Toll Collection Research Articles

Fine-Grained Traffic Flow Prediction of Various Vehicle Types via Fusion of Multisource Data and Deep Learning Approaches

Both road users and road administrators are keen to know traffic flow of fine-grained vehicle type. Successful prediction on the traffic flow of heavy, medium and small vehicle could contribute to the improvement of travel safety and efficiency. However, the classification on vehicle type is always not accurate enough using in practice. It could cost a lot to identify from the additional video cameras to cover the full-length of large-scale freeway with high-resolution to capture vehicles clearly. In this paper, empirical data are cleaned, normalized, compensated, filled, decoded and filtered with help of the fusion of vehicle detector data, remote microwave sensors data and toll collection data. The traffic flows of fine-grained heavy, medium and small vehicles are successfully reconstructed. Improved deep belief network (DBN) are then proposed to forecast traffic flow of different types of vehicles in 30-, 60- and 120-minutes time interval. Random-selected road segments on a ring way around a city are trained with data accumulated three months and predict data in the next month. According to prediction error analysis, the proposed method performs better in estimation and forecasting, with respect to the existing methods, especially for longer time prediction and heavy vehicle prediction. It would benefit traffic control to prevent freeway congestion escalation, protect the traffic infrastructure via heavy vehicle control, reduce the road risk, prompt quick emergency response and eventually contributes to more applications for intelligent transportation system (ITS).

AUDIT OF INCOME FROM LOCAL FEES IN SELECTED COMMUNES OF THE POMERANIAN PROVINCE IN POLAND

The article presents the importance of auditing the assessment of a commune's budget revenues for tourist fees (local fee or spa fee) as a tool enabling its increase by the commune authorized to impose it. The purpose of this article is to present on the basis of selected coastal municipalities of the Pomeranian Voivodeship in Poland, the role and significance of the audit of the assessment of income to the municipal budget in terms of local and spa fees. The article uses case study, analytical method, inference method and document examination method as the research methodology. The source materials for the analysis were documents made available on the pages of the Public Information Bulletin by the assessed local government units from the Pomeranian Voivodeship (reports on the implementation of the budget and Rb-27s reports containing information on revenue for the year). The local and spa fees constitute a small share in the total income of the budgets of the surveyed municipalities. The key factor improving the revenues of municipalities from local and spa fees is the improvement of their collection system. The risk of inefficient collection of fees by those who collect them from tourists is a threat to effective collection of the fees. Therefore, individual communes should improve the supervision system and control of toll collection by hotel service providers.

Machine Learning Based Framework for Vehicle Make and Model Recognition

Nowadays, the speedy increase with in the rage of the automobiles on the main road and urban roads have created several challenges regarding the proper management and management of traffic. This is a very significant framework for intelligent traffic monitoring and management. Vehicle analysis is an important component for many smart applications, that includes automated toll collection, self-guided car driver assistance systems, smart car parking systems. In a recent years, due to increased security awareness in parking lots, restricted areas and building for access control systems, the need to identify and classify the vehicles has become important.

On-road detection of trucks with high NOx emissions from a patrol vehicle with on-board FTIR analyzer

Technological advances in heavy-duty vehicle engines, allowing them to reach NOx emissions comparable to European diesel passenger cars per km driven, are being compromised by aftermarket defeat devices such as selective catalytic reduction (SCR) emulators, many of which can be quickly deactivated by the driver. In a pilot study, the prevalence of trucks with excess NOx emissions on Czech motorways was evaluated using an ordinary Customs Administration patrol vehicle temporarily fitted with a portable fast-response Fourier Transform Infra Red (FTIR) analyzer, acting as an impromptu chase vehicle. The Euro emissions category of the truck was provided from the motorway toll collection transponders. A total of 222 unique trucks were measured during a one-week pilot project. Of these, 66% were Euro VI, 25% were Euro V, and 9% were older categories. NO/CO2 ratios were calculated as a ratio of numerical integrals of the peaks of measured concentrations, as a ratio of maximum measured concentrations, and by linear regression, with the regression approach yielding most realistic results and mean calculated error of 0.2 g/kWh NO. At assumed 85% NO in NOx and 634 g/kWh mean CO2 emissions, the mean emissions of the cleanest 83% of Euro V and cleanest 63% of Euro VI trucks were within the corresponding NOx limit (2 g/kWh for Euro V, 0.46 g/kWh for Euro VI) multiplied by a factor of 1.5. Providing for some allowance for legitimate occurrences of high NOx emissions, about 10–15% of Euro V and about 10–25% of Euro VI trucks are believed to be excess emitters, with no SCR functionality on about 10–15% of Euro VI trucks. The portable FTIR, temporarily mounted on a law enforcement vehicle, can be readily used as a screening tool, identifying vehicles to be stopped for additional inspection, but also during roadside emissions inspections.

