Intelligent Transportation Information Research Articles

INNOVATIVE FACTORS IN THE DEVELOPMENT OF TRANSPORT ENTERPRISES

The purpose of the article is to research and analyze innovative factors that affect the development of enterprises in the transport sector based on the selection of key aspects and strategies that contribute to the successful implementation of innovations in the field of transport business. The peculiarities of the action of the main factors at the enterprises of the transport industry have been determined and researched, they include: the use of modern technologies, intelligent transport systems (ITS), environmental innovations, information management and analytics, electronic market platforms, robotics, automation and artificial intelligence, electronic payment systems, sustainability and security, development of ecosystems, self-driving cars and drones, effective management of labor resources. From the position of an integrated approach, all factors generally cover economic, technical, technological, social and environmental aspects. Their impact on the economic development of enterprises is considered through the focus on reducing costs, forming competitive advantages and increasing competitiveness, ensuring social and environmental effects. This is of particular importance for the adaptation and further development of industry enterprises in the conditions of the current military situation and future dynamic changes in the modern world. The study is based on current concepts of innovation and considers the specifics and features of the activities of transport enterprises.

Influence of climatic factors on the implementation of intelligent transport system technologies in the regions of the Far North and the Arctic

Taking into account natural and climatic factors in various regions of the Far North and the Arctic is extremely important for organizing the successful pickup and delivery of various goods and passengers. These factors have a particular impact on the transportation of goods and passengers by road. The well-known advantages of motor vehicles over other modes of transport, such as mobility, the possibility of door-to-door delivery, low capital costs for transportation organization, etc., make this mode of transport indispensable in the Far North and the Arctic. Meanwhile, the requirements for the reliability and safety of transportation are increasing significantly.The paper discusses a method of forecasting the operation time of temporary transport routes (winter roads) used for transportation most of the year. The volume of transported goods and transportation safety largely depend on the accuracy of such forecasting. Changes in weather conditions, deterioration of visibility, a sharp drop in temperature also have a significant impact on transportation safety and reliability, which makes it urgent to inform the participants of the transportation process about the current situation on the transport route. At the present stage, the main direction of road transport development is the expansion of the use of intelligent transport systems. The development of satellite navigation, on the one hand, and equipment of vehicles with on-board systems to inform drivers about weather conditions along the route, on the other hand, have created the basis for the use of intelligent transport systems (Prikhodko 2011), in particular, meteorological monitoring and information subsystems. The data received from the meteorological monitoring subsystem using external means of information should be sent to the driver for making a prompt decision on how to operate the vehicle. In this regard, it is required to design highly automated vehicles (HAVs), when data are processed from all vehicle subsystems in aggregate, and not from each separate subsystem. HAVs, or so-called unmanned transport systems, are a necessary link in the development of northern territories and in solving one of the global problems of the Strategy of Scientific and Technological Development of the Russian Federation — “territorial connectivity”.

Design and implementation path of intelligent transportation information system based on artificial intelligence technology

By using the concept, guiding ideology and design idea of artificial intelligence (AI) and Internet of Thing, this study puts forward the logistics intelligent transportation system (ITS) model, structure design and function design based on AI, focusing on the time value and information value of the intelligent logistics information system. The results show that the design of ITS model based on AI includes three modules: input, transformation and output of ITS. The ITS supply chain management platform and function design of freight vehicles with AI is feasible and prospective. The application of AI technology in ITS has great value and development prospect.

A Voronoi-Based Group Reverse k Farthest Neighbor Query Method in the Obstacle Space

With the rapid development of intelligent transportation and geographic information system, spatial data query technology has attracted the attention of many scholars. Among them, the reverse farthest neighbor query from the data point to find the target point as its farthest adjacent data points, used to obtain target set of weak influence. Its research results have been widely applied to facility location, earthquake relief, marketing and other major areas. Thus, the research of reverse furthest neighbor query technology is of great significance. However, the existing methods only deal with a single query point, and do not consider how to obtain the optimal farthest neighbor position of group reverse when the number of query points changes from one to a group. In addition, considering it is difficult to avoid some geographical location restrictions in the real situation, the existing studies are limited to road network or Euclidean space simplely, without taking the existence of obstacles into consideration. To this end, this paper proposed the V-OGRkFN(Voronoi-Obstacle Group Reverse $k$ Farthest Neighbor) algorithm. Firstly, the algorithm gets the minimum cover circle of query points which are considered into a whole. Secondly, we use the framework based on the filtering and refining process of query by pruning strategy based on Voronoi diagram's properties. Then we get the candidate set using the theorem of transformation between $k$ nearest neighbors and $k$ farthest neighbors. Finally, the refining algorithm is given to get the final results. V-OGRkFN algorithm shows great performance of reverse $k$ farthest neighbor query through the specific comparative experimental analysis.

