Toll Collection System Research Articles

Intelligent toll collection system for moving vehicles in India

• Automatic number extraction by clicking a photo of the License plate of a moving vehicle. • Identification and matching of the bank account of vehicle owner. • Automatic toll amount debit from bank account at toll plaza. • Automatic Low balance reminder in account to the driver. • Optimize waiting time at toll plaza. • Optimization of fuel wastage and extraction of pollution at toll plaza. This paper proposes an automatic toll collection system to debit the toll of moving vehicles at a toll plaza in India. An effective approach is presented here to localize the license plate of vehicles. A database has been created and linked to test the performance of the prototype toll collection system of moving vehicles. The database includes the number of vehicles, vehicle owner's name, the unique identification number of the vehicle owners, their mobile number and balance of the linked bank account. The results show a significant reduction in the vehicle waiting time, queue length, fuel wastage, and excretion of pollution at a toll plaza. In future the system can be used for the theft control.

Adoption of FasTrak on San Francisco Bay Area Bridges: Impact of Operations Research Models in Relieving Congestion

Bay Area toll bridges are the main transportation link across the nine-county San Francisco Bay Area. These bridges experience extreme congestion and become bottlenecks during peak hours with long backups at the toll plazas. A solution to ensure smooth vehicle throughput at toll plazas is the widespread adoption of the electronic toll collection system called FasTrak. However, the FasTrak system has experienced low usage rates since its inception relative to other toll collection systems in the country. Forecasting, marketing, and operations research models were utilized to make recommendations and collaborate with transportation authorities to increase FasTrak usage during peak hours (5–10 a.m. and 3–7 p.m.) to address traffic congestion. After these recommendations were implemented, FasTrak usage increased from 40% in 2006 to the long-term target of 70% by 2016. This paper presents a synthesis of the challenges and the implementation of the FasTrak Strategic Plan. Furthermore, econometric models are presented that capture the effect on traffic volumes of increased FasTrak usage achieved through congestion pricing. Saved travel time resulted in productivity gains of approximately $569 million per year. This study contributes to an understanding of the role of effective transportation policies in reducing congestion and improving productivity. History: This paper was refereed. Supplemental Material: The online appendix is available at https://doi.org/10.1287/inte.2022.1127 .

Quantitative Analysis of RFID based Vehicle Toll Collection System using UML and SPN

This paper focuses on the quantitative analysis of RFID based vehicle toll collection system. Since we conduct the quantitative analysis long before the implementation of the infrastructure, the approach is realized by the UML and SPN to capture the system dynamics and carry out multiple performance tests of the possible infrastructure. Thus, the performance tests ensure the installation of correct number of RFID vehicle toll collection booth in the entrance of a bridge or a highway so that the traffic congestion can be kept as minimal as possible as well as financial viability can be confirmed. We analyze the response time and throughput to know the maximum limit for the diverse number of arrival vehicles that is served by the different number of toll booths. This finally gives us a better understanding of the number of units necessary for toll collection to decrease the traffic congestion in a budget constraint manner.

An anonymous and unlinkable electronic toll collection system

An anonymous and unlinkable electronic toll collection system

Optimal control method of freeway based on tollbooths lane configuration and variable speed limit control

There are tollbooths on some freeway ramps, and toll lanes can be divided into Electronic Toll Collection (ETC), Manual Toll Collection system (MTC), ETC/MTC hybrid toll lanes and closed. The traffic capacity of different lanes is different. Different lane combinations are set to adjust the traffic flow of the ramp into the main line. Therefore, this strategy can be regarded as a kind of ramp metering (RM). This paper presents an optimal control method for freeways based on tollbooths lanes configuration and variable speed limit (VSL) control. Firstly, cellular automata model and cell transmission model are used to describe the operation of toll plazas and main line traffic flow respectively. Furthermore, the freeway control methods are constructed by using tollbooths RM (TB-RM) and TB-RM combined with main line VSL control respectively to improve the freeway traffic operation efficiency. Finally, the proposed method is simulated experimentally. Results from simulation experiments demonstrate that the proposed method (i) significantly improves the traffic performance in terms of total time spent savings; (ii) observably enhances driving safety.

