Toll Plaza Research Articles

Using a Discrete-Event Simulation Model for Evaluating the Operational Performance of Toll Plazas

Toll plazas are commonly described as a potential bottleneck due to the collection process at specific points on the highway. In a highway concession model, tolls are used to cover the majority of infrastructure costs. However, not all existing road concessions have toll plaza–related key performance indicators (KPIs), resulting in less efficient operations for transport managers and road users. To address this issue, this paper presents a discrete-event simulation (DES) model for policy analysis and the model for the planning, management, and evaluation of toll plazas using an extensible simulation package with animation capabilities, built by selecting modules that contain process features. The DES describes situations in which entities (vehicles) arrive, wait in the queue (if necessary), and then are attended to before leaving the system, either directly or indirectly. As a result, the simulation is based on discrete events (arrivals and departures) and statistical process data. This paper examines data from Brazil’s first public–private partnership (PPP) project in the area of road infrastructure and analyzes the toll plaza in Itaúna/MG using a case study methodology. The DES model was used in this case study, and the results show that the toll plaza was in good operating condition during the peak hour analyzed because the vehicular flow was lower than the system capacity. The willingness to pay the toll rate through the concept of open road tolling or a free-flow system, on the other hand, would provide significant benefits to road users because it would significantly reduce the time it takes to cross the toll plaza. The developed DES model assists toll plaza managers in making decisions while keeping in mind the need to comply with the operational efficiency measures agreed upon in the concession contracts.

Proactive integrated traffic control to mitigate congestion at toll plazas

AbstractToll plazas on expressways often experience congestion owing to the imbalance between traffic demand and supply. To address this issue, this paper designs a proactive traffic control method to relieve congestion at toll plazas based on the model predictive control (MPC) that integrates the dynamic lane configuration, that is, the numbers of electronic toll collection (ETC) and manual toll collection (MTC) lanes, and the variable speed limit (VSL). The proposed method first forecasts short‐term traffic demand in toll plazas based on the long short‐term memory neural network. Then the cell transmission model (CTM) is applied to predict the traffic evolutions in the toll plaza area. At last, the MPC‐based control framework is used to optimize the numbers of ETC and MTC lanes and the variable speed limit to minimize the total vehicle travel time in a rolling horizon. Micro‐simulation tests are carried out in VISSIM to verify the effectiveness of the proposed control method. The simulation results show that the proposed control method can significantly improve the traffic performances at the toll plazas. The findings in this study can lead to field implementation of proactive control at toll plazas.

A Study Onvehicle Movement And Ticket Vending Machine Distribution Intoll Booth

This study demonstrates for the first time how a toll gate can be fully controlled using the "Internet of Things" idea based on image processing technology. We examine and report on the circumstances of total time spent by a specific vehicle for money transaction on toll plaza and further evaluate total fuel wastage as well as human errors involvement, in reference to survey of annual toll collection on toll plazas, conducted by government in the year 2010. Finally, we agree with the idea of automating toll plazas entirely with the help of IoT technology and image processing in order to provide an ideal answer.

Bitumen stabilized materials as pavement overlay: Laboratory and field study

Bitumen stabilized materials applied as base courses have been used in many countries. In the southern Brazilian State of Rio Grande do Sul, two test sections were built using such mixes (in 2011 and 2015) as overlay asphalt emulsion base courses and have been under monitoring since then. In 2019, a new test section was built to evaluate mixes of granular materials and reclaimed asphalt pavement stabilized with emulsion and Portland cement as overlay base courses. The main objective of the research reported here was to evaluate the mechanical behavior of such materials and to assess their performance in the field during the years after construction. Indirect tensile strength, monotonic triaxial, and repeated load triaxial tests were carried out to obtain the necessary mechanical parameters. The data collected during the monitoring of the test sections were used to analyze the field performance in terms of permanent deformation. Besides, in situ moduli were obtained using backanalysis of deflection basins. The number of equivalent single axle loads (ESALs) for the analysis period was computed using data collected in toll plazas near the test sections. Using field and laboratory results and the South African TG2 performance model, it was possible to estimate the life of the studied pavements regarding permanent deformation. The TG2 model seems to underestimate the life of pavements with thick (>40 mm) asphalt layers. A model relating rutting to the number of ESALs was obtained, allowing the prediction of rutting of asphalt pavements overlaid by a bitumen stabilized base layer and asphalt wearing courses. Considering the test sections’ performances, the mixes proved to be efficient to improve structural capacity, also reducing the influence of the water level variation on pavement performance.

