Toll Collection Research Articles

A study on automated toll collection: towards the utilisation of RFID-based system

The toll collection is becoming a major problem on the highways leading to large waiting queues. Toll gates installed on highways result in increased waiting time and fuel usage. In this paper, a study on automated toll collection system using radio frequency identification (RFID)-based system is presented, which provides fast identification of vehicles and toll collection. Using this system, the identification can be done just by slowing down the speed of the vehicle when it is passing from the toll plaza. The RFID reader scans the RFID tag or card and deducts the amount from it. The research analysed the system by proposing a mechanism and implementing an example scenario, which considered the random arrival of different vehicles. This technique is also compared with other existing mechanisms such as number plate recognition and barcode-based passes, which showed the need to utilise this technique for toll collection.

A Study on User Acceptable Road Pricing Policy for Toll Roads: A Case of Eethakota, India

User’s acceptability and perceptions are the important issues for the successful implementation of road pricing schemes. In a developing country like India, the toll collection is switching from Manual Toll Collection (MTC) to the Electronic Toll Collection (ETC) and Open Road Tolling. A better understanding of perceptions and acceptability on different road pricing schemes can help transport planners and decision makers to know the public support for road pricing schemes before and after implementation. A questionnaire based survey has been used to explore perceptions and acceptability of road pricing schemes such as High Occupancy toll (HOT), Dynamic Toll Pricing (DTP), Distance based pricing etc. For the present study, the sample of 550 respondents has been taken with the help of an online platform and face to face interview. The results show that about 41.18 percent of the users are willing to use the distance-based pricing scheme. The study developed multinomial logit model to analyse the acceptability of different pricing schemes. The results show that there are significant differences in user acceptability by the type of charging scheme proposed. HOT was most acceptable by users who perceive less travel time savings for using toll roads. The acceptability of DTP decreases for users who felt tolls are not an appropriate mechanism to fund roads. Number of toll booth passed is a significant parameter affecting acceptability of distance based pricing. In addition; socioeconomic variables also affect each of the pricing schemes. The signs of estimated parameters fit prior knowledge and are statically significant.The outcome of the present study will provide a reference for providing a users’ acceptable pricing scheme in India.

Highway Toll Collection Method for Connected Automated Vehicle Platooning Using Spatio-Temporal Grid Reservation

In the intelligent transportation system, the autonomous vehicle platoon is a promising concept for addressing traffic congestion problems. However, under certain conditions, the platoon’s advantage cannot be properly developed, especially when stopping for electronic toll collection (ETC) to pay the toll fee using the highway. This study proposes a software architectural platform that enables connected automated vehicles to reserve a grid-based alternative approach to replace current highway toll collection systems. A planned travel route is reserved in advance by a connected automated vehicle in a platoon, and travel is based on reservation information. We use driving information acquired by communication mechanisms installed in connected automated vehicles to develop a dynamic map platform that collects highway toll tax based on reserving spatio-temporal grids. Spatio-temporal sections are developed by dividing space and time into equal grids and assigning a certain road tax rate. The results of the performance evaluation reveal that the proposed method appropriately reserves the specified grids and collects toll taxes accurately based on a spatio-temporal grid with minimal communication time and no data package loss. Likely, using the proposed method to mediate driving on a one-kilometer route takes an average of 36.5 seconds, as compared to ETC and the combination of ETC and freeway road lane methods, which take 46.6 and 53.8 seconds, respectively, for 1000 vehicles. Consequently, our proposed method’s travel time improvements will reduce congestion by more effectively exploiting road capacity as well as enhance the number of platoons while providing non-stoppable travel for autonomous vehicles.

Forecasting regional short-term freight volume using QPSO-LSTM algorithm from the perspective of the importance of spatial information.

It is of great significance to accurately and efficiently predict expressway freight volume to improving the supervision level of the transportation industry and reflect the performance of transportation. Using expressway toll system records to predict regional freight volume plays an important role in the development of expressway freight organization work; especially, the short-term (hour, daily or monthly) freight volume is directly related to the compilation of regional transportation plans. Artificial neural networks have been widely used in forecasting in various fields because of their unique structural characteristics and strong learning ability, among which the long short-term memory (LSTM) network is suitable for processing and predicting series with time interval attributes such as expressway freight volume data. Considering the factors affecting regional freight volume, the data set was reconstructed from the perspective of spatial importance; we then use a quantum particle swarm optimization (QPSO) algorithm to tune parameters for a conventional LSTM model. In order to verify the efficiency and practicability, we first selected the expressway toll collection system data of Jilin Province from January 2018 to June 2021, and then used database and statistical knowledge to construct the LSTM data set. In the end, we used a QPSO-LSTM algorithm to predict the freight volume at the future times (hour, daily or monthly). Compared with the conventional LSTM model without tuning, the results of four randomly selected grids naming Changchun City, Jilin city, Siping City and Nong'an County show that the QPSO-LSTM network model based on spatial importance has a better effect.

The Influence of Figures in Warning Signs at the Manual Toll Station on the Lane Change Timing of Drivers in the Context of Virtual Reality of High‐Proportion ETC Vehicles

The increase of ETC (electronic toll collection system) vehicles on expressways has changed the proportion of ETC/MTC (manual toll collection system) lanes at toll stations. Based on a driving simulator, three toll gate lane warning sign schemes (scheme for present situation, MTC guidance scheme, and arrow + MTC guidance scheme) were proposed in this study. Driving simulation experiments were conducted to study the influence of figures in warning signs at the manual toll station on the lane change timing of drivers. It was found that the addition of arrows to the warning signs can significantly shorten the response time and guide the driver to make lane change decisions earlier to reduce the congestion between MTC vehicles and the mainline ETC vehicles at the toll plaza, thereby improving the traffic capacity and safety.

A study on automated toll collection: towards the utilisation of RFID-based system

A study on automated toll collection: towards the utilisation of RFID-based system

Государственная система «Платон»: от неприятия к позитивному мультипликативному эффекту в строительстве и эксплуатации автомобильных дорог

The experience of the first five years of operation of the “Plato” satellite toll collection system (“fee per ton”) to compensate the damage caused to federal public highways by vehicles with a permitted mass of more than 12 tons transiting along them is given a consideration. The reasons for the introduction of this system are provided. The most significant interim results of the system are listed. An overview of cargo carriers’ critical comments and claims on this system is given, possible growth points are indicated. Special attention is paid to the most important result of functioning of the “Plato” system, which consists in the multiplicative effect of the Russian economy, which will increase over time.

Performance comparison of various techniques for automatic licence plate recognition systems

Automatic licence plate recognition (ALPR) system is direly needed nowadays for various applications like toll collection system, parking system, identification of stolen cars, incident management, electronic payment service, electronic customs clearance of commercial vehicle, automatic security roadside inspection, security monitoring in a car, emergency notification, and personal security, etc. An automatic licence plate recognition system performs three important processing steps on the input image, i.e., extraction, segmentation, and recognition. A number of algorithms are developed for these steps in the last few years. The result of which is significant improvement in the licence plate recognition. The aim of this study is a survey of the existing techniques for licence plate recognition. In this paper, a number of existing techniques for automatic licence plate recognition are presented and their benefits and limitations are discussed. Further, the paper also foresees the future scope in the area of automatic licence plate recognition system.

Dashboard for performance monitoring of toll stations

Business Intelligence (BI) is a modern approach to the processing of large amounts of data and their transformation into quality information. Dashboards are a type of BI application that improves the decision-making system by giving importance to cognitive and human perception abilities. The way of presenting and visualizing data and information on the dashboard provides better, more reliable and faster decision-making. The paper presents a dashboard for performance monitoring of toll stations on the highway, which allows the analysis of traffic flows and engaged resources at the level of one day. Performance includes various characteristics that describe the functioning of the process and activities and can be obtained for each station in the toll collection system. The designed dashboard enables the display of business performance, quality data visualization, fast and clear inference about the operation of the system, and a good basis for decision making.

Dashboard for performance monitoring of toll stations

Business Intelligence (BI) is a modern approach to the processing of large amounts of data and their transformation into quality information. Dashboards are a type of BI application that improves the decision-making system by giving importance to cognitive and human perception abilities. The way of presenting and visualizing data and information on the dashboard provides better, more reliable and faster decision-making. The paper presents a dashboard for performance monitoring of toll stations on the highway, which allows the analysis of traffic flows and engaged resources at the level of one day. Performance includes various characteristics that describe the functioning of the process and activities and can be obtained for each station in the toll collection system. The designed dashboard enables the display of business performance, quality data visualization, fast and clear inference about the operation of the system, and a good basis for decision making.

