Toll Station Research Articles

Economic analysis of expressway building envelope in cold area based on RSM

The DeST-c energy consumption simulation software was used to build the building model based on the toll station and service area building in expressway of Zhangjiakou in the cold area, simulates and calculates the impact of single factor on energy consumption, and carries out economic analysis based on life cycle theory to determine the level of influencing factors. Finally, the BBD test design method and the orthogonal test design method were used to design the test scheme respectively and the economic analysis of the comprehensive thermal performance of the envelope structure, and the optimal energy saving scheme of the comprehensive thermal performance of the building envelope in the cold area was obtained.

Analysis of Traffic Properties of Commuters in a Speed-Limit Corridor with Toll Station under Microscopic Method

AbstractThis study applies the full velocity difference (FVD) model to investigate commuters’ driving process in a speed limit corridor with a toll station and explains how some factors affect the ...

Calculation Model of Preposition Distance of Electronic Toll Collection Signs Based on Lane Changing Behavior

ETC and MTC lanes of China’s hybrid toll stations have various setting modes. When the vehicles passed through the toll stations, they would face a more complicated lane change process. If the ETC sign was set in the appropriate position in advance, the traffic safety in front of the toll stations would be effectively improved. The paper analyzed the process of lane change in 18 scenes by taking one-way three-lane highway at the upstream of toll station with six lanes as an example. Based on the definition of driver’s reaction distance, reading distance and safe distance of action, the theoretical calculation model of ETC sign preposition distance was established. It revealed the functional relationship between ETC lane layout schemes and sign preposition distance, and explored the reasonable setting position of the ETC sign in the full scenes of the lane layout. Finally, a case study of Nanjing toll station on Shanghai-Nanjing Expressway was carried out.

Lane Work-Schedule of Toll Station Based on Queuing Theory and PSO-LSTM Model

A reasonable lane work-schedule in each time period can not only guarantee the traffic efficiency of toll stations, but also reduce the operating cost of toll stations. This paper proposes a comprehensive solution for lane work plan. Firstly, the average queue length is selected as a good index for measuring the congestion of toll station. And then, based on the queuing theory, the service level of toll station is divided into four levels according to the relationship between the average queue length and traffic capacity. Secondly, based on the toll data, a toll station congestion prediction model is established with the Long Short-Term Memory model (LSTM) and the particle swarm optimization (PSO) algorithm. In this model, the average queue length, service time and traffic volume are selected as three inputs, the average queue length value of the next hour is the output. Thirdly, on the basis of meeting the secondary level service level of toll stations, the lane work-schedule model is established. Then, the number of lanes opened in each time period can be calculated by using this model and congestion prediction results. Fourthly, considering the two scenarios of weekday and weekend, the effectiveness of the methods proposed in this paper is analyzed and verified with the toll data of the Dongshe, Changfeng, and Linfen toll stations in Shanxi Province. Finally, based on operating costs analysis, the results show that the proposed solution could effectively realize the reasonable work-schedule of the toll station.

Optimizing the Site Selection of Payment Stations Based on P-median Mathematical Model

Site selection is one of the classic problems in operations research. In this research, starting from a mathematical modeling example, a model was established to solve the site selection problem of 6 toll points in 52 cells. Taking the shortest distance between the residential area and the toll station as the objective function, this paper introduced 0-1 variables, established the P-median site selection model, and transformed the residents’ payment query problem into a linear programming problem. The Lingo software was used to solve the problem of positioning the 6 points as 1, 6, 14, 26, 28 and 36. This paper successfully applies the site selection model to the site selection of toll station, which has certain reference value to the site selection in real life

佛开高速取消省界收费站施工组织方案研究

佛开高速取消省界收费站施工组织方案研究

Research on the Method of Determining Highway Truck Load Limit Based on Image Processing

Over-limit transportation is the leading cause of highway pavement diseases and traffic accidents. The Ministry of Transport of China has determined the weight limit for different trucks entering the highway based on the number of truck axles and the coupling method. However, because determining the truck weight limit is more complicated, the current work is mainly done manually by the toll station staff at the expressway entrance, and the recognition speed is slow Cand the recognition result is inaccurate. In response to this problem, we first analyzed and established the relationship between the number of axles and the position distribution, and the truck weight limit. Based on the above, we developed a circle detection method with an improved Hough and CURE algorithm as the core to identify truck wheel axles. We collect 100 test images at the expressway entrance and use 50 of them to perform detection experiments to determine the radius step, angle step, and the maximum and minimum circle values during the detection process. After using the entire data set, comparing the hough algorithm, the improved Hough algorithm, and our proposed method, the results show that our proposed method has higher accuracy and efficiency.

Study on identification and classification of hidden dangers in highway toll stations based on accident causation theory

Aiming at high safety risk of expressway toll station, based on the theoretical model of accident cause, this paper makes a systematic analysis and correlation test on the unsafe state of object, personal unsafe behaviour, and the imperfection of safety management system within the jurisdiction of expressway toll stations. Through statistical analysis, the types and distribution areas of unsafe physical state, the types and main causes of unsafe behaviours within the jurisdiction of toll stations are identified. The results show that: education and training, risk management and control, hidden dangers, operating procedures, equipments and facilities management, emergency management, etc., have a great impact on the physical safety of highway toll stations; bad driving habits, trouble free mentality, poor safety awareness, lack of safety knowledge are the main reasons for unsafe behaviours. The results of the study have guiding significance for the risk management of toll station.

Research on License Plate Image Segmentation and Intelligent Character Recognition

With the accumulation of people’s wealth and the improvement of purchasing power, more and more people are buying cars as a means of travel. Walking and cycling of the past have now become a car trip. License plate recognition technology is especially important in intelligent transportation systems. It has been widely used in large shopping malls or supermarket parking lots, highway toll stations, speeding violation supervision and other fields. However, the accuracy and efficiency of license plate image recognition are insufficient. To solve the above problems, we propose a license plate character recognition method based on local HOG and layered LBP feature fusion from the perspectives of image pre-processing, license location, characters’ segmentation and recognition. First, pre-processing the license image area by highlighting the license plate image; then, the license plate is positioned based on wavelet decomposition and brightness moment; next the tilted license plate image is corrected, the license plate frame is adjusted, and characterization is performed by using the improved projection method based on the fact that the projection of the character is a single peak or a double peak. Finally, the local HOG and hierarchical LBP feature fusion methods are used to identify the license characters. The results show that the license plate’s character recognition rate of the proposed method reaches 99.71%, and the time taken is small. This not only improves the character recognition rate, but also saves recognition time. The results show that the method has important practical significance in license plates’ recognition.

PM2.5 concentrations in the greenbelt near the Lin’an toll station of the Hang Rui expressway and related influencing factors

Expressways in China are developing rapidly, as is traffic pollution, which is one of the major sources of urban pollution. In this study, we chose the greenbelt in the idle zone near the Lin’an toll station along the Hang Rui expressway as our sampling area. Five points in the sampling area along Qianjin road were marked vertically at distances of 0, 15, 30, 45 and 60 m to monitor concentrations of PM2.5 and learn the varying patterns of these concentrations and influencing factors. The results showed that in spring (March, April and May), the average PM2.5 concentrations in the greenbelt were 32.56 ± 22.51, 77.71 ± 32.11 and 64.15 ± 29.00 μg m–3, respectively. The ranking of concentrations at different monitoring points in the same period was 0 > 15 > 60 > 30 > 45 m. The average concentrations in winter (November and December 2017, and February 2018) were 33.56 ± 9.34, 60.78 ± 17.67 and 124.71 ± 43.19 μg m–3, respectively. However, the ranking of concentrations at different monitoring points in the same period revealed some differences. Except at 0 m, the concentrations of PM2.5 in the other four positions were higher in winter than in spring. The reduction rate at 45 m reached its maximum in both spring and winter. PM2.5 concentrations were significantly correlated with meteorological factors, the structure of the plant community and traffic flow. PM2.5 concentrations were negatively correlated with temperature, positively correlated with relative humidity and was not significantly correlated with wind speed. The correlations of PM2.5 concentrations with the canopy density and degree of porosity differed greatly due to different seasons, and concentrations were significantly correlated with the amount of traffic flow, especially when there were large trucks.

