scholarly journals INTELLIGENT TRANSPORTATION SYSTEMS IN THE TRANSPORT PROCESS

2021 ◽  
Vol 1 (161) ◽  
pp. 212-217
Author(s):  
О. Stepanov ◽  
А. Venger
Keyword(s):  
Intelligent Transportation Systems ◽  
Road Safety ◽  
Transport Process ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Modern Society ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems

The article is devoted to the consideration of the concept of "Intelligent transportation system" – ITS in modern society. The main world concepts of ITS development, which are aimed at the organization of road traffic in order to comply with road safety, are analyzed. The authors concluded that ITS is the most effective way to qualitatively solve road safety problems.

scholarly journals LPWAN-based hybrid backhaul communication for intelligent transportation systems: architecture and performance evaluation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Area Network

AbstractIncreased number of the vehicles on the streets around the world has led to several problems including traffic congestion, emissions, and huge fuel consumption in many regions. With advances in wireless and traffic technologies, the Intelligent Transportation System (ITS) has been introduced as a viable solution for solving these problems by implementing more efficient use of the current infrastructures. In this paper, the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and NB-IoT, for ITS applications has been investigated. LTE-M and NB-IoT are designed to provide long range, low power and low cost communication infrastructures and can be a promising option which has the potential to be employed immediately in real systems. In this paper, we have proposed an architecture to employ the LPWAN as a backhaul infrastructure for ITS and to understand the feasibility of the proposed model, two applications with low and high delay requirements have been examined: road traffic monitoring and emergency vehicle management. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end-to-end latency per user. Simulation of Urban MObility has been used for realistic traffic generation and a Python-based program has been developed for evaluation of the communication system. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

Study on Path Optimization Method of Traffic Guidance System under the Condition of the Car Networking

2014 ◽  
Vol 624 ◽  
pp. 567-570
Author(s):  
Dan Ping Wang ◽  
Kun Yuan Hu
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
System Integration ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Guidance System ◽  
Wide Range ◽  
Computer Communication Network

Intelligent Transportation System is the primary means of solving the city traffic problem. The information technology, the communication, the electronic control technology and the system integration technology and so on applies effectively in the transportation system by researching rationale model, thus establishes real-time, accurate, the highly effective traffic management system plays the role in the wide range. Traffic flow guidance system is one of cores of Intelligent Transportation Systems. It is based on modern technologies, such as computer, communication network, and so on. Supplying the most superior travel way and the real-time transportation information according to the beginning and ending point of the journey. The journey can promptly understand in the transportation status of road network according to the guidance system, then choosing the best route to reach destination.

Design and implementation of microstrip array antenna for intelligent transportation systems application

Frequenz ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Arun Kumar Singh ◽  
Arun Kumar ◽  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Bansibadan Maji
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Impedance Matching ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Array Antenna ◽  
Design And Implementation ◽  
Microstrip Patch ◽  
Microstrip Array Antenna

Abstract This article proposes a design and implementation of array Microstrip Patch antenna of configuration 2 × 2 at an operating frequency of 3.5 GHz. The proposed design takes a dimension of 80 mm × 92 mm × 1.6 mm with four radiating elements arranged in rectangular form with an optimized separation between the patches. All the radiating elements were connected through a corporate series network with an inset feed to have better impedance matching. The model gives an efficiency of 90.99% with a bandwidth of 510 MHz and with fractal configuration, the bandwidth further enhances to 1.12 GHz. The maximum gain measured was found as 11.01 dBi at θ = 10° and ɸ = 360° and 10.45 dBi with fractal configuration. The designed antenna is proposed to be used in RADAR which will be used in the intelligent transportation system for the detection of nearby (short-range) vehicles in the blind zone. This kind of Radar also finds its application in collision avoidance and activating airbags/break boosting and thus helping mankind by saving lives. The article gives an idea of the use of an array antenna in intelligent transportation system for better gain and efficient results.

scholarly journals Vision Based Automatic Steering Control Using A Pid Controller

2012 ◽  
Author(s):  
Ahmad Saifizul Abdullah ◽  
Kim Hai Loo ◽  
Noor Azuan Abu Osman ◽  
Mohd Zamri Zainon
Keyword(s):  
Control System ◽  
Intelligent Transportation Systems ◽  
Pid Controller ◽  
Intelligent Transportation System ◽  
Vision System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Steering Control ◽  
Automatic Steering

