Dynamic congestion pricing is emerging as a potential approach to contemporarily manage traffic congestion and air quality. However, most toll road pricing strategies tend to rely on traditional solutions such as fixed or variable pricing, leading to suboptimal results in terms of traffic demand or pollution. In this paper, we propose a dynamic congestion pricing algorithm enabling to deal with both traffic congestion and PM2.5 levels reduction. Through a case study based on the SS36 road corridor connecting Milan to Bormio, we show that the proposed approach activates an extra toll fee on 28.26% of observations in 2022, leading to a total charge cost of 14.9€ million. This approach determines a reduction in road traffic density equal to 11.2%, contributing to a percentage drop of PM2.5 levels equal to 0.01%. The results remain robust across alternative specifications, including sensitivity analyses on air quality and traffic speed thresholds, as well as demand price elasticity assumptions. Overall, the paper shows that the dynamic congestion pricing strategy may provide insights for policymakers aiming to target both air quality and traffic management issues.

The 2024 electric vehicle distance-based charge introduced in Victoria, Australia, to recognise that such vehicles do not pay fuel excise tax, led to a high court challenge in which it was deemed unconstitutional for a State to introduce such a charge, which is the responsibility of the Federal government (through legislation amendment). This loss of fuel excise as a tax (not a charge) on electric cars whetted the appetite of the Federal Government to place road user charging on a round table in August 2025. We now have elevated the topic right into the political sphere where any change will require such support, and it opens up an opportunity to not only consider the fuel excise issue per se but the broader agenda on road pricing reform. • This short topical issues paper sets out a new political era for road user charging regime. • The focus is on the political buy as a result of concerns over loss of fuel excise aswe switches to electric vehicles. • A staged approach to reform is required to ensure the changes can occur with more detailed repricing. • A distance-based charge for all cars when removing fuel excise, vs just for EVs if we retain the fuel excise on ICEs.

The overarching goal of this paper is to introduce and study a class of random generalized inverse quasi-variational inequalities (RGIQVIs), which captures the desired properties of both random inverse quasi-variational inequalities (RIQVIs) and random generalized quasi-variational inequalities (RGQVIs) within the same framework. By using the randomization principle for coincidence points, the Banach contraction principle for set-valued mapping, and the Schauder fixed point theorem, we obtain some new existence theorems of random solutions for RGIQVIs under mild conditions. Moreover, we give some applications concerning the random generalized Nash game and random road pricing problem to illustrate and to support our main results.

Road price and capacity policies subject to a fiscal constraint in a city

Agent-based models have become valuable tools in transport planning, particularly for evaluating mobility policies in complex urban contexts. The model simulates the daily activity-travel patterns of approximately 3 million agents (10% of the population in Greater Jakarta), incorporating socio-demographic attributes and activity chains from household travel surveys. The modelling process includes population synthesis, activity imputation, and calibration against observed mode share, trip distances, and activity distributions, resulting in a realistic representation of urban travel behaviour. This study further develops policy scenarios and assesses the impact of distance-based electronic road pricing (ERP) for private cars and motorcycles. ERP scenarios are applied to eight major arterial roads in Jakarta, with tolls differentiated by travel distance and agent income using a Discrete Mode Choice (DMC) framework through Eqasim. Results show that ERP effectively reduces private vehicle use, particularly during the evening peak, where car traffic decreases by up to 19.95% and motorcycle traffic by 14.21% under the highest pricing scenario. However, the impact during the morning peak is more modest, reflecting lower travel flexibility. The results also show that the impact varies across socio-demographic groups, with stronger effects observed among low-income individuals, female users, working-age individuals, and employed persons.

Reinforcement learning for road pricing: a review and future directions

Assessing emergency medical services (EMS) accessibility before and after road pricing: A dynamic 2SFCA approach

