Development on ARM9 System-on-chip Embedded Sensor Node for Urban Intelligent Transportation System

Intelligent Transportation System (ITS) is the emerging transportation which comprises of the advanced technologies such as wireless communications, video vehicle detection, distributed system architectures, human machine interface, sensing and actuating, to improve safety of the passengers, traffic congestion, fuel consumption and optimize other services of the transportation system such as real time traffic situation, electronic toll collection, automatic road enforcement and hot lanes. The current ITS systems lacks self-adaptive capability to take spontaneous decisions. The environment of the ITS system is very complex so optimal decisions cannot be taken but a good enough decision can be taken which fulfills the requirement of the system. To build an ITS system having the capability to adapt itself, this paper presents the self-adaptive requirements for the ITS. To elicit the requirements for ITS, we use scenarios based model and goal based model using the requirements Engineering processes (Elicitation, Elaboration, Specification, Validation) with MAPE-K. We use Knowledge Acquisition on Automated Specification (KAOS) approach to build goal model using Objectiver tool, and use RELAX syntax to elicit adaptive requirements for ITS.

Intelligent Transportation Systems (ITSs) are built considering numerous legal regulations, organisational conditions, and user needs. For this reason, they cannot be sold as plug a play products and their implementation requires a clear definition of functional and technical requirements. The primary objective of ITSs is to improve the efficiency and safety of road traffic. In fact, nowadays, the number of motorways all over Europe is increasing. The road freight transport is also growing. These are one of some reasons of caused accidents. Solution to this problem may be implementation of ITS systems. But, a reliable work of them is possible when their reliability is at a very high level. The aim of this paper is to present a new model of reliability and operation analysis of the selected ITS system which include continuous provision of power to its elements. The article also contains a logical, functional and physical viewpoint of selected ITS system.

Backbone Technologies for the Exchange of Traffic and Travel Information

Nowadays the quantity of vehicles in the Lithuanian cities is growing very fast. Loading on street intersections, traffic jams, wasting fuel and air pollution is increasing also. One of the ways to solve these problems is creating Intelligent Transportation Systems (ITS) and efficiency increasement of these systems. Quality parameters for ITS systems are: efficiency of data collecting system, volume and effectiveness of control system, adaptive and efficiency of algorithms. To project optimal and effective ITS systems structure, subsystems, installation and control places it is very important to evaluate efficiency for these systems. In this article we can find one of the possible ways for rating transport streams data collecting systems. After experiment (expert interrogatory method) results showed that video surveillance and digital analyzing of video signal is most efficient traffic flows data collecting technology used to control traffic flows and road intersections. Also in the article we can find efficiency evaluating methods for: video cameras, dislocation video cameras for road section and for data collection system. Ill. 6, bibl. 7 (in Lithuanian; summaries in Lithuanian, English and Russian).

Intelligent Transportation Systems (ITS) have developed rapidly over the last three years in Korea. This has been driven largely by rapid development of information processing, communication, and vehicle technology, combined with ever-increasing congestion on the urban streets. This is every reason to believe that ITS will be most heavily deployed in metropolitan cities of Korea, where important safety and congestion benefits. ITS is being developed as a national program to cope with diverse traffic problems in Korea. The Korea government plans to spend 1% of the total transport expenditure on research and development of ITS over the next 5 years, reaching 100-200 million US$ annually. It is suggested that the benefits of ITS systems are substantial, but that failure to address a number of important institutional issues is one major reason for failure this system to live up to expectations, at least thus far. This paper examines the institutional issues that affect the implementation of ITS in Korea. In this paper, the definition and components of ITS are explained, and the recent developments of this system are discussed. The institutional issues on ITS implementation are identified on an extensive literature review.

Comprised of a broad range of diverse technologies, including information processing, communications, control, and electronics, Intelligent Transportation Systems (ITS) were first introduced as a means to solve the conflict between constantly increasing travel demand and insufficient transportation infrastructure. However, the impact of ITS on road safety was soon realized, and it became one of the major purposes of some ITS systems instead of only a side product. This paper summarizes the impacts of ITS technologies on road safety and the challenges of ITS safety evaluation. Based on the evaluation of collected ITS benefits information, this paper concludes that a variety of ITS technologies have the potential to make a substantial contribution to road safety and thereby have a substantial positive economic impact in the United States.