Real-time Intraday Traffic Volume Forecasting – A Hybrid Application Using Singular Spectrum Analysis and Artificial Neural Networks

The present paper provides a comparative evaluation of hybrid Singular Spectrum Analysis (SSA) and Artificial Neural Networks (ANN) against conventional ANN, applied on real time intraday traffic volume forecasting. The main research objective was to assess the applicability and functionality of intraday traffic volume forecasting, based on toll station measurements. The proposed methodology was implemented and evaluated upon a custom developed forecasting software toolbox, based on the software Mathworks MatLab, by using real data from Iasmos-Greece toll station. Experimental results demonstrated a superior ex post forecasting accuracy of the proposed hybrid forecasting methodology against conventional ANN, when compared to performance of usual statistical criteria (Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, Coefficient of Determination R2, Theil's inequality coefficient). The obtained results revealed that the hybrid model could advance forecasting accuracy of a conventional ANN model in intraday traffic volume forecasting, while embedding hybrid forecasting algorithm in an Intelligent Transport System could provide an advanced decision support module for transportation system maintenance, operation and management.

Atmospheric particle retention capacity and photosynthetic responses of three common greening plant species under different pollution levels in Hangzhou

The retention capacities and photosynthetic response to different-sized particulate matter in plants are very important indicators for urban green plant species selection. A large number of studies have been reported on the particulate matter retention capacities of plants, but few reports have been reported on the photosynthetic response of plants after particulate matter retention. In this study, we investigated the capacities of Rhododendron x pulchrum Sweet, Osmanthus fragrans Lour. and Photinia x fraseri Dress to retain atmospheric particles of different sizes and their photosynthetic gas exchange capacity in autumn and winter of 2017 at a freeway toll station and on a university campus. The results showed that the retention capacities of the three plant species were in the order R. pulchrum > O. fragrans > P. fraseri. The total suspended particles (TSPs) absorbed by R. pulchrum at the freeway toll station was the highest (autumn: 371.22 μg cm−2; winter: 177.11 μg cm−2), while the TSPs absorbed by P. fraseri at the campus was the lowest (autumn: 36.13 μg cm−2; winter: 41.50 μg cm−2). Plant surface retention (sPM) accounted for more than 60% of TSPs. Large particulate matter (10–100 μm) in sPM and wPM accounted for 52.17–9.60% and 45.36–72.20%, respectively. In winter, the proportion of fine particulate matter (0.2–2.5 μm) of sPM was significantly higher than that in autumn. Photosynthetic gas exchange capacity of plants, especially stomatal conductance (Gs), was significantly reduced by particulate pollution. There was a negative correlation between plant dust retention and photosynthetic gas exchange capacity. The amount of PM2.5 retained by plants was negatively correlated with the net photosynthetic rate (Pn). The photosynthetic gas exchange capacity of P. fraseri was the least affected under different particulate pollution levels, and this species was best able to adapt to growing in a more polluted environment.