Deep Learning and SVM-Based Approach for Indian Licence Plate Character Recognition

Every developing country relies on transportation, and there has been an exponential expansion in the development of various sorts of vehicles with various configurations, which is a major component strengthening the automobile sector. India is a developing country with increasing road traffic, which has resulted in challenges such as increased road accidents and traffic oversight issues. In the lack of a parametric technique for accurate vehicle recognition, which is a major worry in terms of reliability, high traffic density also leads to mayhem at checkpoints and toll plazas. A system that combines an intelligent domain approach with more sustainability indices is a better way to handle traffic density and transparency issues. The Automatic Licence Plate Recognition (ALPR) system is one of the components of the intelligent transportation system for traffic monitoring. This study is based on a comprehensive and detailed literature evaluation in the field of ALPR. The major goal of this study is to create an automatic pattern recognition system with various combinations and higher accuracy in order to increase the reliability and accuracy of identifying digits and alphabets on a car plate. The research is founded on the idea that image processing opens up a diverse environment with allied fields when employing distinct soft techniques for recognition. The properties of characters are employed to recognise the Indian licence plate in this study. For licence plate recognition, more than 200 images were analysed with various parameters and soft computing techniques were applied. In comparison to neural networks, a hybrid technique using a Convolution Neural Network (CNN) and a Support Vector Machine (SVM) classifier has a 98.45% efficiency.

Why are Toll Plazas Always Congested?

Why are Toll Plazas Always Congested?

Development of Toll Equivalency Factors for FASTag Lanes Under Mixed Traffic Conditions

The traffic conditions in India consist of a high degree of heterogeneity in vehicle categories plying on the highways without any lane-following behavior. A similar behavior is observed at the toll plazas where a dedicated lane assigned to a vehicle class is encroached by the vehicles of other categories, causing a mixed nature of the traffic in the same lane. In the present study, service headway is taken as the measure of effectiveness for studying the effect of mixed traffic conditions on traffic operations at electronic toll collection system (ETC) lanes, which are called FASTag lanes in India. Service headway is composed of processing time and the clearance time of the vehicle. Videographic data were collected at three different toll plazas located on National Highways in India to capture the variability in traffic and human behavior. The results showed that the service headway for a vehicle varies between 1.56 s and 34.40 s. The service headway-based toll equivalency factors (HTEF) are developed for converting the mixed traffic flow into a homogeneous equivalent for FASTag lanes. The results showed that the HTEF varies from 1.01 to 2.61. The results are validated spatially with data taken from a different site, and no significant difference was found between both the converted and equivalent data. Field engineers can use the developed HTEFs to estimate the traffic flow in equivalent terms based on the traffic composition. Further, the present study results can also be used to study the capacity and level of service (LOS) of FASTag lanes.

