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

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.

2014 ◽  
Vol 926-930 ◽  
pp. 1314-1317 ◽  
Author(s):  
Li Yang

To solve the demand of real-time event detection in the RFID-based Intelligent Transportation Systems , using Complex Event Processing technology to establish a rule model to detect events.The model allows users to customize the Basic Events and Complex Events, using the rule files describe the complex events modes, clearly expressed the timing and gradation relationships between RFID events, meeting the needs of real-time event detection in the Intelligent Transportation System ,achieving the appropriate rules engine,. Finally, test and verify the effectiveness of the rules file and the rules engine model by experiments.


Frequenz ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Arun Kumar Singh ◽  
Arun Kumar ◽  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Bansibadan Maji

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.


Author(s):  
Ahmad Saifizul Abdullah ◽  
Kim Hai Loo ◽  
Noor Azuan Abu Osman ◽  
Mohd Zamri Zainon

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


2018 ◽  
Vol 7 (2.18) ◽  
pp. 7 ◽  
Author(s):  
Venkata Ramana N ◽  
Seravana Kumar P. V. M ◽  
Puvvada Nagesh

Big data is a term that describes the large volume of data – both structured and unstructuredthat includes a business on a day-to-day basis including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation. 


2014 ◽  
Vol 484-485 ◽  
pp. 1101-1105
Author(s):  
Jing Ya Chen

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.


2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Qiang Shi ◽  
Lei Wang ◽  
Taojie Wang

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.


2021 ◽  
Vol 1 (161) ◽  
pp. 212-217
Author(s):  
О. Stepanov ◽  
А. Venger

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.


Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew

The advancements of several real-time system applications enable us to provide better solutions to day-to-day problems. One such real-time systems that has significantly enhanced its efficiency in aiding travelers to make commutation pleasant is the intelligent transportation system (ITS). There are several aspects of an ITS application that make it efficient and resourceful, but the major significant factor is its capability to provide services within a time constraint. This chapter aims to provide the basic concepts, background, and importance of dependability on distributed real-time systems in ITS using two applications for efficient traffic management. A novel automated traffic signal (ATS) is proposed that manages traffic flow by enumerating vehicle density of road segments using image processing techniques. The other proposed work involves the estimation of congestion rate (CONGRA) for given target area using the proposed hybrid vehicular ad hoc network (VANET). The details of the modules, implementation, and result analysis of the applications are discussed and presented.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gongxing Yan ◽  
Yanping Chen

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.


Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi

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.


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