Recent catastrophic bridge failures clearly indicate the urgent need for improving interval-based bridge inspection procedures that are qualitative and subjective in nature. Structural Health Monitoring (SHM) can mitigate the deficiencies of interval-based inspection techniques and provide real-time diagnostic information regarding the bridge structural health. SHM is not flawless however; the variability in the vehicle characteristics and traffic operational conditions makes it prone to false diagnosis. Recent advancements in the integration of SHM with intelligent transportation systems (ITS) demonstrate the successful use of ITS devices (e.g., traffic cameras, traffic detectors) in the analysis of bridge responses to multimodal traffic with varying loads or during the critical events that cause excess vibration beyond the normal limit. In an ITS-informed SHM system, the ITS device collected data can be integrated with SHM to increase the reliability and accuracy of the SHM system. This integration would reduce the possibility of false diagnosis of damages detected by the SHM system (e.g., vibrations caused by heavy vehicles on a bridge could be read by a SHM sensor as a structural health problem of the bridge), which would eventually decrease the bridge maintenance costs. Similarly, in SHM-informed ITS system, SHM sensors can provide data on bridge health condition for ITS applications, where ITS uses this bridge health condition information for real-time traffic management. In this paper, literature related to both ITS-informed SHM and SHM-informed ITS is reviewed. Based on the literature review, potential challenges and future research directions associated with ITS-SHM integration are also discussed.

Traffic data is very important for Intelligent Transportation Systems. The traffic data is collected by different types of detectors. However, the data collected by these detectors cannot meet the precision and completeness requirement of ITS. To improve traffic data's completeness and comprehensiveness, this paper addresses a problem when road sections have no GPS sampling signals based on floating vehicle systems. A robust Kalman Filter fusion algorithm is proposed to fuse the information of associated road sections, of which traffic information is known, and to obtain the traffic information of the road sections without GPS sampling signals. The method is verified with the real GPS traffic data of Hangzhou city, China, and compared with the standard Kalman Filter algorithm. Finally, experimental results show that the proposed fusion method is effective and can provide more precise and comprehensive traffic information for traffic managers.

Traffic density data plays an important role in decision making by the Intelligent Transportation System (ITS). This system uses this data in the process of adaptive traffic management. The inaccuracy of the data provided into the ITS system can result in errors in decision making. This study utilizes digital image engineering technology in the detection of four-wheeled vehicles in traffic traffic for the purpose of acquiring traffic density data. In this study, we propose a multi-ROI (pixel area methodRegion of Interest). This multi-ROI proposal is to be put forward to improve reading accuracy compared to just one ROI. With the use of this multi-ROI, the information obtained from the overall ROI can strengthen the accuracy of the data of vehicles passing in a lane. Our experimental results show that the use of multi-ROI with a certain amount of ROI can produce an accuracy rate of up to 88.66% compared to single-ROI which has an accuracy rate of 84.65%.

With the use of technologies, ‘cities’ are able to control everything from traffic lights to the distribution of water in the city, traffic, environment, social actions, health, education, urban planning, security, and public administration, are some of the main areas of activity. The implementation of technology also brings other concerns such as data security and vulnerability and the privacy of individuals. The evolution of intelligent transport systems (ITS) has been accelerated, multifaceted, and often based on the technological advances considered revolutionary for the Urban Mobility sector. Recently, the widespread use of ITS in the operation and management of urban mobility is part of everyday life. Numerous tools are now available for a variety of contexts and scales, with applications that directly impact both locally and globally. This dissertation seeks to analyze the security risk within smart cities. It addresses the theme of what are intelligent transport systems and what are the main solutions to ensure the safety of these systems. To this end, is performed an analysis and classification of ITS threats. With the help of the NS-3 network simulator to model, the ITS communications architecture and the Simulation of Urban Mobility (SUMO) traffic simulator an urban road area scenario was generated. Finally, lessons learned and future research challenges to improve the security of ITS systems are presented.KeywordsSmart citySafetyPrivacyDataInfrastructuresMobilityInternet of Things (IoT)Traffic controlE-GovernanceCybersecurityHackers