Pollution Characteristics of Heavy Metals in PM2.5 Near Highway

In this study, we evaluate the pollution characteristics of heavy metals in particulate matter with diameters less than 2.5 μm (PM2.5) near highways. Three rounds of cluster sampling of PM2.5 were conducted on three highways, Changzhang, Changtong, and Wenhou, in peri-urban areas near Nanchang from March to August 2018. The sampling sites included service areas, toll stations, tunnels, and areas near the highway. The concentrations of six heavy metals including Cu, Zn, Pb, Cd, Cr, and Ni in PM2.5 were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). The pollution and distribution of heavy metals in PM2.5 near the highway were analyzed, and that pollution characteristics and the level of possible ecological jeopardy were assessed by using the Geoaccumulation Index and Potential Risk Index methods. No significant difference was observed in PM2.5 or in heavy metals in PM2.5 along highways with different traffic flow, but they differed significantly in among highway settings in the following order:super-long tunnels > long tunnels and area near the highway > service areas and toll stations. The heavy metal concentration in highways decreased in the following order:Zn (3.8 μg·m-3) > Pb (10.2×10-2 μg·m-3) > Cr (6.8×10-2 μg·m-3) > Cu (3.5×10-2 μg·m-3) > Ni (1.5×10-2 μg·m-3) > Cd (0.1×10-2 μg·m-3). In accordance with the influence of temperature and precipitation, PM2.5 and heavy metals in PM2.5 showed significant variations among the monitoring months. The PM2.5 concentration had a significant negative correlation with atmospheric temperature. We observed that PM2.5 concentration was significantly lower from May to August than from March to April. The Zn concentration in PM2.5 was more significant from May to August than from March to April. Pearson analysis showed a significant positive correlation between Zn in PM2.5 with atmospheric temperature because elevated temperatures could aggravate wear and tear and metallic corrosion, which then prompts the emission of Zn. According to the Geoaccumulation Index and Potential Ecological Jeopardy Index, the level of pollution associated with heavy metals of PM2.5 manifested in the following order:Zn and Cd > Pb > Cu > Ni and Cr. The pollution and degree of jeopardy associated with Zn and Cd were the most severe in the assessment criteria; therefore, the pollution by these elements and the sources of traffic should be noted in air pollution control plans. Super long tunnels, long tunnels, and areas near highways showed greater levels of pollution and higher potential ecological jeopardy than service areas and toll stations. The degree of pollution in densely populated service areas and toll stations was consistent across partially urban areas.

Geolocation Process to Perform the Electronic Toll Collection Using the ITS-G5 Technology

Recent research in intelligent transportation system focus on different possible use cases. Among them are the payment applications with cooperative intelligent transport system (C-ITS) equipment. In this paper, we deal about the tolling application performed with the C-ITS equipment. These latter use the ITS-G5 technology, the Roadside Unit (RSU) and the on-board unit (OBU) with features specified by the standardization Institute ETSI. To perform this service, we highlight two mains requirements: how to have a reliable geolocation of the vehicle when it crosses the tollgate and how to secure the communication during the transaction process. In this paper, we will address the methods that is propose to solve the issue of geolocation. The proposed method takes advantage of the communications data. It uses the principle of Differential - GPS mixed with Kalman filtering and extended Kalman filtering applied to the GPS and CAN bus measurements received by the RSU from the connected vehicles. The kinematic of the vehicle is taken into account to choose the suitable system model. Here as novelties, we discuss about the whole procedure to perform the geolocation process during the tolling service and we have results when we apply the dynamic model according to the real behavior of the vehicle when approaching and crossing the toll station.

Road traffic forecasting — A hybrid approach combining Artificial Neural Network with Singular Spectrum Analysis

The paper presents a comparison of a hybrid methodology which combines Singular Spectrum Analysis (SSA) with Artificial Neural Networks (ANN) against conventional ANN, applied on time series analysis and forecasting of road traffic volume. The main research objective was to develop a short-term forecast of daily traffic volume at toll stations across the Greek National Highway Network. The proposed methodology was implemented and evaluated upon a custom developed integrated forecasting software, based on the Mathworks MatLab platform. Experimental outcomes on daily data, from specific toll stations, demonstrate a superior prediction accuracy of hybrid SSA–ANN forecasting methodology against conventional ANN, when compared to performances of statistical criteria such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Coefficient of Determination (R2). A comparison of results revealed that the SSA–ANN hybrid model could improve the forecasting accuracy of the conventional ANN model in the case of daily traffic volume forecasting. An Intelligent Transport System with embedded hybrid SSA–ANN forecasting algorithm could manage and analyze big data traffic volume time series in real time, providing an advanced decision support system for transportation system management and maintenance, while it would enable proactive decisions to mitigate the economic and environmental impacts of traffic congestion.

Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway

To support the rapid growth of demand in passengers and freight, separating trucks and passenger-cars is a potential solution to improve traffic efficiency and safety. The primary purpose of this paper is to comprehensively assess the multilane separate freeway at Huludao Toll Station in Liaoning Province, China. Based on the configuration and segmentation of the freeway near a toll station, a six-step guidance strategy is designed to adapt to the separate organization mode. Five conventional traffic scenarios are designed in the Vissim platform for comparative analysis between different guidance strategies. To investigate the vehicle-to-infrastructure (V2I) environment, a microscopic testbed is established with cooperative car-following and lane-changing models using the MATLAB platform. The numerical simulation results show that the guidance strategy significantly improves efficiency and safety, and also reduces emissions and fuel consumption. Meanwhile, pre-guidance before toll channels outperforms the scenario only applied with guidance measures after toll plaza. Compared to conventional conditions, the assessment of pollutant emissions and fuel consumption also embodies the superiority of the other five scenarios, especially in the sections of toll plaza and channels with the lowest efficiency and safety level. Generally, all indexes indicate that the cooperative V2I technology is the best alternative for multilane separate freeways.

RESEARCH ON WIND PERFORMANCE AND FIELD EXPERIMENT OF LARGE SCALE COMPLEX SURFACE SPACE TRUSS WITH STEEL PIPE

The wind-induced performance response of large-span truss curved roofs is extremely complex and changes obviously under wind load. This paper has taken the large-span steel roof of Liu Zhaike highway toll station as an example to analyze by both numerical simulations and field tests of responses of the steel canopy under wind load. In this case, simulated analysis results using finite element software were calibrated and verified by the field test results. In addition, a new method of large structure field testing was proposed which obtained the internal force and displacement of the canopy structure. Moreover, this paper analyzed and determined the actual stress state of the rectangular pipe truss. Finally, the safety condition of the roof was evaluated based on the monitoring data and the simulation of the finite element model. And the analysis methods provides references for similar engineering field tests, as well as guidance for the operation and maintenance for this project.

Containment control of directed networks with time-varying nonlinear multi-agents using minimum number of leaders

In this paper, the problem of containment control with minimum number of leaders in arbitrary directed networks consisting of time-varying nonlinear multi-agents is investigated. Unlike the existing containment control problem with redundant leaders in special networks, we consider the problem with minimum number of leaders in arbitrary directed networks. We show that the problem of finding the minimum number of leaders can be converted into a minimum spanning tree problem by introducing a toll station connecting with each agent. By employing the developed Edmonds’ algorithm, the minimum number of leaders is located at the roots of each tree in the obtained spanning forest. This situation allows us to achieve containment control in a distributed manner. On the basis of this situation, a distributed protocol is developed to address the containment control of multi-agent systems with time-varying nonlinear dynamics. Simulation results are provided to illustrate the efficiency of the proposed methodology. Our work makes it possible for studying and extending application of containment control problems in various complex networks.

Incident Detection Method of Expressway Based on Traffic Flow Simulation Model**Supported by the National Natural Science Foundation of China under Grant Nos. 71871130, 71471104, 71771019, 71571109; the University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; and the Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236

The expressway traffic incidents have the characteristics of high harmful, strong destructive and refractory. Incident detection can guarantee smooth operation of the expressway, reduce traffic congestion and avoid secondary accident by informing the accident, detection and treatment timely. In this paper, an incident detection method is proposed using the toll station data that takes into account the traffic ratio at the entrances and crossway in the network. The expressway traffic simulation model is improved and a simulation algorithm is established to describe the movement of the vehicles. A numerical example is experimented on the expressway network of Shandong province. The proposed method can effectively detect the expressway incidents, and dynamically estimate the traffic network states so as to provide advice for the highway management department.

WAVE-Based Short-Range Vehicular Localization Through Vector Match

Precise and real-time position information are critical for an enforcement, autopilot, or navigation system at a toll station. However, global positioning system (GPS) has insufficient accuracy and low sampling rate. In this paper, a short-range vehicle localization algorithm is proposed to supplement the distance gap of the GPS. A normalized received signal strength indication (RSSI) sequence takes the place of RSSI at position evaluation in which problems of low signal noise ratio are alleviated. A position similarity degree algorithm is proposed to mitigate the low variability of a fingerprint, a seamless localization is achieved. A filter is designed to cut off the dataset of remote calibration points; the multipath effect is mitigated. Finally, the experiments verify the suitability of accuracy and execution time for enforcement and autopilot, and the insignificant effect of speed, traffic, and grid size.