Fraud likelihood determinants in the road toll collection system in Cameroon

The study set out to investigate fraud likelihood determinants in the road toll collection system in Cameroon. The specific objectives were to examine fraud likelihood determinants in the management of road toll ticket production, inventory of vehicles accessing tollgates, sale of road toll tickets, physical security of money collected at the tollgate, and physical security of money conveyed to the public treasury. The poor physical state of toll roads in Cameroon points to the degree to which toll collections are used in road maintenance. The roads are usually plagued with potholes and poor or no road signs leading to deadly road accidents. The researcher collected data through a questionnaire, and regressed using a summation model. The findings revealed that toll ticket production, ticket sales, and physical security of money at tollgates have crucial internal control weaknesses that create fraud opportunities. It was therefore recommended that manual tollgate systems be converted to electronic systems so as to cut down on tollgate traffic congestions and secure more road toll cash inflow for road maintenance. The second recommendation was that toll fee collections be visibly seen by tollgate actors to be used for road maintenance when they use good roads. In this way, their road ethics increases while road toll evasion reduces. The third recommendation was that government fight against corruption and fraud should moves from rhetoric to action. Lastly, monitoring and impromptu audits at tollgates be instituted and activated.

Economic impact of road transportation infrastructure projects: the case of Egnatia Odos Motorway

ABSTRACT Non-cyclical and high-leverage infrastructure projects, such as road transportation networks, have been considered as critical policy instruments to promote growth and social development. Yet, their growth-generating effect on the economic welfare of countries and regions has come under scrutiny in recent years: several studies have nuanced the implicit positive associations between investments in transportation and economic benefits. Building upon a set of traffic flow characteristics as potential correlates to the regional development indicator, this research focuses on the economic impacts of Egnatia Odos Motorway (EOM) on Greece's Northern region. To specify, by employing a large-scale longitudinal dataset which includes over 230 million entry records of various vehicle types along EOM, generated from toll collection systems between 2010 and 2019, we investigate the associations between traffic data and potential variations in regional GDP per capita annual growth rate. Our results suggest positive associations between regional economic development and the EOM operation and, more specifically, with passengers' transportation and inland freight. We conclude that transportation big data provide essential input for the appraisal of a road transport investment project, reveal the status of regional welfare, and may contain valuable information for spatial management and planning.

SURVEY PAPER ON AUTOMATED ELECTRONIC TOLLING SYSTEMS USING RADIO FREQUENCY IDENTIFICATION TECHNOLOGY

Purpose: In this paper we carry out a review on Automated e-tolling systems using RFID technology that has already been proposed by other researchers. Analysed and synthesised the researchers’ solutions and identifying their advantages and disadvantages, and also the gap they left that needs further research.
 Methodology: the approach used to conduct this review was to collect extensive peer reviewed literature on how solutions by several authors’ RFID technology implementation for Automated e-tolling systems helped collect road tax automatically and efficiently around the world with the effect of eliminating vehicle congestion around toll plazas. A prototype was developed to test the effectiveness of our proposed solution.
 Findings: This study found out that the use of RFID technology in Automated E-tolling systems is the cheapest and most effective way of collecting road tax revenue without delaying motor vehicles. Furthermore, enables vehicles to pay road tax while moving. This study also revealed that for the Automated E-tolling system to be secure and efficient the communication between RFID tag and reader has to be secured. Due to limitations in resources in cheap passive RFID tags, text steganography using Unicode zero width characters is most appropriate due to its high embedding capacity and very low processing needed.
 Unique contribution to theory, practice and policy: The review was able to bring out the importance of securing the communication between tag and reader thus building a system with security from design not as an afterthought. It also reveals the use of text steganography as a way of preserving tag privacy. Vehicle congestion at toll collection points has a domino effect of causing pollution to the environment, loss of productive time while waiting in the queue at toll plazas to be saved and also loss of fuel while the vehicle is idling waiting for its turn to be saved. Automated e-tolling systems using RFID technology also reduces the cost of collecting road taxes by significantly reducing the manpower needed at various toll plazas thereby making the system more efficient than the current manual or semi-automated toll collection systems currently available in Zimbabwe.