User perception of fairness of time-of-day pricing and other typical toll discounts

Abstract The paper describes the research conducted by the authors concerning the opinion of transportation users about the fairness of Time-of-Day pricing and discounts for users of Electronic Toll Collection technology and for frequent users of the toll facilities. To this effect, the authors analyzed attitudinal data collected from a sample of more than one thousand users, who provided their opinions about the fairness of using pricing to reduce congestion and of providing such toll discounts. The authors conducted descriptive analyses of the data, and estimated ordinal discrete choice models, elasticities, and marginal effects to assess the significance of various socio-economic attributes of the respondents. The paper ends with a discussion of chief conclusions and policy implications.

The potential of IoT for instrumentation and measurement

It is rare for someone in the engineering or science fields not to have heard of the Internet of Things (IoT). IoT has been disrupting many industries by providing an unprecedented approach for a (potentially large) number of distributed components connected over a network to collect data, collaborate, and perform tasks with almost no human intervention. Spending in IoT is forecasted to reach US $1 trillion by 2022 [1] and is considered to be one of the core enabling technologies behind the fourth industrial revolution. But what is IoT really? The deep understanding of IoT and therefore its definition are still evolving. Meanwhile, IEEE defines an IoT system as “a system of entities (including cyber-physical devices, information resources, and people) that exchange information and interact with the physical world by sensing, processing information, and actuating” [2]. Furthermore, the “Thing” in IoT can be defined as “an IoT component or IoT system that has functions, properties and ways of information exchange” [2]. The exact interpretation of the “Thing,” and not the “Internet” part which has existed for many years, is causing IoT's definition to still evolve [3]. In essence, the components of an IoT system interact with each other to fulfill the goal for which the system has been designed. For example, in a smart home, an IoT system consisting of interconnected thermostats, switches, alarms, triggers, cameras, sensors, and actuators can autonomously control lighting, temperature, ambience, and security based on the inhabitants' observed behaviors, leading to more efficiency, comfort, and energy savings. Our transportation systems can benefit from an IoT consisting of connected vehicles, drivers, pedestrians, and traffic infrastructure (signs, lights, roads, etc.) for more efficient traffic routing, road assistance, emergency response, parking support, and toll collection. Or, in an industrial setting, IoT can enable the integration of manufacturing machines or robots equipped with instrumentation, sensing, processing, communication, and collaboration, leading to more efficiency and profitability in the management of equipment, assets, processes, and produced goods. This Industrial IoT, also known as IIoT, is of particular interest, since it is a core enabling technology behind Industry 4.0, estimated to generate a US $12 trillion market by 2030 [4].

Receiver Designs for Electronic Toll Collection Systems : A Survey

<p>This paper discusses about different receiver designs adopted so far for various electronic toll collection systems. A comparative analysis based on the discussions is also provided. It shows that each design has it's own advantages and disadvantages compared to others. The main aim of this paper is to identify the most suitable design. The researches shows that the receiver design described in the 5.8GHz digitally controlled DSRC receiver for Chinese electronic toll collection system is the most suitable one. Here all RF, IF blocks and digital baseband for on-chip automatic gain control, are integrated on an RF-SoC. The proposed digitally controlled LNA and mixer circuits are elaborated. The technology used is 0.13μm CMOS technology. The RF block occupies a chip area of 0.75mm2. It consumes 22mA under a 1.5V supply voltage. The bit error rate maintains better than 10-6, the input power level varies from -75dBm to -8dBm. This design provides a receiver sensitivity improvement of at least 25%, and a dynamic range enhancement of at least 12%.</p>