Total Solution For Smart Traffic and Toll Roads Management in Indonesia


 
 
 
 
 
 The Ministry of Public Works and Public Housing has the task of carrying out government affairs in the field of public works and public housing to assist the President in administering the state government. One of the mandated functions in carrying out this task is to formulate and implement policies in the field of road administration in accordance with the provisions of laws and regulations, including the regulation of toll roads in Indonesia in accordance with Government Regulation No. 15 of 2005 concerning Toll Roads. The toll road is one of the vital means needed to increase efficiency in public services, logistics and industry which leads to economic efficiency. According to data released by the World Bank in 2019, losses due to traffic jams in Indonesia amounted to USD 4 billion, equivalent to an estimated IDR 56 trillion, more than that due to queuing at toll gates there is potential for losses for all business entities. To
 
 
 
 
 
 
 overcome this problem, Indonesia is preparing to implement a non-stop (touchless) toll payment system on the Multi Lane Free Flow (MLFF) system using RFID-based ETC (Electronic Toll Collection) Total Solution technology and the transaction process is carried out through a special application that can be accessed from the Internet. Integrate all departments with an IoT (Internet of thing) system. This payment system can eliminate the GTO function of toll entry and exit gates. In addition, the MLFF system using RFID-based ETC will recognize and identify vehicles and users. In addition to the RFID-based ETC system to increase the productivity and effectiveness of traffic management on toll roads, maintenance of toll roads and bridges is also very vital, therefore detecting road surface damage directly using sensors, CCTV cameras and UAV unmanned aerial vehicles. (Unmanned Aerial Vehicle) which has the advantages of high.

Quad-Port Multiservice Diversity Antenna for Automotive Applications.

A quad-element multiple-input-multiple-output (MIMO) antenna with ultra-wideband (UWB) performance is presented in this paper. The MIMO antenna consists of four orthogonally arranged microstrip line-fed hexagonal monopole radiators and a modified ground plane. In addition, E-shaped and G-shaped stubs are added to the radiator to achieve additional resonances at 1.5 GHz and 2.45 GHz. The reliability of the antenna in the automotive environment is investigated, with housing effects taken into account. The housing effects show that the antenna performs consistently even in the presence of a large metal object. The proposed MIMO antenna has potential for various automotive applications, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-everything (V2X), intelligent transport system (ITS), automatic vehicle identifier, and RFID-based electronic toll collection.

Enhanced Dynamic Spectrum Access in UAV Wireless Networks for Post-Disaster Area Surveillance System: A Multi-Player Multi-Armed Bandit Approach.

Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With the aid of Unmanned Aerial Vehicles (UAVs), a post-disaster surveillance system is implemented using Cognitive Radio Network (CRN). UAVs are distributed in the disaster area to capture live images of the damaged area and send them to the disaster management center. CRN enables UAVs to utilize a portion of the spectrum of the Electronic Toll Collection (ETC) gates operating in the same area. In this paper, a joint transmission power selection, data-rate maximization, and interference mitigation problem is addressed. Considering all these conflicting parameters, this problem is investigated as a budget-constrained multi-player multi-armed bandit (MAB) problem. The whole process is done in a decentralized manner, where no information is exchanged between UAVs. To achieve this, two power-budget-aware PBA-MAB) algorithms, namely upper confidence bound (PBA-UCB (MAB) algorithm and Thompson sampling (PBA-TS) algorithm, were proposed to realize the selection of the transmission power value efficiently. The proposed PBA-MAB algorithms show outstanding performance over random power value selection in terms of achievable data rate.

The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data

To overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of expressways is proposed. Firstly, the characteristics of the ETC gantry data are analyzed, and then data are cleaned and reconstructed, after which an algorithm is proposed for constructing a vehicle travel speed data set. Secondly, the speed feature vector model of the road section is established by taking the relationship among the speed distribution feature, time domain feature, and the maximum speed limit of the road section into consideration. Then, a data supplement algorithm is constructed to solve the problem of the imbalance of data samples. Finally, the combined GC-XGBoost classification algorithm is used to train and learn the potential speed limit features, and it is verified through the Fujian Provincial Expressway ETC data and the speed limit information provided by the Fujian Traffic Police. The result shows that the accuracy of the method in the recognition of the maximum limited speed information of the expressway is 97.5%. Compared with the traditional limited speed information recognition and extraction methods, the proposed approach can identify the maximum limited speed information of each section of the expressway more efficiently. It can also accurately identify the dynamic change of the maximum limited speed information, which is able to provide data support for intelligent expressway management systems and map providers.

Development of an adjustable step toll scheme in compliance with expected effects of queuing reduction for the Suez Canal

The widening and deepening of the Suez Canal were completed in 2016, and this enabled most large-sized ships to cross the canal. Because the demand for the canal has continued to increase, the queuing problem at the entrance of the canal would be anticipated to be more serious. In the existing literature, an optimal time-varying toll scheme has been established for the Suez Canal to eliminate the queuing phenomenon that many ships wait in line for entry into the canal. However, this toll scheme might be difficult to implement because the toll rate continuously changes according to the arrival time of the ship. To find an alternative, we calculate all possible combinations of the area ratios of the optimal time-varying toll triangle to its inscribed step toll rectangles to develop an adjustable step toll scheme. The developed toll scheme could achieve all expected effects of queuing reduction that could not be accomplished by other toll schemes in the existing literature. Moreover, the regularities in values of toll amounts and the start and end charging times that we have presented under the adjustable n-step toll scheme (n = 1,2,3, …) could be conducive to the implementation of the electronic toll collection system. Finally, we simulate the implementation of the adjustable step toll scheme for the Suez Canal and provide practical suggestions for the canal authorities.

The impact of large vehicles on the traffic performance of toll plazas, a case at Hochiminh City

In recent years, toll stations are bottlenecks creating queues during rush hours on the highway, accompanied by manual toll collection, leading to traffic congestion, increasing travel time, and economic losses. This paper focuses on studying the influence of large vehicles, such as buses, trucks, and trailers, one of the causes of long queues, leading to reducing traffic performance of toll plaza. The Hanoi highway toll plaza was selected as the case study, the station has a very large traffic volume, especially large-sized vehicles entering/exiting Hochiminh city. The research results by using traffic simulation VISSIM show that the large-sized vehicle component greatly affects the queue lengths at the station, the suggestion of applying the electronic toll collection (ETC) method is considered the best potential solution to this problem.

ETC-Oriented Efficient and Secure Blockchain: Credit-Based Mechanism and Evidence Framework for Vehicle Management

An electronic toll collection (ETC) system is one of the most important parts of an intelligent transportation system (ITS), but existing ETC systems are not efficient and have vehicle fee evasion complications. Owing to the traceability and tamper resistance of a blockchain, the combination of a blockchain and ETC system is a feasible way to solve the above problems. However, traditional blockchain (e.g., Bitcoin and Ethereum) has high power consumption and low efficiency. Hence, it cannot be used in ETC systems with high throughput and is not suitable for power-constrained Internet of Things (IoT) devices. In this study, therefore, we propose a blockchain architecture for the ETC system. To curb vehicle fee evasion behavior, thereby reducing the economic loss caused, we propose a vehicle behavior management mechanism based on credit value. Furthermore, to reduce the burden of storage and build a chain of evidence for auditing purposes, we propose an evidence chain framework. To protect the data security in the transaction process, we designed a data protection method to encrypt the transaction data. Additionally, this system is based on an open-source alliance blockchain framework called Hyperledger Fabric, which is more in line with the current application scenarios of ETC systems. We implemented the system on a Raspberry Pi and carried out simulations. The comprehensive evaluation results and analysis show that the system effectively reduces the number of illegal acts, completes the evidence inspection, and improves the security of the data.

Assessment of Changes in Toll Fares in Conditions of Increased Traffic Load

The purpose of the study is to assess changes of toll fares used on toll collection points. When toll road is operating in an urban environment, the operator is inevitably faced with the need to adapt intelligent transport system to the conditions of an ever-increasing volume and changing composition of the traffic. Such changes have a direct impact on the capacity of the toll road, in particular at toll collection points. The conducted research is aimed at analyzing the method of reducing the traffic load at the toll collection points during peak hours by making changes to the toll fares aimed at uniform distribution of traffic flow throughout the day. As an example, a toll collection point on the main road direction of the Western High-Speed Diameter toll road was chosen.Materials and methods. A discrete-event simulation model developed in the AnyLogic software was used to assess the quality of operation and throughput of the toll collection point. The software has a sufficient level of detail to reproduce the operation of the toll collection system, and allows managing all the necessary parameters of the system and traffic flow. Analysis of the data obtained from the simulated model experiments was carried out using the statistical package R. Results. As part of the study, the operational characteristics of the toll collection point, in particular its threshold capacity, were determined, and, if it was exceeded, the length of the emerging queue was determined. Taking into account the operator’s risks arising from the formation of a traffic congestion, an approach was proposed to change the toll fare policy of the toll road by using a more flexible fares based on dividing the day time fare into several time intervals and using increasing coefficients for toll fare when paying for travel during peak hours. Using the example of toll booth of the Western High-Speed Diameter, the increasing coefficients of the cost of travel at a rush hour were considered, and the risks of reducing the operator’s income from toll collection were assessed.Conclusion. Based on the results obtained, an assessment of the effectiveness of the application of measures to change the existing toll fare policy, aimed at optimizing the traffic flow of a toll road, can be carried out. In addition, such an analysis can be used to assess the investment attractiveness of a project, develop a toll fare policy, increase income and other similar tasks. Further research can be aimed at increasing the economic indicators of toll road projects, and developing additional mathematical tools used in the formation of toll fare policy.

Selection of the Optimal Toll Collection System for the Purposes of Sustainable Development of Transport in the Republic of Srpska

Transport system has multiple interactions and multidimensional effects on the environment, by way of, amongst other, land acquisition and urban pollution; on economic development with regard to the GDP growth; as well as on social equity in terms of access, quality of life and health of population. This paper considers the possibility of introducing toll collection in the Republic of Srpska. The goal of the developed model is to increase revenue, which could be directed to the sustainable development of transport in the Republic of Srpska. The selection of a toll collection system has been made taking account of: economic, traffic, technical, organizational and exploitation criteria. Multiple-criteria approach has been applied together with the Analytic Hierarchy Process.

Blockchain Based Intelligent Transport System

Blockchain technology is widely studied in these days and has vital role in the ITS and Vehicular network. Intelligent Transport System (ITS) have resolved several issues of transportation like congestion, electronic toll collection, traffic light cameras, traffic updates, and environment forecasting. The vehicular network is the ever-increasing network it is not only facilitates us but also brings new challenges with it. The mobile nature of vehicular networks it is very important to collect and broadcast information of traffic events in real-time. A little delay to broadcast important information or deciding on this information can cause a serious situation in the mobile vehicular network. Moreover, malicious vehicles in the network broadcasting false information about these traffic events cause a disturbance in the network. In large-scale scenarios, the transmission of malicious messages offers a lot of danger to the system. They can wrongly claim the roads and provide false information about the incident. These traffic events can be life-threatening and cause unwanted situations like accidents, wastage of time and other resources. Therefore, it is very much important to provide real-time information on recent traffic events and real-time authentication of vehicles that broadcast information in the network. Traditional studies are unable to solve these security issues and contain a single point of failure issue. These studies are centralized and dependent on a single higher authority. Moreover, they have serious security concerns that are harmful for vehicular network. Moreover, any vehicles are unwilling to share their private information while broadcasting information about traffic events because they are strangers to each other. And if a vehicle does not want to share its private information like name, id, etc. It is not possible to authenticate this vehicle and manage trust in the network. It means that it is very crucial to prevent vehicles to broadcast wrong information in the network while preserving their privacy at the same time. Therefore, there is a need to authenticate vehicles and manage trust in the network while preserving their privacy simultaneously. Blockchain can offer better solution to solve these issues due to its secure distributed environment and features that ensure immutability about actions. The purpose of this report is to provide real-time security and privacy in the network. It is also ensured that vehicles get real-time authenticated information about traffic incidents from legitimate vehicles while simultaneously preserving their privacy. It means that only authenticated and legitimate entities (vehicles) can participate in vehicular network and privacy of both sender and receiver is secured in the network. Details of conducted experiments are given, and shreds of evidence are provided to evaluate the performance of architectures for authentication and trust management. The shreds of evidence show that these blockchain-based systems can solve security and trust issues more effectively.