Manual Toll Collection Research Articles

WITHDRAWN: Alert message based automated toll collection and payment violation management system using smart road side units

Abstract In the current scenario, Automated Toll Collection system plays a significant role in smart transportation for traffic management. Now a days, vehicle drivers and passengers spend their valuable time at the toll plaza as it is required to stop at the toll plaza and pay the toll amount, eventually, causes the cumulative effect of queuing up vehicles near the toll plaza. This situation highly increases the traffic congestion, pollution, long delays and also increases travel time of the passengers. Aimed at addressing this difficulty, in this study, a novel approach is proposed for automatic toll collection and toll violation management system. This paper presents the complete methodology of alert message based automatic toll payment collection and payment violation management system using smart Road Side Units (RSUs) and RFID reader, and thereafter, it presents the operations to be carried out at the toll plaza and by RSUs and also calculates the time required to cross the toll plaza by the vehicles with successful/unsuccessful payment. As vehicle traffic would be heavy in peak hours, handling manual toll collection method may cause queuing up vehicles at toll plaza, and for addressing this issue, in our proposed system, a novel methodology of fully automatic with completely man-free and barricade-free system is discussed and also toll violation management process is presented to perform necessary action against the vehicle that violates the toll plaza. Furthermore, we evaluate the performance of our proposed methodology using network simulator platform and the results are presented.

Effects of the manual and electronic toll collection systems on the particulate pollutant levels on highways in Taiwan

Few studies have quantified the effects of particulate air pollution reductions on electronic toll collection (ETC) and manual toll collection (MTC). Our study evaluated the levels of particulate pollutants, including particulate polycyclic aromatic hydrocarbons (p-PAHs), PM1.0, PM2.5, and PM10, from MTC and ETC systems in booths at a manual/electric hybrid toll station on a highway in Taiwan. A two-week sampling campaign was conducted at the toll station on the first highway in the Taipei metropolitan area. Indoor tollbooth monitoring samples were collected for the ETC and MTC lanes to assess the hourly p-PAH, PM1.0, PM2.5, and PM10 concentrations. The hourly average particle concentration was calculated for different types of toll collection based on 100 vehicles per hour. The average traffic density in the truck and bus lanes or car and van lanes with ETC was significantly higher than that with MTC. The mean p-PAH, PM1.0, and PM2.5 concentrations in the car and van lanes with MTC were higher than those for ETC. The increases in PM1.0 and PM2.5 concentrations per 100 vehicles in the bus and truck lanes with MTC were approximately 2 times greater than those for ETC. ETC technologies serve as a solution to traffic delay problems at toll stations in Taiwan and may more homogeneously reduce the levels of p-PAHs, PM1.0, and PM2.5 particulate pollutants from traffic emissions than the MTC along highways.

Developing Policy Framework of Dynamic Toll Pricing in India

There are 543 toll plazas across the National Highways and State Highways in India and most of them are currently operating under Manual Toll Collection (MTC) system. The Government of India has recently adopted Electronic Toll Collection (ETC) system over MTC system, but, due to the technical constraints of toll plazas, they are either operating with both ETC and MTC systems or with MTC system only. The motive of switching from MTC to ETC is to reduce congestion and delay time. However, due to the fix toll charges for a vehicle type and heterogeneity in traffic mix, the peak hour traffic causes congestion that ultimately returns to enormous delay to users. The present study proposes the policy framework of Dynamic Toll Pricing (DTP) that alleviate the congestion at toll plazas by consisting of shifting traffic volume from peak/congested hours to off-peak/non-congested hours. This type of pricing proved to be one of the methods to control the traffic by elevating the toll in peak hours and thus giving discounts in off-peak hours. Such type of study about dynamic toll is not yet carried out for Indian scenario where traffic is highly heterogeneous. Hence, the main goal of the present study is to evaluate the DTP for the Indian condition and thus to examine the effect of discount and time saving on the shift in peak hour traffic demand. The observations revealed that most of the respondents are willing to shift in the morning peak hour than evening peak hour. The maximum shift was observed for small cars and for 25 % discount in toll charges. Further, the price elasticities of demand are calculated and are found to vary between -0.03 and -1.19 i.e. with 1 percent of discount the traffic volume changes between 0.03 % to 1.19 %. The output of the present study may set up a framework for DTP in India and may be used for analysing the travel choice behaviour models in future studies.