Road transport has become one of the most politically contested domains of decarbonization, as measures such as road pricing redistribute costs and responsibilities in ways that directly shape everyday life. These conflicts signal a broader shift in climate governance, where low-carbon transitions increasingly hinge not on public acceptance but on political struggle. This article addresses this challenge by examining how contestation actively shapes transition pathways. We develop the concept of contestation-as-participation, which integrates insights from Energy Justice and Ecologies of Participation. This lens clarifies the content of justice claims while revealing the relational and emergent practices through which actors mobilize, transform, and negotiate these claims over time. In doing so, the article advances action-oriented approaches within Energy Justice by showing how justice is enacted, reworked, and made consequential through ongoing conflict. Empirically, we analyze media debates on road tolls in Bergen, Kristiansand, and Trondheim between 2000 and 2022, focusing on peak moments of contestation in 2006, 2013, and 2019. The findings show that: (i) contestation is not an obstacle but a driver shaping the direction and legitimacy of transition pathways; (ii) public debates involve heterogeneous actors, strategies, and claims that are obscured by notions of a singular “public”; and (iii) contestation generates ambivalent outcomes, simultaneously enabling democratic renewal and contributing to polarization and mistrust. We conclude that climate governance should not seek to minimize or bypass conflict. Instead, contestation must be recognized and engaged as a crucial form of participation—and as a resource for negotiating just, democratic, and resilient low-carbon transitions. • Shows contestation as constitutive and generative of transition politics • Introduces a contestation-as-participation lens, combining EJ and EP • Identifies three forms: justice-based, pluralistic, and strategic contestation • Demonstrates ambivalent outcomes of justice and participation claims • Argues that democratic governance must engage constructively with contestation

Road congestion has long been an issue plaguing urban areas, including Kuala Lumpur, the capital city of Malaysia. Accordingly, one of the strategies to reduce road congestion, as suggested by the experts, is road pricing, which is successfully practiced in several big cities around the world. Road pricing is a direct charge levied against drivers to reduce the number of private vehicles during peak hours. However, policymakers remain doubtful of its success in effectively reducing road congestion in Kuala Lumpur. In this regard, this study aims to identify the causes and effects related to road pricing implementation to reduce road congestion. To fulfil that, a causal loop diagram (CLD) model based on the system dynamics (SD) approach is developed by considering four significant causal relationships, namely the degree of road congestion, driving attraction, public transport, and road pricing charge. In developing CLD, a curved line with an arrow is created to represent the causal relationship that links one variable to another variable. Every link in the diagram must be labelled with polarity, whether positive or negative. Subsequently, the feedback loop is indicated in two types: either the reinforcing loop or the feedback loop based on the number of negative polarities. As a result, road pricing, road congestion, and driving attraction turn into a reinforcing loop where the changes in these loops could drastically affect the whole system. From the managerial perspective, this research helps highway stakeholders in Malaysia make better decisions by having a holistic view of road pricing implementation for a better metropolitan lifestyle.

Autonomous vehicles (AVs), including privately owned self-driving cars and shared autonomous vehicles (SAVs), hold great potential to transform urban mobility by enhancing safety, accessibility, efficiency, and sustainability. However, their widespread deployment also carries the risk of significantly increasing vehicle miles traveled (VMT), a phenomenon known as the rebound effect. This paper examines the VMT rebound effects resulting from AV and SAV deployment, drawing on recent studies and global case insights. We conducted a systematic narrative review of 48 studies published between 2019 and 2025, drawing on academic sources and credible agency reports. We do not conduct a meta analysis. We quantify how different automation levels (SAE Levels 3, 4, 5) impact VMT and identify the primary factors driving VMT growth, namely: reduced perceived travel time cost, induced demand from new user groups, modal shifts away from transit, and empty VMT. Global case studies from North America, Europe, Asia, and the Middle East are reviewed alongside regional policy responses. Quantitative analyses indicate moderate to significant VMT increases under most scenarios—for example, approximately 10 to 20% increases with conditional automation and potentially over 50% with high/full automation, under the circumstances of no effective policy interventions. Meanwhile, aggressive ride-sharing and policy interventions, including road pricing and transit integration, can mitigate or even reverse these increases. The discussion provides a critical assessment of policy strategies such as mileage pricing, SAV incentives, and integrated land-use/transport planning to manage VMT growth. We conclude that without proactive policies, widespread AV adoption is likely to induce a rise in VMT, but that a suite of well-designed measures can steer automated mobility towards sustainable outcomes. These findings help policymakers and planners balance AV benefits with congestion, energy use, and climate goals.