Analysis on Lane Capacity for Expressway Toll Station Using Toll Data

Toll stations are bottlenecks in the traffic flow of expressways, and the evaluation of their capacity is essential for the operation of the expressway. Traditional capacity studies are mostly based on theoretical modelling of traffic engineering or simulation, with a focus on parameter tuning and idealized hypotheses, resulting in poor reliability. In view of the coexistence of electronic toll collection lanes and compound toll collection lanes at toll stations of expressways in China, the present study analyses the capacity of entrance and exit lanes of toll stations under mixed traffic conditions using a real toll data-driven approach. Firstly, the service time of a single vehicle during the saturation period was taken as the starting point for the capacity estimates. Secondly, the variation in service time for multiple categories of vehicles is modelled using lognormal distribution. Finally, the capacity of the two types of toll lanes at the designated toll station is determined. The important outcome of this study is the calculation of authentic capacity at the toll stations and the discussion of individual special toll lanes. Accordingly, it contributes to the development of appropriate policies to manage the operation of the toll plaza effectively.

CFC-GAN: Forecasting Road Surface Crack Using Forecasted Crack Generative Adversarial Network

Forecasting the road surface crack images with given present crack images is an important task to assist the road survivors in planning for their next lay down of road with the required financial assistance. We develop a Crack ForeCast (CFC) dataset comprised of road crack images captured with certain time intervals (months), the number of vehicles traveled (collected from toll plaza), and climatic information like temperature and precipitation. We have proposed a Conditional Forecasted Crack-Generative Adversarial Network (CFC-GAN) model to forecast the road surface crack images with various conditional factors. The proposed CFC-GAN model is trained in a paired end-to-end manner to avoid accumulative blurriness and to generate the appropriate forecasted crack images. Moreover, this paper introduces a new estimation loss function to improve the accuracy of the forecasted crack images. Wide experimental results were demonstrated to showcase the better performance of our model. The quantitative and qualitative analyses were made with various evaluation metrics like structural similarity, peak signal to noise ratio, inception score, Frechet inception distance, and intersection over union for the CFC-GAN model with the proposed dataset and other existing benchmark datasets.

Transport Sustainability Index: An Application Multicriteria Analysis

The unrestricted consumption of fossil fuels negatively impacts the economic, social and environmental aspects, observed from a sustainable perspective. Therefore, it is necessary to develop and adopt skills that enable the monitoring and mitigation of risks to the environment. In view of this, we propose a method with multiple approaches emphasizing a three-dimensional perspective of energy consumption by diesel engines, which represent one of the main pollutants emitters in transport. As a methodology, fuzzy logic was adopted, together with a recognition system, in order to mitigate the uncertainties inherent to the applied data. The procedure was applied to the city of Rio de Janeiro, Brazil, with information collected from seven toll plazas and a radar with volumetric counting. The results indicate a good adherence of the sustainability index to real cases, allowing a better observation of changes in environmental criteria and a more efficient inspection in the application of good practices, in addition to enabling greater participation of society in the inspection and adoption of environmental criteria in transport.

Improving highway traffic performance: Merging pattern design of a departure zone after tollbooths or ETC

There are two kinds of traffic congestion at a toll plaza on a highway: Congestion in the approach zone and congestion in the departure zone, while congestion in the departure zone has received less attention. The performance improvement in the departure zone can directly reduce congestion in that area and indirectly increase traffic capacity in the approach zone by increasing the upper limit of the outflow from the departure zone. In this paper, we propose a method on merging pattern design in the departure zone after tollbooths or electronic toll collection, to determine the optimal merging patterns for the departure zones with two typical shapes (i.e., right-trapezoidal and isosceles-trapezoidal). Different traffic congestion simulations show that, for the departure zone with either right-trapezoidal or isosceles-trapezoidal, our optimal merging pattern has the largest throughput, shortest mean time delay, and smallest average number of stops per vehicle, among other possible merging patterns, in heavy traffic scenarios. The optimal merging pattern for the isosceles-trapezoidal departure zone is usually better than that for the right-trapezoidal departure zone.