Expressway Exit Traffic Flow Prediction for ETC and MTC Charging System Based on Entry Traffic Flows and LSTM Model

The Expressway (controlled-access highways) of China is the longest in the world and plays an important role in people’s daily life. Accurate short-term traffic prediction is essential for travel schedule and active traffic management. There are two coexisting charging systems for expressway in China, Electronic Toll Collection (ETC) and Manual Toll Collection (MTC), which have different passing capacity and variation pattern. In this work, we demonstrate that the exit traffic flow prediction at Shanghai Xinqiao toll station using entry traffic flows from multiple close-related stations with Long Short-Term Memory (LSTM) model. Based on the origin-destination (OD) traffic data of a month, we present a new method to predict the exit station’s traffic flow in the future 5 minutes. After deleting abnormal data, we select 12 of the 109 entry toll stations for the experiment. The traffic flow of these 12 entry stations account for 86% of the total exit traffic flow. This method uses the spatial-temporal matrix to deal with different three scenes that are ETC and MTC charging systems individually, the mix of ETC and MTC. We use the LSTM model with various lengths of flow sequence and amounts of hidden layer neurons for three different scenes. Lastly, we validate our model and carefully select the hyperparameters for better prediction accuracy by three evaluation metrics. The experimental results demonstrate that predicting the ETC is the best in the three scenes.

Spatio-temporal variability in black carbon concentrations at highway toll plaza: Comparison between manual and electronic toll lanes

The quantification of the differences in the magnitudes of black carbon (BC) concentrations between electronic and manual toll lanes is necessary to understand the impacts of toll plazas to air pollution. This study investigated the space-time distribution of BC concentrations and compared the BC pollution profiles between traffics and toll collection lanes of an urban highway toll plaza in Shanghai. Experiments were carried out between August 15 and August 22, 2019. The mean BC concentrations at east-westbound manual toll collection (MTC) lanes were 17.8 and 14.8 μg m−3, respectively, while the counterpart values for the electronic toll collection (ETC) lanes were 7.7 and 9.2 μg m−3, respectively. Moreover, parallel measurements at urban background site yielded mean BC level ranges between 3.4 and 2.8 μg m−3. The traffic volumes through the east-westbound ETC and MTC lanes were estimated as 489 and 347 vehicles h−1, respectively. Although ETC-lane traffic was ~1.4 times higher than that of the MTC lanes, owing to the toll collection method, the BC concentrations at the MTC lanes were 1.6–2.3 times higher than those at the ETC lanes and 4.8–5.9 times higher than that of the urban background site. As per multivariate regression analysis, it was found that the variations in BC concentrations were caused by traffic emissions and influenced by the local background BC levels, influences of wind speed and humidity were also determined. This study found that at highway toll plazas, when compared with MTC lanes, ETC lanes can contribute to reducing BC emissions by ~50%.

Toll Plaza Lane Choice and Lane Configuration Strategy for Autonomous Vehicles in Mixed Traffic

Toll plazas are one kind of highway node that pose a challenge to the flow of autonomous vehicles (AVs). Some toll roads have open road tolling (ORT), which makes it easier and more efficient for AVs, but most toll plazas do not have ORT. The authors developed a decision model to assist AVs in choosing the right lane that involves two main indicators, the rod speed (SRi) and the decision-making value (DSRi). The decision model was applied to a six-lane toll plaza with manual toll collection (MTC), electronic toll collection (ETC), and electronic toll collection for AVs toll types. The suitable lane configurations for the varying percentages of AVs in traffic were as follows: at 10% AV, the optimal lane configuration was 4 MTC and 2 ETC/AV (4M2EA), at 30% AV it was 3M3EA, at 40%–60% AV it was 3M2EA1A, and at 70% AV it was 2M2EA2A. Thus AVs should share toll lanes with ETC manned vehicles before the population of AVs reaches 30%; after that dedicated lanes may be introduced. It was also concluded that a 10% increase in AVs reduces delays by 9% if the populations of ETC and MTC vehicles are equal.

Effect of Implementing Electronic Toll Collection in Reducing Highway Particulate Matter Pollution.

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

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.

Comparison of different models for evaluating vehicle collision risks at upstream diverging area of toll plaza

Toll plazas with both Electronic Toll Collection (ETC) lane(s) and Manual Toll Collection (MTC) lane(s) could increase crash risks especially at upstream diverging areas because of frequency lane-change behaviors. This study develops the logistic regression (LR) model and five typical non-parametric models including, K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), Support Vector Machines (SVM), Decision Trees (DT), and Random Forest (RF) to examine the relationship between influencing factors and vehicle collision risk. Based on the vehicle trajectory data extracted from unmanned aerial vehicle (UAV) videos using an automated video analysis system, the unconstrained vehicle motion’s collision risk can be evaluated by the extended time to collision (ETTC). Results of model performance comparison indicate that not all non-parametric models have a better prediction performance than the LR model. Specifically, the KNN, SVM, DT and RF models have better model performance than LR model in model training, while the ANN model has the worst model performance. In model prediction, the accuracy of LR model is higher than that of other five non-parametric models under various ETTC thresholds conditions. The LR model implies a pretty good performance and its results also indicate that vehicle yields the higher collision risk when it drives on the left side of toll plaza diverging area and more dangerous situations could be found for an ETC vehicle. Moreover, the vehicle collision risks are positively associated with the speed of the following vehicle and the angle between the leading vehicle speed vector and X axis. Furthermore, the results of DT model show that three factors play important roles in classifying vehicle collision risk and the effects of them on collision risk are consistent with the results of LR model. These findings provide valuable information for accurate assessment of collision risk, which is a key step toward improving safety performance of the toll plaza diverging area.

