Computer vision based vehicle detection for toll collection system using embedded Linux

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.

Because the highway has become more and more important in modern road network and the traditional manual toll collection has clearly exposed its weakness, non-stop automatic toll collection is now imperative in highway systems. With the advent of the intelligent transportation systems (ITS), the establishment of electronic toll collection system (ETC) by using of computer technology, electronic technology and modern communication technology, etc, to provides some solutions to the traffic jam, delay and some other problems, can radically enhance the safety and efficiency of road operation and achieve safe road traffic environment. This article has deeply analyzed the networking toll collection management system, including network structure, system framework, and safty and reliability guaranty of the system, etc. The program will provide a reference to non-stop toll collection system of the highway.

Abstract: The traditional systems for toll collection are plagued with various problems, including traffic buildup at toll booths, long waiting time on users, and administrative costs. This research proposes a GPS-Based Toll Collection System that would help to solve these problems by using better location-based technologies for the automatic tolling of vehicles. This system consists of a combination of a GPS receiver, a microprocessor, and a battery inside the vehicle. It can track the vehicle's course in real-time and the position where the vehicle enters or exits the toll road zone is automatically detected and the toll amount calculated per distance traveled using pre-defined rates or dynamic pricing models. The user-friendly web interface allows vehicle owners to register their vehicles, maintain a digital wallet, and view transaction histories. The deducting toll is automatic without the need for any toll booth physical interaction, efficiently accelerating the toll collection process, thereby causing less traffic congestion, more throughput, and substantial operational cost reduction in staff and manual handling. Apart from better user convenience and operational benefits, the automated, highly accurate, and transparent toll collection system assures equal opportunities for all persons entering the national highways by way of toll. This paper discusses the architecture of this system, major components, critical challenges faced during its implementation, and its potential impact on the transport sector. Comparison of the proposed GPS-based system with traditional tolling methods reveals advantages such as lower maintenance costs, improved scalability, and real-time data processing. It also examines security protocols employed to ensure data privacy and fraud prevention. Lastly, the study concludes with an account of the proposed improvements and the possibility of the wide-scale deployment of the system in furtherance of smarter and more sustainable transportation infrastructure development

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.

Service time thresholds at barrier-operated freeway exit toll booths

Methodologies for quality assessment of highway operators based on governance best practices with emphasis on toll collection ecosystem

The present manual toll collection system of Sri Lankan expressways is expected to be inadequate to serve the forecasted traffic demand on most interchanges. High waiting times at the manual toll booths would directly affect the expressway user delay and the level of service. Therefore, an efficient tolling system will have to be introduced. This study is focused on developing a methodology to evaluate the operational improvements of using electronic toll collection incorporating the traffic characteristics of Expressways in Sri Lanka. A micro-simulation method using a commercially available software; PTV Vissim, was adopted to conduct a scenario analysis for a forecasted traffic demand at the Kottawa interchange as a case study. A calibrated sample model was developed and its simulation results show that the electronic toll collection system can reduce the average per vehicle delay and increase the toll plaza capacity up to 50% during peak hour if the proper toll plaza configuration is provided. The findings of the study are beneficial to toll station operators as well as for planning for toll station upgrading by assessing its optimum capacity.

The European Electronic Toll Service (EETS) was created in 2004 with the aim of ensuring interoperability among the existing electronic toll collection (ETC) systems in Europe. However, the lack of cooperation between groups of stakeholders has not made possible to achieve this goal ten years later. The purpose of this research is to determine the better way to achieve interoperability among the different ETC systems in Europe. Our study develops a review of the six main ETC systems available worldwide: Automatic Number Plate Recognition (ANPR), Dedicated Short-Range Communications (DSRC), Radio Frequency Identification (RFID), Satellite systems (GNSS), Tachograph, and Mobile communications tolling systems. The research also provides some insight on different emerging technologies. By focusing on different operational and strategic aspects offered by each technology, we identify their main strengths, weaknesses, opportunities and threats and makes different recommendations to improve the current framework. The research concludes that given the diversity of advantages and inconveniences offered by each system, the selection of a certain ETC technology should also take into account its potential to overcome the weaknesses in the current ETC framework. In this line, different policy recommendations are proposed to improve the present ETC strategy at the EU.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3186

[EN] The European Electronic Toll Service (EETS) was created in 2004 with the aim of ensuring interoperability among the existing electronic toll collection (ETC) systems in Europe. However, the lack of cooperation between groups of stakeholders has not made possible to achieve this goal ten years later. The purpose of this research is to determine the better way to achieve interoperability among the different ETC systems in Europe.
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\nOur study develops a review of the six main ETC systems available worldwide: Automatic Number Plate Recognition (ANPR), Dedicated Short-Range Communications (DSRC), Radio Frequency Identification (RFID), Satellite systems (GNSS), Tachograph, and Mobile communications tolling systems. The research also provides some insight on different emerging technologies. By focusing on different operational and strategic aspects offered by each technology, we identify their main strengths, weaknesses, opportunities and threats and makes different recommendations to improve the current framework.
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\nThe research concludes that given the diversity of advantages and inconveniences offered by each system, the selection of a certain ETC technology should also take into account its potential to overcome the weaknesses in the current ETC framework. In this line, different policy recommendations are proposed to improve the present ETC strategy at the EU.