Intelligent Traffic Control System Based on Cloud Computing and Big Data Mining

This article aims at discussing problems such as complex object types, large amount of data collection, high demand for transmission and calculation, and weak real-time scheduling and control ability in the construction of modern intelligent traffic information physical fusion network, cloud-based control system theory, modern intelligent traffic control network as the research object, and the physical design of the intelligent transportation information fusion cloud control system scheme. The scheme includes intelligent transportation edge control technology and intelligent transportation network virtualization technology. Based on intelligent traffic flow data, in the center of the cloud control management server using deep learning and overrun learning machine intelligence study methods, such as the forecast of traffic flow data for training, to predict urban road short-term traffic flow and congestion. Further up in the air by using intelligent optimization scheduling algorithm for real-time traffic flow control strategy, the simulation results show the effectiveness of the proposed method.

Development of Information Evaluation System for Smart City Planning Using Geoinformatics Techniques

Urbanization is a continuous process, which transforms the traditional setup into the modern era. Uneven population growth over the next 3 decades is expected in cities. In this context, the new technology-based solutions are desirable, which can provide more efficient and robust approaches for urban infrastructure planning. Keeping these visions, the smart city concept is evolving in the developing countries like India, which appears a new paradigm of systematic intelligent urban infrastructure planning in the city. This research work comprises of grids-based, eight different land use and infrastructure-related information evaluation systems namely urban settlements information evaluation system, water resource information evaluation system, urban green space information evaluation system, intelligent transportation information evaluation system, basic infrastructure information evaluation system, power distribution information evaluation system, telecommunication mast information evaluation system and city surveillance information evaluation system for the development of smart city priority zones in the Bhopal city, capital of Madhya Pradesh, India. The LISS IV and Cartosat 1 sensor digital Image data along with ancillary data were used. The GPS survey was carried out to confirm ground realities, and digital intelligent map was prepared for various utilities after integration of thematic layers. The geostatistical analysis and weights-based methods were used for the creation of information evaluation system for city planning. The investigation of results have shown that various parameters related to smart city planning can be analyzed in a more efficient manner by dividing the area into an appropriate size grid. The spatial integration of information evaluation systems were carried out and areas were divided into low-, medium- and high-priority zones. These prominent categories such as high-priority zones covered the 14% of the study area, similarly medium-priority zones covered the 34% of the study area and low-priority zones covered the 52% of the study area. This research work investigations are very useful for the formulation of new strategic plans, in order to achieve better land use and infrastructure features utilization for the smart city planning.

Интеллектуализация управленческих функций дежурного по станции

The railway transport network is a complex dynamic object, the management of which is impossible without automated information systems. Information systems today are not just means of supporting management, but the main elements of the railway transport infrastructure. A high level of requirements for the efficiency of rail traffic management determines the need for the development of “smart” (intelligent) transport information systems. Intellectual systems, using the expert knowledge incorporated in it, will generate management solutions optimal for a particular technological situation and offer them to the user's choice.The article details the functional capabilities of an automated work station for the station operator (AWS SO). On the example of a hostile situation, a minimal set of parameters is listed, which should promptly evaluate the SO for making an optimal management decision.The necessity of developing the intellectual capabilities of station systems is justified. A number of technological responsibilities for SO are identified that require quality management tips (solutions) from information systems. Some principles and methods for constructing intelligent systems for controlling the operational work of stations are considered. Intellectualization of control systems of station processes will allow reducing production losses and improving the efficiency of the functioning of railway stations.

