Research on evaluation of expressway operation status based on vehicle trajectory traceability

Electronic Toll Collection (ETC) system is an important part of modern intelligent transport system, which plays an important role in intelligent car parks and congestion charging. Electronic Toll Collection (ETC) system includes automatic vehicle identification system and electronic billing system. The automatic vehicle identification system includes three parts: automatic vehicle identification (AVI), automatic vehicle model identification (AVC) and inspection system (ES).The application of ETC in intelligent car parks and congestion charging also includes automatic vehicle identification system (automatic vehicle identification, automatic vehicle model identification and inspection system) and electronic billing system. In intelligent car parks, ETC technology achieves fast and accurate automatic toll payment by automatically identifying the ETC tags carried by vehicles, which greatly improves the efficiency of car parks and reduces the queuing and waiting time due to manual toll collection. In terms of congestion charging, ETC technology provides an effective means to implement congestion charge collection. By setting up ETC toll lanes in core urban areas or busy road sections, the system can automatically record the information of the vehicles passing through and carry out toll settlement, thus realising dynamic toll collection according to the degree of congestion and the frequency of vehicle use. This congestion charging strategy aims to regulate urban traffic flow through economic means, alleviate traffic congestion and promote the sustainable development of urban transport. Although China's theoretical research on congestion charging, has been relatively mature, but affected by a variety of factors, no city has yet to start the implementation of congestion charging, the lack of experience in practice. Singapore will not stop the car charging system (ETC) technology successfully applied to urban congestion charging and intelligent car parks, ETC system in intelligent car parks and congestion charging application, help to promote the development of urban transport to a more intelligent, green direction. China can learn from the successful experience of foreign countries and apply it to its own intelligent car parks and congestion charging. This paper introduces the basic principle of ETC, discusses the research progress of ETC in terms of technical characteristics, and analyses the application scenarios of ETC in intelligent car parks and congestion charging. By examining the opportunities offered by Electronic Toll Collection (ETC) systems in smart car parks and congestion pricing, this study aims to delve into the transformative impacts of Electronic Toll Collection (ETC) systems on intelligent mobility and contribute to the sustainable development of intelligent mobility.

Highway vehicle emissions can result in adverse health problems to nearby residents and workers, especially during traffic congestion. In response, the policy to implement electronic toll collection (ETC) has helped alleviate traffic congestion, as compared to manual toll collection (MTC) and has led to reduced air pollution and improved public health. However, the effect of ETC in reducing particulate matter polluting the air is not well understood, especially in the ultrafine particle (UFP) range (particle diameter <100 nm). To the best of our knowledge, this is the first study to investigate how ETC affects the traffic pattern and air quality, especially UFP and PM2.5. We selected a site in Tainan, Taiwan, and measured UFP and PM2.5 concentrations before and after the construction of the ETC system. The computed traffic volumes during peak travel periods (7:00 AM to 9:00 AM and 4:00 PM to 6:00 PM) respectively, accounted for approximately 23-25% and 14-18% before and after the implementation of ETC, indicating that peak traffic volumes were more homogeneous after ETC. Moreover, the results indicate that the full implementation of ETC can help reduce UFP number concentrations and PM2.5 mass concentrations in the highway downwind area by 4 × 103 #/cm3 and 20.5 μg/m3, respectively. After the full implementation of the ETC, significant reductions in both the UFP number concentration and PM2.5 mass concentration were seen. Furthermore, excessive lifetime cancer risks (ELCR) from exposure to PM2.5 and UFP together were reduced 49.3% after the implementation of the ETC. Accordingly, ETC not only helps alleviate traffic congestion but also reduces traffic emissions and lifetime cancer risk for people living or working near highways.

The environmental outcome of the Electronic Toll Collection (ETC) system is an important aspect in evaluating the impacts of the ETC system, which is influenced by various factors including the vehicle type, travel speed, traffic volume, and average queue length of Manual Toll Collection (MTC) lanes. The primary objective of this paper is to develop a field data-based practical model for evaluating the effects of ETC system on the fuel efficiency and vehicle emission. First, laboratory experiments of seven types of vehicles under various scenarios for toll collection were conducted based on the Vehicle Emissions Testing System (VETS). The indicator calculation models were then established to estimate the comprehensive benefit of ETC system by comparing the test results of MTC lane and ETC lane. Finally, taking Beijing as a case study, the paper calibrated the model parameters, and estimated the monetization value of environmental benefit of the ETC system in terms of vehicle emissions reduction and fuel consumption decrease. The results shows that the applications of ETC system are expected to save fuel consumption of 4.1 million liters and reduce pollution emissions by 730.89 tons in 2013 in Beijing.