Dynamic Toll Charge using openCV and Spark

There are many implementations of intelligent transportation system which is mandatorily required to curb the rising traffic in metropolitan cities. One such implementation is dynamic toll generation which reduces the time taken to pay toll at the toll gates compared to the relatively old method of manual toll collection, although it is still being implemented. One crucial factor to curb traffic and reduce pollution in the cities would be to charge toll according to the seat occupancy in the four wheeler i.e. commuters who use the vehicle appropriately will be charged less and others who use the vehicle luxuriously will be charged more. The system thus implemented produces the toll based on the seat occupancy and the data stored in the databases when the RFID is flashed is used for further analysis.

Use of Microscopic Traffic Simulation Software to Determine Heavy-Vehicle Influence on Queue Lengths at Toll Plazas

Highways and expressways provide support for the local, regional, and national transportation of services and goods. Moreover, they are indispensable to economic activities as modern lifestyle would be impossible without them. Activities related to work, education, shopping, tourism, and social are generating a demand for trips. Furthermore, the presence of toll plazas at expressways slows down traffic, thus creating traffic congestion during rush hour. Malaysian toll plazas are considered conventional toll collection, which is manual and the most common toll collection method. Manual toll collection is usually the cause of congestion related to the delay experienced by drivers, toll collection procedure, and operators at the manual toll lanes. This paper aims to examine the effect of the percentage of heavy vehicles on the performance of toll plazas in terms of the queue length using the microscopic traffic simulation model called VISSIM. The findings indicate that the percentage of heavy vehicles in traffic flow significantly affects queue lengths at toll plazas.

Examining traffic conflicts of up stream toll plaza area using vehicles’ trajectory data

Despite the recognized benefits of electronic toll collection (ETC) system as an important part of toll plaza area, the mixed traffic of electronic toll collection (ETC) vehicles and manual toll collection (MTC) vehicles in the toll plaza diverging area are considered risky to vehicles, in which complex diverging and crossing behavior of vehicles would increase the collision risks. Therefore, it is vitally important to investigate the vehicle collision risk in the up stream toll plaza area. Video data are collected from a typical toll plaza in Nanjing, China, and vehicle trajectory data are extracted using an automated analysis system based on OpenCV. An extended Time-To-Collision (TTC) is proposed to evaluate the vehicle collision risk. Subsequently, the different effects on vehicle collision risk of vehicles with different toll collection types, target lanes and locations are compared. Furthermore, the random parameters logistic model is developed to investigate the effects of explanatory factors on the collision risk of vehicles diverging or adjusting their lane position. The results suggested that the MTC vehicles have the highest collision risk in the toll plaza diverging area and there are significant different effects on collision risk among vehicles with different target toll collection lanes. Further, more dangerous situations could be found for a vehicle if it is closer to the toll collection lanes and surrounded by heavy traffic. It is also confirmed that mixed traffic with MTC and ETC vehicles could increase the crash risk in the toll plaza diverging area. It is expected that the findings could help engineers and operators select the appropriate engineering and traffic control solutions to enhance the safety at the toll plaza diverging area.

Sustainable industrial systems within kernel density analysis of artificial intelligence and industry 4.0

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.

Impact of Electronic Toll Collection System on Energy Saving and CO2 emission: A Case Study of Passenger Cars in Thailand

Traffic problems have been a long-standing issue for Thailand, although many measures have already been implented to solve them. Electronic Toll Collection system (ETC) is one of those measures used for reducing the traffic problems at the front of checkpoint on the expressway. However, there are no research studies on the effect of ETC on expressway transportation in Thailand. The objective of this study was to evaluate the impact of the four main factors (time, speed and acceleration, fuel consumption, and CO 2 emission) on the ETC system compared to the Manual Toll Collection (MTC). In addition, four scenarios of applying ETC were analyzed to evaluate the potential of energy saving and CO 2 emission in Thailand. In this study, Ram Inthra Toll Plaza, Bangkok was selected as a case study, and the car model Nissan March year 2010 was selected as the representative vehicle. Results found that time consumed for paying the fee at ETC was only two seconds which is faster than MTC about six times. Using ETC toll can reduce fuel consumption by up to 4 milliliter/trip and reduce CO 2 emission about 9.7% compared with MTC. It is estimated that Thailand could reduce fuel consumption up to 1,262,471 liter/year with the reduction of 2,754 ton CO 2 eq/year, when ETC toll is applied to all the expressways of the country.