Time-varying Analysis of Traffic Conflicts at the Upstream Approach of Toll Plaza

This study investigates the traffic conflict risks at the upstream approach of toll plaza during the vehicles’ diverging period from the time of arrival at the diverging area to that of entering the tollbooths. Based on the vehicle’s trajectory data extracted from unmanned aerial vehicle (UAV) videos using an automated video analysis system, vehicles’ collision risk is computed by extended time to collision (TTC). Then, two time-varying mixed logit models including time-varying random effects logistic regression (T-RELR) model and time-varying random parameters logistic regression (T-RPLR) are developed to examine the time varying effects of influencing factors on vehicle collision risk, and four models including the standard random effects logistic regression (S-RELR) model, standard random parameters logistic regression (S-RPLR) model, distance-varying random effects logistic regression (D-RELR) model and distance-varying random parameters logistic regression (D-RPLR) are developed for model performance comparison. The results indicate that the T-RPLR model has the highest prediction accuracy. Eight influencing factors including following vehicle’s travel distance, following vehicle’s initial lane, following vehicle’s toll collection type, leading vehicle’s toll collection type, distance between two vehicles’ centroids, and following vehicle’s speed, are found to have time-varying effects on collision risk. Meanwhile, the first six factors are found to exhibit heterogeneous effects over the travel time. Another important finding is that the vehicle that comes from the innermost lane has an increasing trend to be involved in traffic conflicts, whereas the collision risks of other vehicles decrease as the travel time increases. Moreover, vehicles with higher speed have a decreasing probability to be involved in crashes over the travel time. Interestingly, the results of D-RPLR model are similar with that of T-RPLR model. These findings provide helpful information for accurate assessment of collision risk, which is a key step toward improving safety performance of the toll plazas’ diverging areas.

Toll and Traffic Management System for Express Highways

Now a days, toll plazas at the highways are operated manually, where a vehicle comes near the toll booth and toll collector collects the cash and enter the vehicle data and provides a receipt. Manually operated Toll Plaza Systems leads to longer waiting time of vehicles and heavy traffic at the highways. To overcome this issue of traffic congestion and time management and to bring automation in the toll management system, we have introduced an innovative, optimized and revolutionary system. This paper is putting forward an efficient and cost-effective technique of automatic toll collection. The system is based on the mobile GPS network and will use various APIs for development. The cost to be paid at the toll gate is auto decided as per the government limits and the toll booth charges. System will use online payment gateways to collect those revenues. If the balance is low in the user’s account then it can be recharged at the booth itself. At the user’s end, If the toll tax payment is delayed by certain timeline then user will be informed by an alert message and if delay still exists then strict actions will be imposed along with proper penalty charges for the same. This system is the novelty to the existing toll system. It will have a wide impact on people's life as its scope will lead to safe and enhanced productivity through the use of advanced technologies. This will also minimize fraud and will provide user convenience. It will also enhance the operational efficiency of toll collector.

T-Coin: Dynamic Traffic Congestion Pricing System for the Internet of Vehicles in Smart Cities

Alleviating traffic congestion is one of the main challenges for the Internet of Vehicles (IoV) in smart cities. Many congestion pricing systems have been proposed recently. However, most of them focus on punishing the vehicles that use certain roads during peak hours, neglecting the proven fact that rewards can encourage drivers to follow the rules. Therefore, in this paper, we propose a new congestion pricing system based on reward and punishment policies for the IoV in a smart city environment, where the vehicles are rewarded for voluntarily choosing to take an alternative path to alleviate traffic congestion. The proposed system is implemented using vehicular ad hoc networks, which eliminate the need for installing a costly electronic toll collection system. We propose a new virtual currency called T-Coin (traffic coin), that is used to reward the vehicles for their positive attitude. T-Coin is also used in the tender between vehicles to manage the road reservation process. The proposed system uses dynamic pricing to adapt to peak-hour traffic congestion. Using simulated traffic on a real map of Beijing city, we prove the usefulness of T-Coin as a traffic congestion pricing system.