Motorcycles are a popular mode of transportation for many people. Their simple design makes them easier to maneuver than other types of vehicles. However, the increasing ownership of motorcycles has the potential to increase conflicts with other road users, especially in heterogeneous traffic. Motorcycle movements, especially in urban areas, can affect road performance and ultimately lead to higher levels of vehicle emissions. This research paper is a systematic literature review (SLR) examining evidence from studies on motorcycle demand management policies implemented in various countries. The focus is to evaluate the effectiveness of these policies, especially in countries with high motorcycle usage rates. To address the problem of vehicle emissions on roads with significant motorcycle traffic, several policies have been implemented by relevant authorities. These include banning motorcycles from certain areas or time periods, introducing congestion price, electronic motorcycles, using eco- friendly fuels, and promoting mode shift. The research finding is that a combination of congestion/electronic road pricing policies and a mode shift to public transportation is the most effective traffic management strategy for reducing air pollution.

We present a novel road pricing protocol which, unlike existing solutions, provides verifiable privacy guarantees to users without requiring any dedicated hardware. Instead, our protocol makes use of the GNSS capabilities of users' cell phones to track their travel history. This makes it a cost-effective and accessible solution to pay-per-use road pricing. The novelty of our approach lies in the use of a hybrid cryptosystem to ensure user privacy. Specifically, the service provider divides the monitored area into cells, assigning each a key. Some keys are genuine public keys with known private keys, while others are hash outputs designed to appear identical to the real keys, making it impossible for users to distinguish between them. As users travel, their data is encrypted with these keys before being shared. The service provider is therefore only able to decrypt data encrypted with real keys, allowing for random checking. At the end of the protocol, the provider shares the preimages of the hash outputs with the users, proving non-knowledge of the associated private keys. We evaluate our protocol's security and show that it provides resistance to misbehaving users, dishonest service providers, and third-party listeners. Additionally, we instantiate our protocol using ElGamal encryption and the SHA-256 hash function, and provide a proof-of-concept implementation with benchmarking results.

Congestion is one of the most problematic concerns that cities experience currently, and Rawalpindi – Pakistan is not an exception. The roads of Rawalpindi especially in the Saddar area have turned into one of the worst places for commuters as well as for city authorities and managers. The area concentrated with commercial centres, wholesale markets, government and private offices experiences a very high traffic density resulting in longer travel times, higher fuel consumption and more emissions. Therefore, this study considers road congestion pricing as an appropriate strategy for confronting this problem proactively since it is based on demand-side management using the software; VISUM. The study is aimed at helping policy makers early on develop equitable and workable road pricing. This can reduce traffic volume and discourage usage of private vehicles on roads by using private cars or even any other forms of transport in time slots, hence showing 8.3% reduction of volume when charges were implemented in the study period for car users and light transport vehicles. Equally promising is the financial impact: an estimated PKR 67 billion annually through road pricing, which is an enormous source for reinvestment into urban transport infrastructure, such as developing reliable public transport systems, improving road quality, and modern toll collection. This is where current developments in road pricing come in — to demonstrate how this transport management tool can have impacts on one of Rawalpindi’s important urban routes before cautious endorsement is given to embracing this particular solution for improving sustainable accessibility without disadvantaging people.

Stationary charging, electric road charging or battery swapping? A multi-day truck trip cost model

Intermodal freight transportation network design with road pricing: a Lagrangian relaxation algorithm

A biased preference for the status quo could explain the increased support for policies following their implementation. However, the influence of status quo bias on support for transport policies has been analysed to a limited extent only. The counterfactual test serves as a potential method to empirically explore this influence by framing policies as the existing or alternative situation. This paper employs the counterfactual test to ascertain whether individuals disproportionately favour the status quo. To this end, we have designed separate experiments focusing on three transport policies: road pricing, speed limits, and train ticket fare differentiation. The results indicate that status quo bias does indeed influence support for transport policies. Participants prefer each policy option when framed as the status quo. In contrast, support for the same policy option declines when presented as the alternative situation. These findings underscore the irrational tendency to adhere to the status quo, which may stem from psychological commitments or cognitive misperceptions. Therefore, politicians, policymakers, and practitioners should anticipate a bias towards the status quo when introducing controversial transport policies. • Status quo bias influences support for controversial transport policies. • The status quo is consistently preferred over alternatives in three experiments. • The counterfactual test is effective in testing bias favouring the status quo in transport policies.

