Toll Charges Research Articles

Blockchain-enabled intelligent toll management system

Abstract Road toll tax contributes significantly in the economic development of any nation. In developing countries, the toll tax collection is carried out either manually or electronically. However, both approaches suffer from various challenges, including prolonged waiting times, lack of transparency, high operational costs, and concerns regarding data security and privacy. This research aims to address these challenges using a blockchain-based system. The proposed system employs advanced image processing techniques, specifically “You Only Look Once” version 5 (YOLOv5), to accurately capture and store vehicles’ registration numbers in a local server situated at toll plazas. Subsequently, the vehicle identification, along with the driver’s credentials, is transmitted to an application server, where an Ethereum smart contract verifies the information and automatically deducts the toll charges from the driver’s account. The results from this study indicate that the proposed system effectively reduces vehicle waiting time and facilitates uninterrupted vehicular movement. Additionally, the system ensures transaction transparency, safeguards the security and privacy of vehicle details, facilitates non-stop payments, rendering unnecessary cash payments or radio-frequency identification scanning at toll booths, and incorporates a decentralized architectural framework to enhance security and mitigate potential system failures.

Pricing and revenue allocation mechanisms for regional logistics networks in Cyber-Physical Internet

Cyber-Physical Internet technology links physical and virtual networks, facilitating communication and coordination for logistics stakeholders regarding their operational decisions. However, the optimal pricing within a regional logistics network incorporating Cyber-Physical Internet remains unexplored. To address this issue, this paper develops a Stackelberg game model between a carrier and a group of road operators. We derive and analyze the equilibrium decisions of the carrier’s logistics service fee and road operators’ tolls under distributed and horizontal partnership pricing strategies. Furthermore, we compare these two strategies and design a revenue allocation mechanism for road operators. Our theoretical and numerical analyses yield the following key findings. First, our results debunk the prevailing belief about toll pricing, demonstrating that road operators reduce their toll charges in response to a peer’s toll increase driven by rising unit variable road costs. Second, a collaborative pricing strategy among road operators consistently enhances market demand and profits by minimizing toll charges to the carrier. Third, revenue allocation among road operators is primarily based on unit variable road costs, ensuring fair distribution and encouraging cooperation for long-term benefits. This study enhances our understanding of both theoretical and practical aspects of pricing strategies for carriers and road operators within Cyber-Physical Internet.

Travel burdens to access care among children with cancer between 2016 and 2019: Analysis of a national population-based cancer registry in Japan.

Centralization of cancer care increases survival but increases the travel burden (i.e., travel durations, distances, and expenditures) in visiting hospitals. This study investigated the travel burdens to access cancer care for children aged 18 years and younger in Japan. The study population comprised 10,709 patients diagnosed between 2016 and 2019 obtained from a national population-based cancer registry in Japan. Their residences were classified as urban or rural. We counted the number of patients treated at specialized hospitals and investigated the treatment centralization across diagnostic groups by Pareto plot. Travel burdens to access care were estimated using a route-planner web service and summarized using median values. A multivariable logistic model was performed to investigate factors associated with the events of car travel duration exceeding 1 h. Of the patients, 76.7% lived in urban areas, and 82.5% received treatment in designated hospitals for childhood cancer. The Pareto plot suggested that the top five hospitals treated 63.5% of patients with retinoblastoma. The estimated travel burdens for all patients were 0.62 h (0.57 h in urban areas and 1.00 h in rural areas), 16.9 km, and 0.0 dollars of toll charges. Regarding travel duration, 21.7% of patients had travel exceeding 1 h, and rural areas, retinoblastoma, malignant bone tumors, and childhood cancer-hub hospitals were associated with travel duration exceeding 1 h (adjusted odds ratios of 6.93, 3.59, 1.94, and 1.91, respectively). Most patients were treated in specialized hospitals and the treatments for specific diseases were centralized. However, most patients were estimated to travel less than 1 h, and the travel burden tended to increase for patients in rural areas, those with specific diseases, and those going to specialized hospitals. Cancer control measures in Japan have steadily improved centralized treatment while keeping the travel burden relatively manageable.