Visualizing Potential Transportation Demand From ETC Log Analysis Using ELK Stack

Traffic conditions are among the issues most concerned with the general public, and the freeway is a large-scale Internet-of-Things application. In addition to obtaining real-time road usage information, analysis of local road usage habits is crucial in evaluations of government policy implementation. Using road usage data provided by the electronic toll collection (ETC) system, we investigated the data on road usage history on the freeways. The ELK stack was employed to construct a platform for visualizing real-time road usage information and history in this article; the platform is named the local transportation knowledge (LTK) platform. By analyzing more than 500 million pieces of data, the LTK platform proposed in this article efficiently visualized road usage data and facilitated the acquirement of local road usage knowledge. We verified that residents of other counties and cities commuted to Taichung each day. We also discovered that a considerable number of Taichung city residents were employed in Hsinchu Science Park and commuted between the two places. The LTK platform can present real-time freeway traffic conditions, facilitate in-depth analysis of local road usage data, and provide data to verify the relevant information.

Estimation of Regional Economic Development Indicator from Transportation Network Analytics

With the booming economy in China, many researches have pointed out that the improvement of regional transportation infrastructure among other factors had an important effect on economic growth. Utilizing a large-scale dataset which includes 3.5 billion entry and exit records of vehicles along highways generated from toll collection systems, we attempt to establish the relevance of mid-distance land transport patterns to regional economic status through transportation network analyses. We apply standard measurements of complex networks to analyze the highway transportation networks. A set of traffic flow features are computed and correlated to the regional economic development indicator. The multi-linear regression models explain about 89% to 96% of the variation of cities’ GDP across three provinces in China. We then fit gravity models using annual traffic volumes of cars, buses, and freight trucks between pairs of cities for each province separately as well as for the whole dataset. We find the temporal changes of distance-decay effects on spatial interactions between cities in transportation networks, which link to the economic development patterns of each province. We conclude that transportation big data reveal the status of regional economic development and contain valuable information of human mobility, production linkages, and logistics for regional management and planning. Our research offers insights into the investigation of regional economic development status using highway transportation big data.

Tolling in Turkey

With over three million vehicles using electronic toll collection in the country, Turkey has invested substantially in the business of highway tolling by Dr Erkan Dorken, Aselsan, Turkey

Intelligent System to Identify Unauthorized Automobiles using Internet of Things

In cities vehicle checking and analysis is a prominent task. These tasks are accomplished by traffic policeman and include various manual works. We present a system to automate the existing task using the technologies Internet of things (IoT) and Artificial Intelligence (AI). The proposed system checks the details of the vehicle and isolates unauthorized automobiles, detects the overall traffic in a specific area, road damage analysis and automated fine collection and toll collection. This system is composed of a two module. Module one embedded with a unique code located in the vehicle and Module two is a scanning device in which the unique code is obtained and further processed in the receiving end using which other details of the vehicle is gathered from the cloud storage. This paper mainly focuses on multiple checking of vehicles using RFID wireless communication, OFDMA technique for numerous access and Artificial Intelligence to predict the traffic and road damage analysis. This system operates using radio frequency communication, and replaces manual task in vehicle invigilation process.

Methodology for determining ecological benefits of advanced tolling systems

Toll plazas are places on the road network where increased emissions of exhaust gases occur due to changes in vehicle driving regime in their corresponding impact areas. Therefore, they provide a great potential in terms of the ability to significantly reduce the emission of pollutants by using advanced technologies. In light of this, this paper aims at getting the most accurate quantification of pollutant emission (CO, CO2, HC and NOx) for the various vehicle categories which use Manuel System (MS), Electronic toll collection (ETC) with mechanical barriers and Multi Lane Free Flow (MLFF) system, for determining ecological benefits that can be achieved using advanced tolling systems. The measurement of the emission of harmful gases was carried out in real field conditions for the five most common classes of passenger cars, light truck and semi-trailer-truck. Vehicle speed, fuel consumption and emission of pollutants were recorded every second, in various driving processes in the impact areas of toll plazas, as well as in numerous scenarios that involve a different number of vehicles in a queue. The obtained results show that the use of the MLFF system, compared to the MS, can achieve a reduction in CO2 in the range of 25%–45% and the reduction in NOx in the range of 32%–98%, depending on the type of vehicle and the considered scenario. The case study of the tolling system in the Republic of Serbia, on a sample of 77,408,112 vehicles, has shown that moving from the existing to an advanced MLFF tolling system allows for annual ecological benefits ranging from 1,349,862 € to 1,491,391 €.