A Discriminated Release Strategy for Parking Variable Message Sign Display Problem Using Agent-Based Simulation

With the development and application of intelligent transportation systems (ITS), parking guidance and information system (PGIS) has become a hot topic for research and applications. Parking variable message sign (parking VMS) is the most common form of PGIS currently in use, particularly in providing the space availability information to en-route drivers. The aim of this study is to model drivers' responses to the parking VMSs under various parking information in a dynamical way. To ensure the guiding efficiency and assist drivers to identify parking lots with vacant spaces, the display strategies of parking VMS were studied. A discriminated release strategy with a space occupancy indicator (SOI) was then proposed to determine the display content on the parking VMS, in which an agent-based simulation was introduced to incorporate both parking choice model and traffic assignment algorithm dynamically. Guiding reliability and display strategies were further analyzed to attain a discriminated release strategy with SOI effectively. The results indicate that the guiding reliability was improved by reducing the SOI value of the corresponding parking lot, and the relatively uniform guiding reliabilities of all parking lots were attained by modifying SOI values iteratively. Additionally, the performance by incorporating the waiting time into the parking choice model was investigated and recommended. The discriminated release strategy presented in this study will assist in designing and operating urban PGIS.

ITTS: Intelligent Transport and Tourism System

Vast amount of information is stored in the World Wide Web and search engines are able to extract information from the web based on the keywords issued by the users. Existing search engines are not able to provide a customized solution for the visitors or tourists who wish to know the information related to transport facility, places of visit in a city, items for purchase, lodging and restaurant details, etc. in a city. Hence, an intelligent transport and tourism information system is essential for facilitating the tourists or visitors. This system should be able to provide information such as lodging facilities available in a city, items to be purchased in a city in an efficient manner. In this paper, we have made efforts to propose the architecture for transport and tourism information system and also we have developed a prototype system named as Intelligent Transport and Tourism System (ITTS) in Hadoop environment.

Decision Oriented Intelligent Transport Information Platform Design Research – Case study of Hangzhou City

With reference to Hangzhou's intelligent transport information platform design, this paper presents the central aim, system function and implementation technique of city's intelligent transport information platform construction, which is one of the major tasks of constructing China's metropolitan ITS (Intelligent Information System). First of all, the current situations and existing problems of Hangzhou's ITS construction are analyzed along with the present global development concerned. Secondly, its aim, system users and their requirements are specified. Designing the structure of platform system based on user's requirement analysis covers the subsystems of basic transport information collection, transport information exchange and sharing, intelligent transport simulation and transport information service. Meanwhile, with a detailed introduction to the functions of each subsystem, the key technologies in platform construction are put forward, such as multi-resolution method, GIS-T(Geography Information System -Transportation) design, mass data on-line analysis and processing technology, decision-oriented transport analysis tool, etc. Above all, the introduction to intelligent platform design affords useful lessons to China's city intelligent transport information platform construction.

퍼지논리 및 GPS정보를 이용한 링크통행속도의 예측

지능형교통정보시스템에 있어서 적절한 교통량 분산을 통한 교통망의 제어 및 정확한 주행정보의 제공을 위해 현재의 교통상황 또는 링크통행정보를 정확히 판단하고 평가할 수 있는 알고리즘의 개발이 필요하다. 본 논문에서는 퍼지추론시스템을 적용하여 보다 합리적으로 링크통행속도를 판단할 수 있는 알고리즘을 제안한다. 교통상황을 특징짓는 세 가지 요인으로 시간, 요일, 속도를 선정하였고 이를 퍼지변수로 표현하여 링크통행속도의 예측을 위한 적절한 퍼지규칙을 선정하였다. 본 논문에서는 실제 주행실험을 통해 얻은 차량의 GPS정보만을 사용하였다. 취득한 GPS정보 중에서 신뢰도가 높은 데이터만을 선택하여 도로통행속도를 계산하였고 퍼지추론의 과정을 통해 링크주행속도를 예측하였다. It is essential to develop an algorithm for the estimate of link travel velocity and for the supply and control of travel information in the context of intelligent transportation information system. The paper proposes the fuzzy logic based prediction of link travel velocity. Three factors such as time, date and velocity are considered as major components to represent the travel situation. In the fuzzy modeling, those factors were expressed by fuzzy membership functions. We acquire position／velocity data through GPS antenna with PDA embedded probe vehicles. The link travel velocity is calculated using refined GPS data and the prediction results are compared with actual data for its accuracy.