Period-dependent pricing methods of multi-type vehicles for BOT highway projects with pavement rehabilitation effects

In the planning stage of a BOT highway project, the future traffic demand plays a pivotal role on designing contract factors. Considering that the traffic demand generally has variations with time, the constant toll during the concession period obviously is not a good choice. And the different toll charges classified by vehicles types definitely affect the traffic composition and maintenance cost. To address this practical issue, this study proposes the mixed integer nonlinear programming models to select the period-dependent toll charges for multi-type vehicles and highway capacity, by considering both the objectives of the government and private firms. Then two solution algorithms are provided to solve our proposed models. Finally, numerical experiments are conducted to assess the applicability and efficiency of our models and algorithms.

A toll-based approach for regulating hazmat transportation network considering boundedly rational route choice

This paper introduces a novel toll charge to regulate transportation of hazardous materials (hazmat), taking into account that carriers are bounded rational decision-makers. In the case of bounded rationality, the route choice behaviour of carriers is described based on the link-based perception error model. Then, a novel bi-level programming model is developed, which aims to minimise both total tolls and maximum total risk, while finding the shortest path according to certain perception errors. To effectively solve the proposed model, it is decomposed into two subproblems, and the particle swarm optimisation algorithm and K-shortest paths algorithm are designed. Furthermore, an extended model is developed to ensure risk equity between different links, where the constraints on maximum link risk are added. Numerical experiments are conducted to validate the proposed models and algorithms, demonstrating that maximum total risk can be effectively mitigated and risk equity between different links can be achieved.

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.

The Day-to-Day Departure Time Choice of Heterogeneous Commuters Under an Anonymous Toll Charge for System Optimum

We consider a bottleneck system in a state of disequilibrium, in which commuters are heterogeneous in the values of travel time and schedule delays. Three representative dynamical systems are used to formulate the day-to-day departure time choice of commuters, and a Walrasian toll charge scheme is utilized to control the evolutionary process of traffic flows. The toll charge scheme is anonymous; that is, toll charges are identical for all user classes, and the scheme’s implementation does not need to resort to information on the values of travel time and schedule delays. We find that the system optimum (SO) flow pattern can be achieved at the stationary state under the implementation of the toll charge scheme. The equivalence between the stationary state and the SO, the existence of the toll charge for achieving the SO, and the convergence of day-to-day traffic flows to the SO under the implementation of the toll charge scheme are theoretically proved. The distributions of traffic flows and toll charges at the SO state during morning rush hour are analytically shown. The application of the toll charge scheme to a network with multiple trip origins is presented. The effectiveness of the toll charge scheme for achieving the SO is also examined by numerical analyses. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72171007, 71890972/71890970, and 72021001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.1191 .

A Review on Location Based Efficient Road Toll Collection System using RFID and NPRS Techniques

The road traffic controlling and road toll collections are became one of the challenging tasks in most of the developing and developed countries. The tollgate systems doesn’t account and verify from which particular place (source) the vehicle is started or joined that concern toll road and up to which particular point (destination) it reached/left/disjoined/used the road. If a toll road is of 60 KM length and a vehicle X started 05 KM away from its tollgate and another same category vehicle Y starts from 60 KM away will have to pay same charges. These existing systems are unable to tell which vehicles are using how much road services and accordingly how much should they pay for it. Therefore, specifically in Indian state highways are concern, road toll collection systems are not efficient and not justifying with the road pricing practices with vehicle owners. Due to these, most of the vehicle owners and passengers are facing numerous types of problems while travelling from one place to another place by road. To solve these issues, I tried to propose an efficient location based road toll collection system using RFID (Radio Frequency Identification) and NPRS (Number Plate Recognition System) techniques in this paper. The proposed model will help to collect toll charges efficiently from all vehicle owners as per their road usage.