Kawalan stereng automatik adalah satu komponen penting dalam pengautomatan lebuhraya, yang kini diselidik di seluruh dunia di bawah beberapa program Intelligent Transportation System (ITS). ITS berpotensi meningkatkan kapasiti lebuhraya yang sedia ada dengan penggunaan yang lebih selamat dan lebih efisien terhadap ruang yang sedia ada. Sistem ini akan terdiri daripada konsep pemanduan “hands–off” secara menyeluruh yang mana kenderaan akan dikawal secara automatik apabila ia memasuki sistem itu. Untuk mencapai objektif di atas, pengawal PID dan konsep dasar penglihatan ke atas sistem kawalan stereng automatik digunakan untuk membolehkan kenderaan menjejak rujukan di dalam pelbagai keadaan. Keputusan simulasi menunjukkan bahawa sistem kawalan yang dicadangkan mencapai objektifnya meskipun ia kurang lasak untuk mengekalkan prestasinya di dalam pelbagai keadaan. Kata kunci: Kawalan stereng automatik, dinamik kenderaan, sistem penglihatan, kawalan PID Automatic steering control is a vital component of highway automation, currently investigated worldwide in several Intelligent Transportation Systems (ITS) programs. The promise of Intelligent Transportation System lies in the possibility of increasing the capacity of existing highways by safer and more efficient use of available space. This system will include completely “hands–off” driving in which vehicles are fully automatically controlled once they enter the system. In order to achieve the above objective, the Proportional–Integral–Derivative (PID) controller and vision based concept to an automatic steering control system is used to cause the vehicle to track the reference under various conditions. Simulation results show that the proposed control system achieved its objective even though it is less robust in maintaining its performance under various conditions. Key words: Automatic steering control, vehicle dynamics, vision system, PID controller

scholarly journals A Review on IEEE 802.11p for Intelligent Transportation Systems

2020 ◽  
Vol 9 (2) ◽  
pp. 22 ◽  
Author(s):  
Fabio Arena ◽  
Giovanni Pau ◽  
Alessandro Severino
Keyword(s):  
Automotive Industry ◽  
Intelligent Transportation Systems ◽  
Road Safety ◽  
Short Range ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Ieee 802.11P ◽  
Dedicated Short Range Communication ◽  
The World

Road safety is an active area of research for the automotive industry, and certainly one of ongoing interest to governments around the world. The intelligent transportation system (ITS) is one of several viable solutions with which to improve road safety, where the communication medium (e.g., among vehicles and between vehicles and the other components in an ITS environment, such as roadside infrastructure) is typically wireless. A typical communication standard adopted by car manufacturers is IEEE 802.11p for communications. Thus, this paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting. Specifically, we analyze both MAC and PHY layers in a dedicated short-range communication (DSRC) environment.

An Intelligent Transportation Systems Model Based on Multi-Agent Technology

2014 ◽  
Vol 484-485 ◽  
pp. 1101-1105
Author(s):  
Jing Ya Chen
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Control Agent ◽  
Transportation Systems ◽  
Agent Technology ◽  
Loosely Coupled ◽  
Systems Model ◽  
Multi Agent

Intelligent transportation system based on multi-agent, become a important method, also is to solve the complex traffic problems. In the geography of the property of the agent in the heterogeneous environment cause implementation difficulties such as interoperability requirements, make the agent of unity between software platforms as a potential infrastructure. This paper puts forward a model and the more intelligent transportation system based on SOA. The model includes four major parts: infrastructure, services, agency, and coordination agent. Elements The model of the agent into different levels and groups, including organization agent, regional control agent, agent, road section road intersection vehicle control agent, the acting to complete different function and goal. Based on the SOA multi-agent technology, can realize the cross-platform loosely coupled, and interoperability and heritage reuse in distributed and heterogeneous network traffic system.

scholarly journals Traffic Big Data in the Development of Intelligent Transportation System

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Qiang Shi ◽  
Lei Wang ◽  
Taojie Wang
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Paper Briefly ◽  
System A ◽  
Basic Characteristics

With the continuous development and advancement of computer technology, big data guarantees the establishment of an urban intelligent transportation system, a solid environmental basis to reform its application, and the construction of a deeply integrated data mechanism for big data-driven traffic management. This review paper briefly elaborates on the basic characteristics and sources of traffic big data as well as expound on the problems and application mechanisms of big data in intelligent transportation systems.