To evaluate the effect of policy on province-wide toll discount for electronic toll collection (ETC) trucks, and to clarify the influence of trucks registered in other provinces on the toll discount flowed back to the local enterprises, we use structured query language server (SQL Server) database technology to process the toll collection data on expressway network, and propose an algorithm of recovery rate for the explanatory variables of toll preference, and verify the feasibility of the algorithm is by a case study. The results show that the recovery rate of the study case is 43.38% when there is an 85% discount on ETC truck toll in 2019, and 52.77% of the 56.62% toll discount outflowed from the case studied is generated by the trucks registered in other provinces according to a conservative estimate. Among them, the proportion of the toll discount of trucks registered in other provinces with 6 axles accounts for 77.29%, which is the root of toll discount loss. Although the traffic number across the province is not large, the toll discount is rather large owing to the long distance and heavy load. The recovery or loss of toll discount concentrates in the trucks with 2 axles, 4 axles and 6 axles, and trucks with 6 axles accounting for the largest proportion. This paper provides a reliable analysis basis for the accuracy of the differential charging policy on expressway, and promotes the rapid development of transportation economy.

Laser range finder technology-based three-dimensional vehicle profile and size measurements are useful for vehicle detection and classification in electronic toll collection (ETC). First this paper briefly makes a comparative study of conventional vehicle detectors employing range measurement technologies to summarize the requirements for vehicle classification in ETC. Secondly two overseas laser range vehicle profilers are presented as typical examples of the ETC application. Newly developed laser range finder to classify vehicles for domestic ETC is also introduced. The developed sensor successfully acquired the shapes of vehicles in detail and measure the both of height and width of them with sufficient accuracies for toll collection at actual tollgate.

Since the resumption of highway tolls in China on May 6, 2020, the national highway network toll collection system based on electronic toll collection (ETC) has been basically stable. With the rapid rise of ETC users, ETC-inefficient transactions increased, which brought great challenges to highway operation services. Based on a full investigation, this paper analyzes the methods and cases of applying vehicle road cooperation to improve the efficiency of highway toll operation service, puts forward the key work direction to improve the highway operation service level in the future, and discusses the implementation idea of constructing vehicle cooperation service system based on a ETC system.

Research and design of simulation and verification system of intelligent expressway based on ETC big data

Influences of traffic volumes and wind speeds on ambient ultrafine particle levels—Observations at a highway electronic toll collection (ETC) lane

This work enhances the machine-to-human communication between electronic toll collection (ETC) systems and drivers by providing an AM broadcast service to deployed ETC systems. This study is the first to show that ultra-high radio frequency identification signals can be received by an AM radio receiver due to the presence of the nonlinearity effect in the AM receiver. Such a phenomenon allows the development of a previously infeasible cross-technology and cross-frequency communication, called Tagcaster, which converts an ETC reader to an AM station for broadcasting short messages (e.g., charged-fees and traffic forecast) to drivers at tollbooths. The key innovation in this work is the engineering of Tagcaster over off-the-shelf ETC systems using shadow carrier and baseband whitening without the need for hardware nor firmware changes. This feature allows zero-cost rapid deployment in the existing ETC infrastructure. Two prototypes of Tagcaster are designed, implemented, and evaluated over four general and five vehicle-mounted AM receivers (e.g., Toyota, Audi, and Jetta). Experiments reveal that Tagcaster can provide good-quality (PESQ>2) and stable AM broadcasting service with a 30 m coverage range. Tagcaster remarkably improves user experience at ETC stations, and two-thirds of volunteer drivers rate it with a score of 4+ out of 5.