A Fuzzy Logic-Based Smart Traffic Management Systems

Traffic congestion is a serious problem in many developing countrieslike Egypt. In the presence of thetraditional traffic light system, it creates health risks, wastes time andfuel, and pollutes the air. Therefore, there is a big need for a smart trafficmanagement system. This study contributes in solving this problem byintroducing an artificial intelligence-based smart traffic light system usingfuzzy logic to ensure the smooth flow of traffic in cities. Research resultsindicate that smart traffic light management is very crucial in smart cities toreduce their carbon footprint to save the world and save energy. Other possibleapplication could be implemented with minor system upgrades such as Detectionand Management of traffic Congestion, Automatic Billing of Toll Charges,Automatic detection of speed limit Violation, Route planning, IntelligentInternet of Vehicles, and Prevention of Road Accidents. Four traffic lightapproaches (fixed-time, smart-time, fixed-time-fuzzy logic, andsmart-time-fuzzy-logic) are developed with different eight traffic scenarios.The four approaches are applied with two tools, the first tool is a realMarquette which consists of 4 roads with only one or two vehicles. The secondis a simulation software which consists of 4 roads with more than 100 vehiclesthrough 10 min. Many sensors such as (IR sensors, rain sensors, and LEDs tocontrol traffic light) are used to collect data and then the fuzzy algorithm isused to ensure the smooth flow of traffic in cities. The traffic data acquiredfrom the vehicles is fed into the proposed model to maximize the duration ofthe green light based on the road state. According to experimental results, theproposed smart fuzzy technique simulation software reduced the average waitingtime of the vehicles from 769 to 289 sec in heavy rain condition. It also reducedthe total time for all vehicles from 2490 to 1154 sec.

How do increases in electric vehicle use affect urban toll ring prices?

Numerous cities around the world have tried to internalize externality costs from road traffic by instituting charges for entering their city centers. The revenues collected from these charges are often redistributed to improve conditions for motorists, cyclists, pedestrians, and public transport. At the same time, many schemes allow for exemption of cleaner vehicles, which potentially reduces revenue collection. This paper assesses the effect of exempting electric vehicles from urban toll ring charges on the charge that is levied on conventional car drivers. Using panel data of Norwegian cities that have urban toll rings, I exploit regional variation in electric car adaption and find that owners of conventional cars pay 3.3 NOK (0.36 USD) more per passage due to the exemption. Moreover, I find that local governments that are fragmented or have a left-wing majority increase toll charges more due to the loss in revenue. As the majority of electric vehicle owners have above-average incomes, the exemption implies a distributional effect in which low-income groups pay the largest portion of the increased toll price.

Modeling the effects of government subsidy and regulation on BOT transport project contract design within contractible service quality

Government subsidy and regulation are frequently employed to encourage the private sector to participate fully in Build-Operate-Transfer (BOT) transport projects. Besides service charge, the service quality of BOT transport project (i.e., maintenance quality, toll service, operational monitoring, emergency management, safety management and so on) is also an important factor affecting the choice of users. This paper studies the optimal service quality decisions in both concession period (CP) and post-CP, in which we assume that the market demand is dependent on both service price and service quality. Firstly, in the absence of subsidy scheme, we derive the related players’ optimal decisions of toll charge, contractible service quality, project capacity and length of CP in the BOT contract design process. Secondly, we investigate how to design an optimal BOT transport project contract when the government subsidizes the private sector. Thirdly, we explore the effects of government regulation policies (i.e., price cap regulation and service quality floor regulation) on the BOT contract design. Finally, we make three extensions to further examine the impacts of the demand uncertainty, the risk-aversion attitude of private sector, the asymmetric cost information and the nonlinear demand function on the BOT contract design. From our model results, some policy implications are derived regarding BOT transport project contract design when the service quality is a fundamental contractible variable.

A HISTORICAL STUDY OF CONTRIBUTION OF MUGHALS FOR THE DEVELOPMENT OF THE TOURISM INDUSTRY IN JAMMU AND KASHMIR

The tourism literature of today frequently combines all of the Mughal contributions to Kashmir. Kashmir had a significant role in the magnificent Mughal Empire. The Valley was close to the Central Asian border in the Kabul area. Strong dynastic monarchs like Akbar, Jahangir, Shah-i-Jahan, and Aurangzeb ruled it. The region's trade and commerce were boosted by the Mughals' conquest because it put an end to the region's long-running domestic fighting, built a centralized government, did away with toll charges, and improved and widened its highways. The damaged economy of the province was also fixed by the maintenance of stability and the agriculture system changes. By taking a number of initiatives for the development of the tourism industry in Jammu and Kashmir, it protected the region's emperors from squandering their enormous wealth on the construction of temples, parks, and wellness resorts and inns, effectively transforming the territory into a "Heaven on Earth." Hence, this paper discusses the influence and contribution of the Mughals for transforming Kashmir a beautiful tourist spot of the world.