Safe Operation Guidelines for Electronic Toll Collection Systems: A Case Study in Korea

In this paper, we present safe operation guidelines for electronic toll collection (ETC) systems with both ETC booths and manual toll collection (MTC) booths. The guidelines are based on an analysis of vehicle speeds and trajectories that were obtained with a speed gun and a video recording method at six expressway tollgates in Korea. From the analysis results, two risk factors for the operation of the ETC systems were identified: speed differences between ETC-tagged vehicles and other vehicles with respect to locations, and lane changes as a result of entering the wrong lane. The guidelines suggest a method to calculate the safe distance necessary for lane changing and a lane configuration method to reduce accident risks resulting from speed variance. Although the guidelines are based on a case study in Korea, the approach could be useful for operation agencies of other ETC systems in strategic planning to reduce accident risks.

Fuel Consumption and Vehicle Emission Models for Evaluating Environmental Impacts of the ETC System

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.

Dynamic simulation of energy consumption in mixed traffic flow considering highway toll station

An improved model of energy consumption including toll station is presented in this paper. Using the model, we study the influences of mixed ratio, the idling energy consumption of vehicle, vehicle peak velocity, dwell time and random deceleration probability on energy consumption of Electronic Toll Collection or Manual Toll Collection mixed traffic flow on single lane under periodic condition. Simulating results indicate that the above five parameters are all increasing functions of total energy consumption, in which the idling energy consumption represents the major amounts with the increase of mixed ratio and occupancy rate. Thus, the existence of toll station has significant effect on the energy consumption of mixed traffic flow.

Allocation Criteria for Increasing Electronic Toll Collection Gates on Freeways Determined Using Simulation Analysis

In Taiwan, the electronic toll collection (ETC) system for freeway toll plazas that commenced operation in February 2006 will operate on all freeways by 2014. When the ETC system was first implemented, each toll plaza was allocated 1 small-vehicle ETC gate and 1 large-vehicle ETC gate. Determining how to allot the gates to ETC and manual toll collection when the number of ETC vehicles increases is crucial. By conducting a simulation using the toll plaza simulation model, the authors observed that 1 ETC gate for passenger cars had to be added to the small toll plaza when the traffic exceeded 1,450 vehicles/hr/gate. The medium and large toll plazas required 1 more ETC gate for passenger cars when the traffic exceeded 1,600 vehicles/hr/gate, whereas 1 non-ETC gate for passenger cars could be removed.

Investigating the impact of highway electronic toll collection to the external cost: A case study in Taiwan

The implementation of electronic toll collection (ETC) on highways aims to reduce toll transaction time and thereby increase service capacity. In this paper, considering the separation of manual toll collection (MTC) and ETC lanes, a method is developed to estimate the carbon dioxide (CO2) emissions, transaction time, and the associated external cost incurred by vehicular traffic at four toll plazas on a northern-central highway in Taiwan. Three vehicle types are considered: passenger cars, buses and trucks. Results show that the CO2 emissions were reduced by 12.4% as the number of ETC lanes for all 4 toll plazas increased. The reduction of external costs fell by 60.1% in terms of value of transaction time, which will arguably lead highway authorities to actively promote ETC

고속도로 영업소의 자동 요금 징수 시스템 도입에 따른 소형 경유 화물트럭의 배출가스 저감 효과 분석

Electronic Toll Collection System (ETCS), so called "Hi-Pass" in Korea, has improved traffic flow at toll gate of highways. It is known that the improvement of traffic flow should reduce air pollutants and <TEX>$CO_2$</TEX> from vehicles. In this study, real driving emission of a light duty truck with Portable Emission Measurement System(PEMS) has been measured to evaluate the emission reduction effect due to ETCS. The correlations between driving variables and emissions have been analyzed to verify its effect on traffic flow improvement and emission reduction at toll gate. We considered average vehicle speed, Relative Positive Acceleration (RPA), and the distance of queue as driving variables. Compared to passing Manual Toll Collection System (MTCS) lane without queue, ETCS was able to reduce 38.7% of <TEX>$NO_x$</TEX>, 21.6% of soot, and 27.7% of <TEX>$CO_2$</TEX>. The results showed that the higher the average vehicle speed, the lower RPA and no queue in ETCS contributed to the emission reductions. Linear equation models with RPA and queue have been established by the multiple linear regression method. The linear models resulted in the higher coefficient of determination than those with only average vehicle speed used for establishing vehicle emission factors.