposure to vehicular emissions, three bilevel road pricing models are established to minimize the exposure to vehicular emissions for on-road travelers, near-road residents, and all populations in the study network. A simulated annealing-based method is applied to solve these models based on a first-best pricing scheme. For ease of implementation, a second-best pricing scheme is then proposed and solved based on a meta-heuristic approach coupled with genetic algorithm with elitism and simulated annealing. The proposed method is tested using the Nguyen-Dupuis network and the Sioux Falls network. It is found that a tradeoff exists between the objectives of minimizing the emission exposure levels of travelers and near-road residents. Another tradeoff is found between the objectives of minimizing total population exposure and total travel time. Results from the numerical example indicate that the optimality results obtained in the first-best pricing scheme may also be approximated by the second-best pricing scheme with fewer tolling locations and less toll collection. The conclusions drawn from the paper could potentially assist policymakers in formulating road pricing policies that prioritize environmental concerns.

Day-to-Day Road Pricing and Network Performance Analysis via Output Stability

Day-to-Day Road Pricing and Network Performance Analysis via Output Stability

Road Pricing with Green Vehicle Exemptions: Theory and Evidence

Road Pricing with Green Vehicle Exemptions: Theory and Evidence

Increasing the occupancy rates of cars: Carrot, stick or both?

This paper uses the Belgian national transport demand model for an analysis of measures to promote a higher occupancy rate for cars: (a) ‘carrot only’ policies that make carpooling more attractive (b) ‘stick only’ policies that make driving alone more expensive (c) a combination of both. An occupancy rate of 1.5 is obtained with a combination of a road charge of 4 EUR cent per km with a support measure for carpool that reduces the variable generalized costs of carpooling for commuting to work by almost 50%. Overall revenues from the road charge lie around 3 300 million EUR, while the monetary equivalent of the support to carpoolers lies around 1 300 million EUR. As the result of reduced car travel, revenues from fuel taxation decrease by around 700 million EUR. Combining road pricing with targeted support measures for carpooling can improve its public acceptance. However, the policies with the largest impacts on occupancy rates do not pass a cost-benefit test. Existing travel behavior suggests that carpooling has intrinsic drawbacks despite being one of the cheapest travel options, which explains why even measures with far-reaching budgetary implications fail to induce stated policy objectives in Belgium.

Comparative Evaluation of Road Pricing Schemes: A Simulation Approach (Australian Perspective)

Road network pricing and congestion charging continue to be debated as efficient instruments to address traffic congestion and emissions. For cities where the schemes have not been implemented yet, the impacts of these schemes are typically evaluated using transport simulation models to understand the impacts and design effective solutions before the schemes are deployed. This paper considers a simulation approach for the city of Melbourne in Australia to investigate the potential impacts of road network pricing on reducing private vehicle travel, road congestion, and vehicle emissions. The study uses a dynamic traffic simulation model developed for Melbourne using the AIMSUN modeling tool, which was extended for modeling road user pricing and congestion charging, including considerations and formulations of distance-based, delay-based, joint-distance-and-delay-based, and cordon-based schemes under low-cost, medium-cost, and high-cost regimes. The study’s contributions also include an extension of the modeling framework to include public transport options to allow for providing travelers with the option of choosing an alternative mode of transport if they do not wish to pay. A mesoscopic stochastic route choice modeling approach was adopted to examine the impact of road pricing inside a nominated charging zone within the network. The results showed it would be possible to achieve a reduction of 11% in vehicle count, a 20% reduction in travel time, a 13% reduction in emissions, and a 3% increase in travel speed within the proposed pricing zone under a high-cost pricing scenario. The results also showed a significant reduction in emissions resulting from shifting drivers who are not willing to pay the congestion charge to public transport. When 20% of car drivers shifted to public transport, carbon emissions were reduced by up to 30% and network performance improved by 45%, compared to the baseline scenario without pricing. The findings of this research provide important directions for policymakers in deciding on the type and scope of charging schemes to use and how these could reshape transportation taxation systems by moving away from taxes on vehicles through registration fees and towards user-pay taxations where travelers pay for the amount of travel they do or the pollution and emissions they are responsible for.