Vehicle Detection and Counting for Toll Plaza

Many highway toll collection systems have already been developed and are widely used in India. Some of them contain manual toll collection, RF tags, barcodes and license plates recognition. All of these systems have drawbacks that lead to some errors in the corresponding system. At toll plaza, all lanes have a mixed lane system that is, both MTC and ETC. The delay and queue is mainly due to this two different charging methods vehicles pass through the same lane. In addition, with the help of collected data and visuals onsite investigation, some additional causes of traffic .Considering all these causes, this is the paper proposes solution to these problems. In this project we are using SSD_Mobilenet_V1 architecture. It uses the TenserFlow algorithm, which helps detect objects using images, videos, or CCTVs. It will contain study of areas such as Image processing, image enhancement. The proposed model can support government agencies to dynamically manage the toll plaza. It will help to tally all the cars at the end of the day to help avoid frauds which can conducted by the toll booth attendee.

Spatiotemporal attention mechanism-based multistep traffic volume prediction model for highway toll stations

As the fundamental part of other Intelligent Transportation Systems (ITS) applications, short-term traffic volume prediction plays an important role in various intelligent transportation tasks, such as traffic management, traffic signal control and route planning. Although Neural-network-based traffic prediction methods can produce good results, most of the models can’t be explained in an intuitive way. In this paper, we not only proposed a model that increase the short-term prediction accuracy of the traffic volume, but also improved the interpretability of the model by analyzing the internal attention score learnt by the model. we propose a spatiotemporal attention mechanism-based multistep traffic volume prediction model (SAMM). Inside the model, an LSTM-based Encoder-Decoder network with a hybrid attention mechanism is introduced, which consists of spatial attention and temporal attention. In the first level, the local and global spatial attention mechanisms considering the micro traffic evolution and macro pattern similarity, respectively, are applied to capture and amplify the features from the highly correlated entrance stations. In the second level, a temporal attention mechanism is employed to amplify the features from the time steps captured as contributing more to the future exit volume. Considering the time-dependent characteristics and the continuity of the recent evolutionary traffic volume trend, the timestamp features and historical exit volume series of target stations are included as the external inputs. An experiment is conducted using data from the highway toll collection system of Guangdong Province, China. By extracting and analyzing the weights of the spatial and temporal attention layers, the contributions of the intermediate parameters are revealed and explained with knowledge acquired by historical statistics. The results show that the proposed model outperforms the state-of-the-art model by 29.51% in terms of MSE, 13.93% in terms of MAE, and 5.69% in terms of MAPE. The effectiveness of the Encoder-Decoder framework and the attention mechanism are also verified.

Review of Toll payment apps for smartphons

The constant increase in motorization rate and passenger cars usage lead to rising traffic congestion, which causes traffic delays and unfavorable traffic regime. In the toll collection system, the use of modern devices, specifically smartphones, would allow vehicles to pass through the toll collection system without stopping and time delays, which would solve the problems of queuing but also reduce the impact of vehicles on environmental pollution. This paper describes the ways of working of various applications that are used today in countries around the world, mainly as a secondary way of paying the fee for the use of the road network. The analysis of applications showed that in order to pay the toll, in addition to downloading the application, the user needs to create a user account, enter the number of vehicle registration plates and the number of payment, credit or debit card through which payment will be made. In addition to the benefits offered by mobile devices, there are certain disadvantages and space for further improvement.

Political and technical complexities of electronic toll collection: Lessons from Taiwan

Traditional manual toll collection (MTC) imposes a significant queue length near toll plazas and results in road users delay (travel time loss), administration, fuel consumption, accidents, and other societal costs. Many countries (e.g. the U.S., Japan, Taiwan) have introduced and are continually upgrading Electronic Toll Collection (ETC) systems, thereby achieving key efficiencies and reduction in social costs. ETC systems worldwide have different toll collections technologies, for example, by road usage or Vignette, by peak or non-peak travel, or by distance travelled. Consequently, countries are faced with many technical and political complexities both at the initial consideration of whether to introduce ETC, and in any subsequent development. Taiwan has much experience of both toll collection and also ETC and has a long history in relation to its introduction. This paper presents historical and qualitative interview data with highly experienced ETC operators and government officials in Taiwan. Results are presented and discussed along four major axes: practical applicability, technological development, political variation and publicity and marketing. It also provides a retrospective and current consideration along these axes of technical and political complexities involved with introducing ETC. The paper is intended to inform transportation agencies considering introducing or developing their own ETC systems. Areas of future research for ETC are also suggested.

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.

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.

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.

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.

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.

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.

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.