What if Air Quality Dictates Road Pricing? Simulation of an Air Pollution-based Road Charging Scheme

Road tolls serve various purposes, such as to refinance the road infrastructure or to regulate traffic. They are typically levied for the use of a freeway or the entire road network of a region or country. Toll charges may depend on the duration of use, the vehicle's emission class, the time of the day, the distance travelled, or the traffic volume. The primary objective of a few recent toll system deployments is to internalize externalities with respect to vehicle-caused air pollution. However, the air quality along the toll roads has so far not been considered to directly influence road usage prices. This article investigated by simulation the expected monetary expenditure for drivers and the traffic impact of applying a new distance and air pollution-based charging scheme in the metropolitan region of Berlin. The road usage charges were determined on a per-trip basis by taking the vehicle's emission class, the distance travelled, and the air pollution levels along the route into consideration. The simulation results indicate that it is beneficial for drivers to avoid areas of high air pollution in order to reduce the trip's total road usage charges. The average additional detour distance is thereby short in comparison to the route's length and the resulting additional emissions do not increase to the same extent as the number of detours, since detours are partly even shorter in terms of distance. The explorative analysis gives initial insights into the traffic effects of a charging scheme in which air pollution dictates road pricing.

A dynamic and deadline-oriented road pricing mechanism for urban traffic management

Road pricing is an urban traffic management mechanism to reduce traffic congestion. Currently, most of the road pricing systems based on predefined charging tolls fail to consider the dynamics of urban traffic flows and travelers' demands on the arrival time. In this paper, we propose a method to dynamically adjust online road toll based on traffic conditions and travelers' demands to resolve the above-mentioned problems. The method, based on deep reinforcement learning, automatically allocates the optimal toll for each road during peak hours and guides vehicles to roads with lower toll charges. Moreover, it further considers travelers' demands to ensure that more vehicles arrive at their destinations before their estimated arrival time. Our method can increase the traffic volume effectively, as compared to the existing static mechanisms.

Acceptance of RFID Toll Payment Method by Highway Users in Malaysia

Radio frequency identification (RFID) is a wireless tracking technology for data identification, capturing and analysis. It is used in numerous business applications to overcome the drawback of collecting data manually, such as data errors, time delay and high labour cost. RFID was introduced as an alternate toll charge payment method in Malaysia highways in 2018, and the government of Malaysia aims for a full implementation by end 2023. However, up to January 2022, only 10% of highway users switched to RFID. Hence, this study aims to assess highway users’ intention level on using RFID as toll payment mode. Additionally, the study also aims to evaluate the causal relationship between users’ perception on RFID payment mode and users’ intention to use RFID. The study views users’ perception based on modified TAM theory, which consist of perceived ease of use, perceived usefulness, perceived culture’s influence and perceived privacy and security. The study is quantitative based, structured questionnaire adopted from prior studies was distributed to the targeted population, which is class 1 highway users, and 176 responded. Data collected is normally distributed and statistically reliable. Hence, data was processed further with descriptive analysis and Pearson correlation test to address the research objectives. Finding from the research reveals that users’ intention to migrate to RFID payment mode is low, which suggested additional effort is required for the full implementation of RFID by end 2023. Additionally. Result of correlation test discloses that users’ perception on the ease of use and the usefulness are significantly associated with the intention to use RFID. However, the correlation of perceived culture’s influence, privacy and security with intention is weak and insignificant. The finding implies that highway operator should focus on addressing users’ anxieties and hesitation of using RFID in order to encourage more users to migrate to RFID. Additionally, the study also contributes to the domain new technology acceptance by the introduction of users’ acceptance model for RFID based on modified TAM theory.

Toll and subsidy for freight vehicles on urban roads: A policy decision for City Logistics

Toll roads constructed under public-private-partnerships (PPP) are very common around the world. Due to the high capital cost invested and high risks associated with subsequent returns, investors are concerned about future revenue. Charging high tolls from freight vehicles is a common practice, especially in urban areas. As a result, freight vehicles tend to divert from freeways (toll roads) to highways and arterial roads to minimize their costs, but this may cause more damage to infrastructure and environment, thus more costs for society and the environment. Consequently, developing an effective solution for toll charges for freight vehicles is a complex City Logistics problem involving multiple stakeholders with multi-objectives.This research investigates total costs (economic, social and environmental) associated with freight transportation based on existing toll structures for a toll road in Melbourne, Australia. Using a real case study, a step by step process was developed to illustrate the inefficiencies that exist in the present rigid toll charging mechanisms and how these inefficiencies can be corrected considering multi-stakeholder objectives and the overall impacts. This research identifies an optimal set of solutions that can be considered by decision-makers for implementation considering trade-offs between multiple management objectives. By considering subsidies, this research also identifies a good practical solution for minimizing the total cost of urban freight transportation while satisfying the investor needs. This policy decision is illustrated and related issues are discussed.