scholarly journals Modelling and Reasoning Techniques for Context – Aware Computing in Intelligent Transportation System

2021 ◽  
Author(s):  
Chinnaiyan R ◽  
Swarnamugi M
Keyword(s):  
Context Awareness ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Contextual Information ◽  
Intelligent Transportation ◽  
Road Transport ◽  
Transportation System ◽  
Transportation Systems ◽  
Data Generation ◽  
Raw Data

Abstract The emergence of IoT technology and recent advancement in sensor networks enabled transportation systems to a new dimension called Intelligent Transportation System (ITS). Due to increased usage of vehicles and communication among entities in road traffic scenarios, the amount of raw data generation in ITS is huge. This raw data are to be processed to infer contextual information and provide new services related to different modes of road transport such as traffic signal management, accident prediction, object detection etc.,. To understand the importance of context, this article aims to study context-awareness in the Intelligent Transportation System. We present a review on prominent applications developed in the literature concerning context – awareness in the intelligent transportation system. The objective of this survey article is (i) to highlight context and its features in ITS (ii) to address the applicability of modelling techniques and reasoning approaches in ITS (iii) to shed light on impact of IoT and machine learning in ITS development.

scholarly journals The Application of Virtual Reality Technology on Intelligent Traffic Construction and Decision Support in Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gongxing Yan ◽  
Yanping Chen
Keyword(s):  
Big Data ◽  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
The Other ◽  
The City

The core of smart city is to build intelligent transportation system.. An intelligent transportation system can analyze the traffic data with time and space characteristics in the city and acquire rich and valuable knowledge, and it is of great significance to realize intelligent traffic scheduling and urban planning. This article specifically introduces the extensive application of urban transportation infrastructure data in the construction and development of smart cities. This article first explains the related concepts of big data and intelligent transportation systems and uses big data to illustrate the operation of intelligent transportation systems in the construction of smart cities. Based on the machine learning and deep learning method, this paper is aimed at the passenger flow and traffic flow in the smart city transportation system. This paper deeply excavates the time, space, and other hidden features. In this paper, the traffic volume of the random sections in the city is predicted by using the graph convolutional neural network (GCNN) model, and the data are compared with the other five models (VAR, FNN, GCGRU, STGCN, and DGCNN). The experimental results show that compared with the other 4 models, the GCNN model has an increase of 8% to 10% accuracy and 15% fault tolerance. In forecasting morning and evening peak traffic flow, the accuracy of the GCNN model is higher than that of other models, and its trend is basically consistent with the actual traffic volume, the predicted results can reflect the actual traffic flow data well. Aimed at the application of intelligent transportation in an intelligent city, this paper proposes a machine learning prediction model based on big data, and this is of great significance for studying the mechanical learning of such problems. Therefore, the research of this paper has a good implementation prospect and academic value.

scholarly journals A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

2021 ◽  
Vol 11 (15) ◽  
pp. 6831
Author(s):  
Yue Chen ◽  
Jian Lu
Keyword(s):  
Intelligent Transportation Systems ◽  
High Efficiency ◽  
Road Traffic ◽  
Low Cost ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Counting Method ◽  
Moving Vehicle ◽  
Available Information

With the rapid development of road traffic, real-time vehicle counting is very important in the construction of intelligent transportation systems (ITSs). Compared with traditional technologies, the video-based method for vehicle counting shows great importance and huge advantages in its low cost, high efficiency, and flexibility. However, many methods find difficulty in balancing the accuracy and complexity of the algorithm. For example, compared with traditional and simple methods, deep learning methods may achieve higher precision, but they also greatly increase the complexity of the algorithm. In addition to that, most of the methods only work under one mode of color, which is a waste of available information. Considering the above, a multi-loop vehicle-counting method under gray mode and RGB mode was proposed in this paper. Under gray and RGB modes, the moving vehicle can be detected more completely; with the help of multiple loops, vehicle counting could better deal with different influencing factors, such as driving behavior, traffic environment, shooting angle, etc. The experimental results show that the proposed method is able to count vehicles with more than 98.5% accuracy while dealing with different road scenes.

Sign in / Sign up

Export Citation Format

Share Document