Critical evaluation of application of robotic process automation on toll plaza

India is having 2nd largest number of road network across the world. Transportation has come in front of us as a regnant part of India. Objectives: Increasing vehicles creating a lot of traffic congestion at toll plazas, therefore manual toll collection system is eliminated with fastag due to a lot of drawbacks. It is a kind of mini device that employs RFID technology, which makes collection of tolls easy and fast. Under this type of system, a RFID chip installed sticker, stick on the vehicle and amount gets automatically deducted from the bank account, in addition, with it numerous benefits to travelers as well as the highways authority of India. But still customers are facing a lot of problems while passing through toll plaza. Methodology: This study was focused on both the primary and the secondary data. To evaluate the factors one sample t-statistics was used for statistical analysis. Findings: The result showed that after implementing Robotic Process Automation numbers of factors like stress, time and satisfaction level came out, which were affecting the performance of toll plazas. Conclusion: The present study tries to detect whether Robotic Process Automation has any significant impact on the performance of toll plazas or not.

Traffic Count Analysis during COVID-19: Case Study of Toll Plazas under Project Highway along Nagpur-Jabalpur National Highway (NH44) near Nagpur, India

The Corona virus is originated in Wuhan, China, and has spread throughout the world since December 2019. Despite being close to China, India took two months to detect its first case. In months’ time it reached major countries of the world. Since then, the social life of the people has been disrupted because of the lockdown situations. Senior members were shocked to see such a situation for the first time in their lives, as all activities have been affected by the restrictions on both domestic and international travel and transport.This case study is an attempt to analyze the vehicle traffic counts at four toll plazas namely Khumari, KKBP, NBP and Borkhedi Toll Plaza located along Nagpur-Jabalpur National Highway (NH44) near Nagpur city from Maharashtra state of India during Session 2020 (during January to December) as an effect of COVID -19 under lockdown and unlocking situations. Tolls at Nagpur have been selected for being the national geographic centre with a hub of all activities. The study critically analyses the vehicle traffic count along with the comparative study of four toll plazas thereby making the analytical remarks with conclusions.

Measuring the Level of Road Safety through Road Safety Audit and Star Rating Method – A Case Study from Himalayan Expressway

National Highways (NH) carry the major portion of the total traffic in India. Road safety on NH is therefore of paramount importance. In the present study, a road safety audit has been performed for a 4-lane NH using Star Rating method. ViDA software developed by International Road Assessment Programme (iRAP) is used for finding the Star Rating of the road sections. This safety rating has been determined for four road user types: Vehicle occupant, Motorcyclist, Pedestrian and Bicyclist. The purpose of the study is to measure the level of road safety and lower the severity level by proposing countermeasures. The case study is a five Kilometre (km) section of NH-5 from Sanwara toll plaza to Jabali in the state of Himachal Pradesh in India. Encroachment on the land, roadside activities, insufficient infrastructure, imperfections in the geometric design, and non-motorized access were some of the severe safety flaws identified through the study process. The Star Rating results indicated that among all the road user types, the vehicle occupant is much safer than the others.

Incremental Learning of Deep Neural Network for Robust Vehicle Classification

Existing single-lane free flow (SLFF) tolling systems either heavily rely on contact-based treadle sensor to detect the number of vehicle wheels or manual operator to classify vehicles. While the former is susceptible to high maintenance cost due to wear and tear, the latter is prone to human error. This paper proposes a vision-based solution to SLFF vehicle classification by adapting a state-of-the-art object detection model as a backbone of the proposed framework and an incremental training scheme to train our VehicleDetNet in a continual manner to cater the challenging problem of continuous growing dataset in real-world environment. It involved four experiment set-ups where the first stage involved CUTe datasets. VehicleDetNet is utilized for the framework of vehicle detection, and it presents an anchorless network which enable the elimination of the bounding boxes of candidates’ anchors. The classification of vehicles is performed by detecting the vehicle’s location and inferring the vehicle’s class. We augment the model with a wheel detector and enumerator to add more robustness, showing improved performance. The proposed method was evaluated on live dataset collected from the Gombak toll plaza at Kuala Lumpur-Karak Expressway. The results show that within two months of observation, the mean accuracy increases from 87.3 % to 99.07 %, which shows the efficacy of our proposed method.

