Significance of Real-Time Systems in Intelligent Transportation Systems

2020 ◽  
pp. 61-85
Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Ad Hoc ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Target Area ◽  
Real Time Systems ◽  
Time Systems

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.

Detection of Real-Time Event in Intelligent Traffic System Based on RFID

2014 ◽  
Vol 926-930 ◽  
pp. 1314-1317 ◽  
Author(s):  
Li Yang
Keyword(s):  
Real Time ◽  
Event Detection ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Engine Model ◽  
Intelligent Traffic System ◽  
Complex Events ◽  
Rules Engine

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.

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.

scholarly journals Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

2018 ◽  
Vol 7 (2.18) ◽  
pp. 7 ◽  
Author(s):  
Venkata Ramana N ◽  
Seravana Kumar P. V. M ◽  
Puvvada Nagesh
Keyword(s):  
Big Data ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Control Logic ◽  
Systematic Analysis ◽  
Real Time Traffic

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. 

scholarly journals Smart Car Parking System (SPS) with the Applications of Intelligent Transportation System

2019 ◽  
Vol 9 (2) ◽  
pp. 5159-5162
Keyword(s):  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
World Population ◽  
Parking Space ◽  
Modern Approach ◽  
Parking System

Intelligent Transportation Systems (ITS) is a modern approach in transportation engineering and management strategies of computer science, electronics and communication as it aims to provide advanced services in various methods of transport and traffic management systems. This helps the users to make safe, smart and efficient transport networks. Intelligent Transportation Systems (ITS) has a very wide application starting from traffic management to driver operation and vehicle control systems. Due to increase in vehicle production and world population leads to demand for more parking spaces and parking facilities. This problem is arising due to gap between demand and supply of parking spaces. The basic focus of this study is how to identify the exact location for parking the vehicle with the help of Arduino IDE software program. It will address the problems effectively associated with identification of parking slots and reaching parking places in urban areas. It informs and guide drivers to find limited number of parking spaces including their price in parking zones with in a shorter duration. Infrared sensors are also used to detect car parking slot occupancy. Smart Parking System (SPS) deals with identification of empty parking space, improper parking of vehicles and show the direction towards vacant parking slots. It also deals with digital payment facility. The ultimate focus of this is to identify the availability or non-availability of parking space.

The Image Process Based on Intelligent Transportation System

2014 ◽  
Vol 945-949 ◽  
pp. 1789-1793 ◽  
Author(s):  
Wen Qian An ◽  
Xu Fang Bo ◽  
Chao Jia
Keyword(s):  
Automobile Industry ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Gaussian Mixture ◽  
Transportation Systems ◽  
Background Model ◽  
Image Process

With the rapid development of China's automobile industry, intelligent transportation systems have become an important means of modern traffic management. The paper analyzes the prospects for detection of several sports: frame difference method, optical flow method and the background model, and compared the effects of several methods of detection, using a strong adaptability to disturbance Gaussian mixture background model to detect moving targets. Then the detected motion foreground image OTSU threshold, using morphological methods de-noising and holes filled, get a complete moving target. In this paper, the characteristics of the target shadow and existing methods are analyzed, using a shadow removal method based on color features.

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 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.

Fog-based Intelligent Transportation System for Traffic Light Optimization

2021 ◽  
Vol 58 (S) ◽  
pp. 29-35
Author(s):  
Muhammad Rusyadi Ramli ◽  
Riesa Krisna Astuti Sakir ◽  
Dong-Seong Kim
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Accidents ◽  
Intelligent Transportation System ◽  
Optimization Problems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Light ◽  
Traffic Condition ◽  
Dilemma Zone ◽  
Traffic Lights

This paper presents fog-based intelligent transportation systems (ITS) architecture for traffic light optimization. Specifically, each intersection consists of traffic lights equipped with a fog node. The roadside unit (RSU) node is deployed to monitor the traffic condition and transmit it to the fog node. The traffic light center (TLC) is used to collect the traffic condition from the fog nodes of all intersections. In this work, two traffic light optimization problems are addressed where each problem will be processed either on fog node or TLC according to their requirements. First, the high latency for the vehicle to decide the dilemma zone is addressed. In the dilemma zone, the vehicle may hesitate whether to accelerate or decelerate that can lead to traffic accidents if the decision is not taken quickly. This first problem is processed on the fog node since it requires a real-time process to accomplish. Second, the proposed architecture aims each intersection aware of its adjacent traffic condition. Thus, the TLC is used to estimate the total incoming number of vehicles based on the gathered information from all fog nodes of each intersection. The results show that the proposed fog-based ITS architecture has better performance in terms of network latency compared to the existing solution in which relies only on TLC.

The convergence of Internet of Things, Blockchain and Connected Vehicles: Conceptual Advantages and Disadvantages of a new Cooperative Intelligent Transportation System

2021 ◽  
Vol 03 (01) ◽  
pp. 33-41
Author(s):  
Vittorio Astarita ◽  
Vincenzo Pasquale Giofrè ◽  
Giuseppe Guido ◽  
Alessandro Vitale
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Main Idea ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Connected Vehicles ◽  
City Management ◽  
Advantages And Disadvantages ◽  
Blockchain Technology

This paper intends to explore the convergence of some technological innovations that could lead to new cooperative Intelligent Transportation Systems (ITS). The technologies that might soon converge and lead to some new developments are: the Blockchain Technology (BT) concept, Internet of Things (IoT) and Connected and Automated Vehicles (CAV). Advantages and disadvantages of the new concepts founding a new ITS system are discussed in this conceptual paper. Blockchain technology has been recently introduced and many research ideas have been presented for application in the transportation sector. In this paper, we discuss a system that is based on a dedicated blockchain, able to involve both drivers and city administrations in the adoption of promising and innovative technologies that will create cooperation among connected vehicles. The proposed blockchain-based system can allow city administrators to reward drivers when they are willing to share travel data. The system manages in a special way the creation of rewards which are assigned to drivers and institutions participating actively in the system. Moreover, the system allows keeping a complete track of all transactions and interactions between drivers and city management on a completely open and shared platform. The main idea is to combine connected vehicles with BT to promote Cooperative ITS use, a better use of infrastructures and a more sustainable eco-system of cryptocurrencies. A short description of BT is introduced to evidence energy problems of sustainability in the implementation of Proof of Work (PoW) that is adopted by many blockchains.

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