Automatic license plate recognition is a technology that relies on optical character recognition methods used on images for reading license plate text. These techniques are, in general, used with image processing techniques, whether the system is composed of them entirely or in addition to deep learning techniques and neural network models. Such a system can be used by CCTV cameras, smart cameras, and other such devices, for tasks in areas like law enforcement, toll collection systems, or parking lot ticket systems. These systems can be used to capture images, locate license plates and recognize the text from the license plate. Depending on the region, post-processing can be conducted to further refine the recognized text based on a set of predefined rules, such as the position of letters and numbers in the license plate string. This work aims to create an automatic license plate recognition system with the use of image processing techniques, mainly from the OpenCV python library. The system will attempt to recognize license plate text from vehicles parked in parking lots. This can be useful for people, who do not remember the place where they parked their vehicle, or in other areas such as law enforcement. For large parking lots, there are generally camera systems already in place, in this case, the system should be able to work with multiple angles and views of the parking lot to get results with the highest accuracy ratings.

실시간 자료를 반영한 통행시간 예측 기법은 다양하지만 관련 연구 검토 결과 과거이력데이터가 충분하다면 타 모형에 비해 K 최대근접이웃(K-Nearest Neighbors)의 정확도가 우수하므로 본 연구에서는 이에 대한 적용 방법 도출 및 가능성 평가를 목적으로 한다. 본 연구에서는 KNN의 입력 자료로 TCS 교통량 및 DSRC 구간통행시간의 실시간 및 과거 이력자료, 경로통행시간 이력자료를 활용하였다. 통행시간 예측치는 TCS 교통량 및 DSRC 구간통행시간의 실시간 자료와 유사한 경로통행시간을 탐색한 후 이를 가중평균하여 산출하였다. 예측 기법을 적용한 결과 DSRC 구간통행시간의 가중치가 증가할수록 정확도는 증가하였으며, 이는 실시간 교통상황 변화를 DSRC 구간통행시간이 잘 반영하기 때문이다. 그러나 TCS 교통량을 기반으로 한 경우 역시 정확도의 차이가 크지 않으며, 변화 추이도 유사하게 나타났다. 이러한 결과를 볼 때 향후 대용량의 과거이력자료가 축적될 경우 예측오차는 더욱 감소될 것으로 기대된다. There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

Intelligent transportation systems technologies are being developed and applied through transportation systems in the United States. An example of this type of innovation can be seen on toll roads where a driver is required to deposit a toll in order to drive on a toll road. To automatically process toll services, automatic vehicle identification (AVI) technologies should be developed and implemented. A summary is presented of a study that focused on the performance analysis of three types of AVI technologies that could be used for toll collection applications on the Crosstown Expressway and the Veterans Expressway in Hillsborough County, Florida. The three AVI technology types were optical/laser scanner, radio frequency, and inductive loop. The study aimed at analyzing the total average delay and AVI market share due to the usage of AVI technologies. Delay performance and market share resulting from the application of each AVI technology type were used to compare the effects of different AVI technology types. The analysis was based on computer simulation using an AVI lane choice model (demand model) and a delay model (performance model) with the data collected from the two toll roads in Hillsborough County. From the simulation results, a cost-benefit analysis was performed to evaluate the impacts of AVI technologies on the ratio of benefit over cost. Results of the cost-benefit analysis can be used to determine the optimal configuration of AVI lanes and manual lanes. A procedure is provided that can be used for planning and designing AVI technologies used in toll service.

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.

This research paper introduces an intelligent parking management system aimed at optimizing parking space utilization. The system's main objective is to first keep a track of all the incoming and leaving vehicles within the parking area, while also updating the track of all the occupied and available parking slots at the same time, effectively managing the traffic. A camera installed at the entry gate will recognise the license plate and will be segmented and processed through optical character recognition achieving the recognition accuracy of 95.8% The vehicle number is then stored in a database where entry and exit times are also stored. The extracted license number will then be linked to an available parking slot that would be closest to the said vehicle, calculated through algorithms such as Dijkstra. Finally, the automatic credit system will calculate the cost through entering and leaving time, and the amount will automatically be deducted from the app's wallet. This integrated approach aims to significantly improve parking efficiency compared to manual systems. The paper will discuss the system's design, implementation, and potential performance outcomes for vehicle detection, license plate recognition, and parking slot availability. . KEYWORDS :Computer vision, Character recognition, YOLO, Vehicle detection, OpenCV

Radio frequency identification (RFID) based automatic highway toll collection system has become very popular among developed countries. However, RFID is not feasible for developing countries to embed with each vehicle since it is very costly. Moreover, as metal objects can influence Radio Frequency (RF) field, intently the nearness of any metal object while reading RFID information may result in unwanted noise. These problems are still significant concerns. We propose a vehicle number plate recognition-based automated toll collection system to address these issues, which is more efficient, reliable, and cost-effective for widely use. In this research, the Normalized Cross-Correlation (NCC) based template matching algorithm is exploited for character recognition from each vehicle's number plate. After recognizing characters from a number plate successfully, a fixed amount of toll fee is charged automatically according to the vehicle's category.