The increasing share of battery-electric vehicles (BEVs) goes hand in hand with declining government revenue from fossil fuel taxes. This, in turn, erodes funding for roads and other purposes. One currently considered option by governments for filling the emerging budget gap is a BEV mileage tax. Recent research suggests that public support for a transition from vehicle fuel taxes to mileage taxes for all vehicles is low. But what about a mileage tax on BEVs only? We argue that majority public support for a BEV mileage tax is currently conceivable, given that owners of electric vehicles may be perceived as (partial) free riders, specifically in countries where fuel taxes are earmarked for road infrastructure. Based on a choice experiment with a representative sample of the adult population in Switzerland ( n =3283), where such a BEV mileage tax is currently considered, we study overall support and also assess how policy design attributes, such as the mileage measurement method and the chosen tariff system, affect policy preferences. We find that a BEV mileage tax could obtain majority support, specifically for tax designs that account for vehicle weight and power. At the same time, current BEV owners are less supportive of a new BEV mileage tax, indicating that growing BEV ownership could challenge policy implementation. Further, we discuss the risk of how the increase in ownership costs for BEV holders could potentially slow BEV adoption and jeopardize climate targets. The research reported here provides a template for studying the issue in other countries. • More battery electric vehicles (BEVs) lead to less revenue from vehicle fuel taxes. • A BEV mileage tax is politically feasible from a public opinion perspective. • Tax designs that account for vehicle weight and power are preferred. • Privacy and burden perceptions drive preferences for distance measurement methods. • Current BEV owners hold more negative views on a BEV mileage tax.

This work presents a knowledge-based approach to traffic congestion pricing system and control. The road traffic congestion has attracted different intelligent contributions which have addressed many real-time traffic scenarios at a toll point unlike the flat toll system that renders parallel toll for every traffic condition. However, existing works on dynamic traffic congestion pricing systems focus entirely on the traffic parameters without taking cognizance of the impacts of the weight of vehicles on the road. More so, despite the numerous health hazards associated with air pollution from vehicle exhaust during traffic peak hour, effects of emission have not been conceived as pivotal input to be circumvented in road toll design. Therefore, a fuzzy logic-based approach to dynamic traffic congestion pricing problems in a 1*2 traffic scenario comprising of a fast lane and a slow lane, is presented. The inputs to the fuzzy inference system are the weights of vehicles, the rate of carbon dioxide emission, and the traffic density on the toll lane; while the output is the congestion price. Simulations results indicate the qualitative robustness of this approach in handling the inherent nonlinear nature of road pricing problems. Investors and traffic management systems can rely on the simplicity, reduced computation cost, reduced health hazards and the justified investment worthiness on road and toll facilities.

Traffic congestion is a common problem in developing countries including Indonesia, especially in dense urban areas such as Bandung City. This study analyzes the potential for the implementation of Electronic Road Pricing (ERP) on Jl. Soekarno Hatta (Gedebage Intersection - Cibiru Roundabout), Bandung City. Traffic characteristics show a Saturation Degree (DJ) value of 0.85 in the morning and afternoon and 0.75 in the afternoon, with Level of Service (LoS) E and D. Congestion costs reach Rp 47,710,714 (morning), Rp 55,759,813 (afternoon), and Rp 75,905,411 (afternoon) per hour. The results show that the implementation of Electronic Road Pricing (ERP) system can reduce the use of private vehicles and increase the efficiency of congestion costs. Thus, the Electronic Road Pricing (ERP) system is a relevant travel demand management strategy in urban areas of Indonesia.

This study addresses the critical environmental challenge of increasing carbon emissions from Thailand’s freight transport sector, focusing on container movement in the strategic Lat Krabang ICD–Laem Chabang Port corridor. The research quantifies and compares CO2 emissions between rail and road container transport modes to identify potential carbon reduction strategies. A comprehensive activity-based methodology was employed, incorporating fuel consumption testing across multiple load conditions, detailed transport activity mapping, and the application of locally relevant emission factors. The results demonstrate that rail transport produces 32.82 kgCO2eq/TEU compared to 53.13 kgCO2eq/TEU for road transport, representing a 38.23% emission advantage. Fuel consumption testing revealed a power relationship between train weight and fuel consumption (y = 0.1121x0.5147, R2 = 0.97), indicating improving efficiency with increased loading. Terminal operations contribute significantly to rail transport’s emission profile, accounting for 36% of total emissions. The current modal split presents substantial opportunities for emission reduction through increased rail utilization. This study identifies and evaluates practical carbon reduction strategies across operational, technological, and policy dimensions, with priority interventions including load factor optimization, terminal efficiency improvements, locomotive modernization, and differential road pricing. This research contributes empirical evidence to support sustainable freight transport development in Thailand while establishing a methodological framework applicable to emission assessments in similar corridors throughout developing economies.