Today, the Intelligent Transportation Systems (ITS) are already in deep integration phase all over the world. One of the most significant enablers for ITS are vehicle positioning and tracking techniques. Worldwide integration of ITS employing Dedicated Short Range Communications (DSRC) and European standard for vehicular communication, known as ETSI ITS-G5, brings a variety of options to improve the positioning in areas where GPS connectivity is lacking precision. Utilization of the ready infrastructure, next-generation cellular 5G networks, and surrounding electronic devices together with conventional positioning techniques could become the solution to improve the overall ITS operation in vehicle-to-everything (V2X) communication scenario. Nonetheless, effective and secure communication protocols between the vehicle and roadside units should be both analyzed and improved in terms of potential attacks on the transmitted positioning-related data. In particular, said information might be misused or stolen at the infrastructure side conventionally assumed to be trusted. In this paper, we first survey different methods of vehicle positioning, which is followed by an overview of potential attacks on ITS systems. Next, we propose potential improvements allowing mutual authentication between the vehicle and infrastructure aiming at improving positioning data privacy. Finally, we propose a vision on the development and standardization aspects of such systems.

An intelligent transportation System (ITS) is an unconventional application that aims to provide traffic congestion information and emergency information to other vehicles. In ITS, the compilation and distribution of traffic event information by vehicles are of the most extreme significance. To establish an effective data-sharing network in ITS, the vehicles need to share the data in a protected form in real-time. Conventional ITS system includes data streaming from On-Board Unit (OBU) sensors through Road Side Units (RSU) to centralized cloud servers. Nevertheless, it is still a challenge to distribute essential event information in a selected area under the dynamic ITS environment and in the existence of a malicious vehicle. The current fundamental issues which emerge include privacy concerns due to third party management of cloud servers, single point of failure which are a bottleneck in data flow among the vehicles.

Standardization plays a crucial role in facilitating adoption of a technology while enabling the interoperability between products of different manufacturers. Standardization of intelligent transport systems (ITS) involves stakeholders in different regions. For enabling a globally interoperable ITS system, EU, Japan, and the USA closely work together towards harmonized standards. A compact overview on a consistent set of important standards to build ITS station units for vehicular ad hoc networks (VANETs) and cooperative-ITS (C-ITS) and, in general for ITS, is provided in this chapter. To a large extent, references are made to standards from CEN, ETSI, IEEE, ISO, and SAE.

Rapid advances in wireless communication technologies coupled with ongoing massive development in vehicular networking standards and innovations in computing, sensing, and analytics have paved the way for intelligent transportation systems (ITS) to develop rapidly in the near future. ITS provides a complete solution for the efficient and intelligent management of real-time traffic, wherein sensory data is collected from within the vehicles (i.e., via their onboard units) as well as data exchanged between the vehicles, between the vehicles and their supporting roadside infrastructure/network, among the vehicles and vulnerable pedestrians, subsequently paving the way for the realization of the futuristic Internet of Vehicles. The traditional intent of an ITS system is to detect, monitor, control, and subsequently reduce traffic congestion based on a real-time analysis of the data pertinent to certain patterns of the road traffic, including traffic density at a geographical area of interest, precise velocity of vehicles, current and predicted travelling trajectories and times, etc. However, merely relying on an ITS framework is not an optimal solution. In case of dense traffic environments, where communication broadcasts from hundreds of thousands of vehicles could potentially choke the entire network (and so could lead to fatal accidents in the case of autonomous vehicles that depend on reliable communications for their operational safety), a fall back to the traditional decentralized vehicular ad hoc network (VANET) approach becomes necessary. It is therefore of critical importance to enhance the situational awareness of vehicular drivers so as to enable them to make quick but well-founded manual decisions in such safety-critical situations.

Vision systems are effective tools for optimization and control of numerous processes. They serve as a platform for the development of autonomic, smart solutions both for vehicles and intelligent transportation systems (ITS). The data acquired by the former are critical to the functioning of the latter. Vision systems enhance the capacity of ITS to effectively manage city logistics. This paper aims to identify new possibilities offered by the addition of more cameras to an existing ITS based on analysis of the largest ITS in Poland, which was deployed in Łodź, the country’s third most populous city, in December 2015.