This paper conveys the theoretical perspectives of sustainable industrial systems of On board Unit (OBU) in Electronic Toll and its transportation industry. It proposes kernel density analysis of artificial intelligence approach to industry 4.0. Regulation for technology developments in artificial intelligence and robotics are deemed as one of beneficial yet structurally neglected domain. This domain refers to human perspective on augmenting automation. This regulation was emphasized in 2017 by the European Parliament report level. The mentioned regulation comprises attention in Indonesia transportation industry indicating positive innovation domains in term of safeguards and regulations are needed. Prior, current and posterior trends of the Internet of Things, Industry 4.0, and Physical Internet constitutes the results of the data development and understanding. Therefore, the topical framework of automation and robotics are triggered by these developments. The mention triggers has impacted the most important wide range implementation of industries in the future. Electronic Toll Collection (ETC) system is 40% higher in cost efficiency than Manual Toll Collection (MTC) system. In this situation, Indonesian government has already issued full swing policy implementation on non-contact freeway toll collection system by the end of 2018. Structural Equation Modelling (SEM) is capitalized to proceed to data processing. Result of this research shown the driver's characteristics that significantly affect willingness to pay an on-board unit are education expenses, distance and frequency. The average value of driver willing to pay an on-board unit was 225.781 IDR and factors that affecting values of the willingness to pay an on-board unit are expenses and distance.

Electronic Toll Collection (ETC) serves a major function in an Intelligent Transportation System (ITS). Recently, ETC has been widespread and prevalent within our national ITS infrastructure construction. However, with the advanced application of new technologies in ETC, people have to face lots of privacy issues. Based on privacy concerns and issues, the paper first analyzes privacy risks in ETC system and then conducts research on technical solutions to and legal strategies for privacy protection. Finally, the paper proposes suitable suggestions for solving privacy issues and risks in our domestic ETC system.

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.

RFID Electronic Toll Collection (ETC) systems have been deployed worldwide to improve toll collection efficiency, reduce road congestion, increase road safety and traveler satisfiability. However, the use of such systems raises a number of security and privacy issues due to unauthorized reading and relay attacks. Unfortunately, currently deployed or proposed solutions targeting these attacks often fail to satisfy the constraints and requirements of the underlying RFID toll road application in terms of (one or more of) efficiency, security, and usability. In this paper, we report our initial work toward a new approach, one that utilizes sensing technologies, to tackle the problems of unauthorized reading and relay attacks in RFID ETC systems by considering efficiency, security, and usability simultaneously. In our approach, on-board tag sensors are used to collect contextual information (location, speed) about the tag. Such contextual information is then used to design context-aware selective unlocking mechanisms for toll cards such that they can selectively respond to reader interrogations and thus minimize the likelihood of unauthorized reading and relay attacks. The premise of our work is a current technological advancement that enables many RFID tags with sensing capabilities.

Traffic simulation models are used to enhance planning, design, operation, and management of transportation facilities. A discrete-event stochastic object-oriented microscopic simulation model is presented that was specifically developed to evaluate the operational performance of toll plazas. Traffic behavior is represented using a set of mathematical and logic algorithms that control the conflicts among vehicles within the toll plaza area. Modified versions of car-following and lane-changing algorithms and a new toll-lane selection algorithm are integrated into this new model to simulate traffic operation at toll plazas. The model output includes measures of effectiveness (MOEs) that can be used to evaluate the performance of existing and future individual toll lanes and the entire toll plaza system. Real-world data collected at the busiest toll plaza in the Orlando–Orange County Expressway Authority system were used to validate the developed model. Statistical tests indicate that there is no significant difference at the 95 percent confidence level between MOEs obtained from the model and those collected in the real world. Sensitivity analysis of market penetration of the electronic toll collection (ETC) system indicates that an increase in ETC subscription rate improves the efficiency of toll plaza operation. The benefits of ETC depend on the specific plaza configuration. One of the most interesting results of this study is that for all plaza configurations simulated with manual payment lanes operating over capacity, total plaza delay can be reduced by half if only 10 percent of the users switch from manual payment lanes to ETC lanes.

The authors present a novel approach to modeling a toll plaza and evaluating a number of possible scenarios for an ETC (electronic toll collection) equipped toll plaza. Utilizing a spreadsheet based demand/capacity model (which was validated and created in a relatively short time frame) rather than using the traditional complex simulation language, the effectiveness of ETC technology was evaluated. For each scenario the modeling effort showed that the implementation of ETC technology should result in an improved toll plaza operation. For the majority of the toll plaza users considered the results from the modeling effort showed that, by implementing ETC technology, service levels would improve and in most cases, significantly so. >