Lucha política en el ciberespacio (Twitter) en tiempos del COVID-19 (Perú: marzo-mayo- agosto 2020)

This research has allowed us to know the most important characteristics of the political struggle being waged in Peru by the political parties that are represented in the Congress of the Republic and the National Government represented by the President of the Republic and the ministries that have been the main agents in the fight against Covid-19.  The study period covers since March 1, 2020, being the month in which the State of Sanitary Emergency began in Peru, with the quarantine and social isolation established by the national government to halt the increase of Covid-19, until August 31, 2020, when Peru became the first country in the world in the mortality rate caused by Covid-19 (Gestion Newspaper, 2020).  During the period under study, the Congress of the Republic has denied the vote of confidence to the Ministerial Cabinet chaired by Pedro Alvaro Cateriano Bellido in the early morning of August 4, 2020 [Congreso Noticias (News Congress), 2020] and the enactment of regulations by the Congress of the Republic that were considered unconstitutional by the National Government, such as the Law for the suspension of toll collection, for which the Executive Branch filed a complaint of unconstitutionality (Gestion Newspaper, 2020).  A thorough review of current theory and previous research related to the topic was carried out. The conclusions allow us to point out that the political struggle in the cyberspace social network twitter has been irregular, differentiated and dissimulated, avoiding direct conflict, without observing defined strategies, preferring populist messages and where few parties show themselves to be moderately opposed to the national government.

Smart Toll Collection System Using ZIGBEE and RFID

As a survey stated by Amit Gupta almost 15 crores vehicles utilize national highways around India, and if on average each vehicle have to wait idly for 10 minutes in toll booths it results in a loss of Thousand two seventy two crore a day. The issues involved in manual toll collection involves hurdles like exact change, system malfunction at times, staff changeover per duty and manual imperfections. It is proposed to implement smart card named INDIA-Pass compatible with other transportation services used in India. But it is highly appreciable to arrive with a solution explicitly for automated toll collection. One such solution is proposed in this paper, an automated toll collection system with wireless transceiver and cloud-local hybrid database maintenance. In automated toll collection system, the driver does not need to stop at the toll gate and one neither have to stand still in a long line to pay his entry fee. Though it sounds simple the proposed method decreases the utilisation of fuel, lessen street blockage, enhance street security and make travelling a pleasure for all. This paper introduce the idea of gateless computerized ETC (Electronic Toll Collection) utilizing ZIGBEE handset with RFID. ZIGBEE mechanized ETC can eliminate human intervention in manual toll collection and consequently bring down the cost of activity.

基于“互联网+识别与支付技术”的高速公路联网收费系统技术改造工程软件研发组织设计

基于“互联网+识别与支付技术”的高速公路联网收费系统技术改造工程软件研发组织设计

Intelligent transport systems in Turkish urban environments: a comprehensive review

The main aim of this paper is to address and elucidate both the functions and the roles of intelligent transport systems, and to provide an overview of their development in Turkey. The major objectives of this paper are to give a clear understanding of and comment on intelligent transportation trends, and to discuss the impact of intelligent transport on traffic status in Turkey. Most of the indicated technologies and applications belong to various disciplines; hence, through the present paper's material, we attempt to close gaps and offer a comprehensive overview. Some of the key intelligent transport system indicators are road and traffic information, dynamic traffic light sequences, smart bus stops, emergency vehicle notifications, emergency services, electronic toll collection, variable messages, wireless communication, and traveller information. Understanding these components can help developers and researchers comprehend how advanced sending can play a crucial role in intelligent transport systems.

Intercity truck route choices incorporating toll road alternatives using enhanced GPS data

ABSTRACT This research presents the data collection, specification and estimation of a route choice model for intercity truck trips, with a focus on toll road usage. The data was obtained from driver-validated and enhanced GPS records. A mixed logit model with a path-size factor is specified. It accounts for heterogeneity among drivers using distributed coefficients for travel time and its variability. The estimation results show wide heterogeneity among drivers based on employment type and availability of electronic toll collection tags. Toll value of time and toll value of reliability distributions are derived. The model application is demonstrated on several trip corridors.