Simulation-Based Dynamic Traffic Assignment with Continuously Distributed Value of Time for Heterogeneous Users

The value of time (VOT) attribute is usually utilized to represent the trade-off between time and monetary expenses in transportation problems. A good representation of VOT is essential for evaluation of any road pricing scheme. Conventionally, in dynamic traffic assignment models, VOT is considered as either constant or finite discrete among travelers because of memory and computational limitations, which in turn could introduce bias in the results. This research explicitly models the individual bi-criteria dynamic user equilibrium (IBDUE) problem and presents a distinct simulation-based solution algorithm that enables individual-based traffic assignment within reasonable run time with a successful implementation of variable and continuously distributed VOT in a simulation-based dynamic traffic assignment package. Numerical analysis reveals that the constant and discrete VOT models tend to overestimate toll road usage compared with the continuous VOT model when the toll charge is low, and underestimate it when the toll charge is high, which reflects previous studies. In the meantime, an experiment on a real-world congestion pricing scheme demonstrates the capability of the proposed algorithm on evaluating flow-dependent pricing schemes.

IOT and Machine Learning based Automatic Toll Collection System

Automatic Toll Collection System is a wireless system which autmomatically collects the toll charge to vehicle at various toll booths in many metropolitian cities. It is very efficient and fast processing technology which will eliminate heavy congestion and over crowding of vehicles in cities. It accelerates hassle free toll collection system and traffic monitoring. This system detects the arrival of vehicle and then captures the image of number plate.

Determining Optimum Toll Charges for Freight Vehicles Considering Multi-Stakeholder Objectives in Urban Conditions

Abstract Trucks generate more externalities (environmental and social) than passenger vehicles, especially when trucks divert off freeways. When toll charges increase, such as the significant recent rise in Mel-bourne, Australia, more trucks tend to avoid toll roads (quality roads), generating more externalities. This diversion adds sub-stantial negative impacts on residents, the environment, and so-ciety. In fact, determining an optimum toll charge for freight ve-hicles is a crucial decision to be made by policymakers consid-ering socioeconomic aspects. The objective of this study is to develop an approach to design an optimal toll pricing scheme for multiclass vehicles, including specific truck types, consider-ing both direct costs and externalities. Additionally, the study developed an approach to identify the tradeoffs between vari-ous objectives of the designed scheme considering given con-straints. Nonlinear programming and user equilibrium techniques are used to model the problem, and the costs (direct costs and externalities) are quantified for Victoria, Australia. This nonde-terministic polynomial-time hard (NP-hard), nonconvex problem with nonlinear constraints was solved using the nondominated sorting genetic algorithm (NSGA) II. The model was applied to both a small-sized hypothetical network and a real network, with static demand conditions to illustrate differences between common toll schemes. Results are presented for Pareto-optimal solutions.

Cordon Pricing Scheme Based on Macroscopic Fundamental Diagram and Distance

To alleviate traffic congestion in key areas, such as city centers, this study proposes an optimal pricing strategy that is based on the distance that users travel in a given cordon. The proposed strategy is derived from the theory of the macroscopic fundamental diagram (MFD). In this strategy, a non-negative, nondecreasing, and nonlinear distance-toll function is defined by a piecewise linear approximation method. A bilevel programming model is then constructed on the basis of the toll charge function and the characteristics of the MFD. The upper model considers the overall operating efficiency of the system and aims to maximize the outflow of the road network. The lower model assumes that user route choice behavior complies with Wardrop’s first principle to formulate a user equilibrium model under a fixed demand. In view of the nonadditive property of path cost imposed by the nonlinear distance-toll function, the network transformation technique is used to realize the conversion between real networks and virtual networks. The Frank-Wolfe algorithm based on road segments is then used to solve the lower model. The verification of the reasonable feasibility of the pricing model and algorithm reveals that the implementation of cordon pricing schemes based on distance can make the outflow of the border area maintain the best level. Moreover, the obtained optimal charge function makes the system run efficiently. These results prove that the nonlinear optimal toll charge function is realistic and effective.