Traffic operations at mainline toll plazas

Traffic operations at mainline toll plazas

Optimizing guidance signage system to improve drivers’ lane-changing behavior at the expressway toll plaza

Although ETC (Electronic Toll Collection) has been widely implemented in vehicles in China in recent years, the channel guidance signage system on expressways has not been updated accordingly. Late lane-changing occurs when drivers are confused about the correct channel to enter, leading to increased crash risks and traffic congestion in front of the toll. The paper aims to optimize the current guidance signage systems, given the high proportion of ETC vehicles on Chinese expressways, and evaluate its effects on the drivers’ lane-changing behavior when passing through the expressway toll channels. A driving simulator experiment was conducted to test four scenarios: Original sign plan, Partial Manual Toll Collection (MTC) sign plan, Complete MTC sign plan and Complete MTC sign with Voice warning plan. Forty participants with a valid driver's license completed the four scenarios, and their behavior performances (e.g., decision-making of lane-changing, response time, average speed and deceleration) in the main lane in front of the toll booth were analyzed. The results showed that compared to the Original sign plan and Partial MTC sign plans, the Complete MTC sign plans (with and without voice warning) played a significant role in improving the MTC vehicle drivers’ lane-changing behaviors. The improvement included earlier initiated lane-changing, shortened response time, lower deceleration rate and extended lane-changing duration distance. The findings of this study have important implications for expressway designers and relevant management departments to optimize the current guidance signage and enhance traffic safety and efficiency at the toll plaza.

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.

Factors affecting particulate matter levels near highway toll plazas in India

Toll plazas are expected to have elevated levels of particulate matter (PM). However, this study through simultaneous measurements at two kerbside highway locations, reveals that PM concentration is higher at around 500 m from the toll plaza. This may be due to higher particulate emissions from vehicles while accelerating/ decelerating mode. Real-world driving approach was adopted using onboard emission monitoring instruments to find particle number concentration in the exhaust during different operating conditions. Subsequently, dispersion analysis was done using US EPA’s AERMOD, which complied with the measurements. Further, relationship between PM levels with traffic and meteorology was also investigated and found that traffic flow had a significant positive effect on PM. Measurements at toll plazas with different geometries divulged that staggered geometry plazas are expected to have highest PM concentration. Lastly, the analysis of PM ratios revealed that contribution of exhaust emissions in overall emissions increases near the toll plaza.

Addressing unobserved heterogeneity at road user level for the analysis of conflict risk at tunnel toll plaza: A correlated grouped random parameters logit approach with heterogeneity in means

Toll plaza is a designated area of controlled-access roads like expressway, bridge, and tunnel for toll collection. A number of toll booths are often placed at the toll plaza accommodating high passing traffic and multiple payment methods. Traffic and safety characteristics of toll plazas are different from that of other road entities. Different conflict risk indicators, which are usually longitudinal, have been adopted for real-time safety assessment. In this study, correlated grouped random parameter logit models with heterogeneity in the means are established to capture the unobserved heterogeneity, with additional flexibility, at road user level for the association between conflict risk and influencing factors. In addition, modified conflict risk indicator is developed to assess the safety of diverging, merging, and weaving movements of traffic, with which vehicles’ dimensions (width and length), and longitudinal and angular movements are considered. Also, prevalence and severity of both rear-end and sideswipe conflicts are assessed. Results indicate that toll collection type, vehicle’s location, average longitudinal speed, angular speed, acceleration, and vehicle class all affect the risk of traffic conflicts. Furthermore, there are significant correlation among the random parameters of severe traffic conflicts. Proposed analytic method can accommodate the conflict risk analysis for different conflict types and account for the correlation of unobserved heterogeneity. Findings should shed light on appropriate remedial measures like traffic signs, road markings, and advanced traffic management system that can improve the safety at tunnel toll plazas.