Collaborative road pricing strategy for heterogeneous vehicles considering emission constraints

Urban transportation problems, primarily characterized by traffic congestion and exhaust emissions, continue to worsen, significantly impeding the economic and social development of cities. Road pricing strategies have emerged as an effective approach to tackle urban transportation problems, and their successful implementation in numerous cities have garnered significant attention. In this context, this study introduces a collaborative road pricing strategy tailored for mixed traffic flow comprising both conventional vehicles (CVs) and new energy vehicles (NEVs). CVs and NEVs are considered as two distinct types of cars with heterogeneous characteristics. The collaborative road pricing strategy consists of two components: congestion pricing and emission pricing. A bi-level programming model for the collaborative road pricing strategy is built. Exhaust emissions within the low-emission zone (LEZ) are used as constraints for the model, while the optimization objective of the model involves minimizing the sum of total travel time and total emissions of the road network. The viability of the proposed collaborative road pricing scheme is demonstrated through numerical tests within the second ring road in Beijing, China. The results imply that the service level of the road network can be improved by implementing the collaborative road pricing scheme. It also concludes that, increasing the penetration of new energy vehicles would help to decrease traffic congestion and emissions.

Operation and Control of an Active Power Collector for Roadside Feeding Electric Road System

The integration of electric vehicles (EVs) as an environmentally sustainable alternative to traditional fossil fuel cars faces a range of technological obstacles, including battery technology, charging infrastructure, and standardization. Dynamic conductive road charging (DCRC) of EVs at high speed has the potential to overcome the technical limitations of existing static charging methods. An intelligent motorway system for EVs called tracked electric vehicle (TEV) was proposed to incorporate the latest technologies of dynamic road charging, autonomous driving, and smart city data into transport infrastructure. This paper presents the operation and control of an active bipolar power collection unit (PCU) for the TEV system. The PCU is seamlessly integrated within the wheel structure of an EV using the concept of a stationary-hub wheel, enabling conductive power transfer from roadside conduction rails while the vehicle is in motion. The PCU is equipped with various features designed to maintain the contact force (CF) with the conduction rails, effectively handle instances of wheel bouncing and vibrations, and ensure a consistently smooth dynamic power transfer. This paper presents the experimental validations of the active PCU controls, including the operation sequence of the PCU, CF control, and PCU interaction with wheel bouncing.

Day-to-day traffic control for networks mixed with regular human-piloted and connected autonomous vehicles

The emerging connected autonomous vehicle (CAV) technology offers a significant opportunity to address the congestion problem caused by the selfish routing behavior of human drivers. If the transportation management center (TMC) can control the routing of all vehicles on the network, they could easily reverse this effect. However, during the transition period, CAVs will share roads with human-piloted vehicles (HVs). In the era of mixed autonomy, a more realistic scenario is to route the CAVs to lead the traffic state towards the desired equilibrium. We first consider a repeated routing game in which the TMC can control the routes of CAVs to minimize the system travel time, i.e., CAVs follow the system optimal (SO) routing principle. In this manner, we can influence the travel time traversing each link, which indirectly influences HV users’ route choices. As a consequence, HV users may adjust their routes dynamically through day-to-day (DTD) learning to minimize individual travel cost. On the other hand, the SO routing strategy may induce higher travel time for CAVs than HVs within the same origin–destination (OD) pair. To address such inherent unfairness, road pricing is used to influence route choices of HVs to achieve specific supply regulation targets, e.g., traffic restraint. We present qualitative analysis on the stability of the controlled DTD dynamics and the effect of road pricing regarding the unfairness. To the best of our knowledge, this paper is one of the first to design dynamic pricing schemes for a mixed autonomy system under DTD learning dynamics. We carry out numerical experiments to demonstrate the effectiveness of the control schemes. The cooperative CAVs could reduce the total travel time when the market penetration rate of CAVs reaches the lower minimum control ratio that the network could escape the user equilibrium (UE) condition. When the market penetration rate of CAVs reaches the upper minimum control ratio, the network would achieve SO condition even though there are non-cooperative HVs. On the other hand, the pricing scheme can reduce the unfairness index and total travel time of the network when the market penetration rate of CAVs is low.

Model for the Evaluation of Urban Transport Policies and Their Interaction with the Housing Market

We analyze several scenarios of transport reforms for the city of Bordeaux (France) using a model that takes into account the interaction between transport and the housing market. We find that road pricing schemes are significantly more effective when they are accompanied by an increase in housing supply in locations where demand increases. This allows households to consider their options for relocation in the medium and long term. Our analysis is based on an aggregate model with a nested decision structure that includes both transport and housing. We provide a full description of the model structure and the calibration steps and make the source code available for those who wish to analyze other cases.