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.

Quad-Port Multiservice Diversity Antenna for Automotive Applications

A quad-element multiple-input-multiple-output (MIMO) antenna with ultra-wideband (UWB) performance is presented in this paper. The MIMO antenna consists of four orthogonally arranged microstrip line-fed hexagonal monopole radiators and a modified ground plane. In addition, E-shaped and G-shaped stubs are added to the radiator to achieve additional resonances at 1.5 GHz and 2.45 GHz. The reliability of the antenna in the automotive environment is investigated, with housing effects taken into account. The housing effects show that the antenna performs consistently even in the presence of a large metal object. The proposed MIMO antenna has potential for various automotive applications, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-everything (V2X), intelligent transport system (ITS), automatic vehicle identifier, and RFID-based electronic toll collection.

The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data

To overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of expressways is proposed. Firstly, the characteristics of the ETC gantry data are analyzed, and then data are cleaned and reconstructed, after which an algorithm is proposed for constructing a vehicle travel speed data set. Secondly, the speed feature vector model of the road section is established by taking the relationship among the speed distribution feature, time domain feature, and the maximum speed limit of the road section into consideration. Then, a data supplement algorithm is constructed to solve the problem of the imbalance of data samples. Finally, the combined GC-XGBoost classification algorithm is used to train and learn the potential speed limit features, and it is verified through the Fujian Provincial Expressway ETC data and the speed limit information provided by the Fujian Traffic Police. The result shows that the accuracy of the method in the recognition of the maximum limited speed information of the expressway is 97.5%. Compared with the traditional limited speed information recognition and extraction methods, the proposed approach can identify the maximum limited speed information of each section of the expressway more efficiently. It can also accurately identify the dynamic change of the maximum limited speed information, which is able to provide data support for intelligent expressway management systems and map providers.

Assessment of Changes in Toll Fares in Conditions of Increased Traffic Load

The purpose of the study is to assess changes of toll fares used on toll collection points. When toll road is operating in an urban environment, the operator is inevitably faced with the need to adapt intelligent transport system to the conditions of an ever-increasing volume and changing composition of the traffic. Such changes have a direct impact on the capacity of the toll road, in particular at toll collection points. The conducted research is aimed at analyzing the method of reducing the traffic load at the toll collection points during peak hours by making changes to the toll fares aimed at uniform distribution of traffic flow throughout the day. As an example, a toll collection point on the main road direction of the Western High-Speed Diameter toll road was chosen.Materials and methods. A discrete-event simulation model developed in the AnyLogic software was used to assess the quality of operation and throughput of the toll collection point. The software has a sufficient level of detail to reproduce the operation of the toll collection system, and allows managing all the necessary parameters of the system and traffic flow. Analysis of the data obtained from the simulated model experiments was carried out using the statistical package R. Results. As part of the study, the operational characteristics of the toll collection point, in particular its threshold capacity, were determined, and, if it was exceeded, the length of the emerging queue was determined. Taking into account the operator’s risks arising from the formation of a traffic congestion, an approach was proposed to change the toll fare policy of the toll road by using a more flexible fares based on dividing the day time fare into several time intervals and using increasing coefficients for toll fare when paying for travel during peak hours. Using the example of toll booth of the Western High-Speed Diameter, the increasing coefficients of the cost of travel at a rush hour were considered, and the risks of reducing the operator’s income from toll collection were assessed.Conclusion. Based on the results obtained, an assessment of the effectiveness of the application of measures to change the existing toll fare policy, aimed at optimizing the traffic flow of a toll road, can be carried out. In addition, such an analysis can be used to assess the investment attractiveness of a project, develop a toll fare policy, increase income and other similar tasks. Further research can be aimed at increasing the economic indicators of toll road projects, and developing additional mathematical tools used in the formation of toll fare policy.

Selection of the Optimal Toll Collection System for the Purposes of Sustainable Development of Transport in the Republic of Srpska

Transport system has multiple interactions and multidimensional effects on the environment, by way of, amongst other, land acquisition and urban pollution; on economic development with regard to the GDP growth; as well as on social equity in terms of access, quality of life and health of population. This paper considers the possibility of introducing toll collection in the Republic of Srpska. The goal of the developed model is to increase revenue, which could be directed to the sustainable development of transport in the Republic of Srpska. The selection of a toll collection system has been made taking account of: economic, traffic, technical, organizational and exploitation criteria. Multiple-criteria approach has been applied together with the Analytic Hierarchy Process.

VEHICLE CLASSIFICATION USING THE CONVOLUTION NEURAL NETWORK APPROACH

We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset’s different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic.