The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Mashrur Chowdhury - One of the best experts on this subject based on the ideXlab platform.

  • Potential of Intelligent Transportation Systems in Mitigating Adverse Weather Impacts on Road Mobility: A Review
    IEEE Transactions on Intelligent Transportation Systems, 2015
    Co-Authors: Kakan C. Dey, Ashok Mishra, Mashrur Chowdhury
    Abstract:

    Adverse weather conditions for roads, which cause Transportation Systems to perform far below capacity, can severely affect society's economic output. As elimination of road weather events is not possible, Transportation agencies perform proactive and reactive maintenance activities to minimize adverse impacts to keep roadways in optimum condition. While reactive maintenance activities are conducted to clear roadways after the occurrence of extreme weather events, proactive activities minimize these impacts beforehand. The success of proactive activities solely depends on the availability of accurate road weather information, however. Traditional road weather forecasting techniques rely on governmental weather services, which are not appropriate to predict route-specific road weather conditions. In this paper, the authors reviewed current Intelligent Transportation Systems (ITS)-based solutions for minimizing road weather impacts and possible ITS innovations to incorporate diverse data sources to improve road weather management activities. ITS-based initiatives, such as road weather information system (RWIS), allow Transportation agencies obtain accurate road weather assessments. Location-specific infrastructures such as RWIS are cost prohibitive for system-wide deployments. Connected vehicles equipped with weather sensors could enhance mobile road weather data collection. This strategy could improve proactive maintenance programs and reduce adverse effects of weather to the surface Transportation system.

  • Introduction to the special issue on emergent cooperative technologies in Intelligent Transportation Systems
    IEEE Transactions on Intelligent Transportation Systems, 2012
    Co-Authors: Miguel Angel Sotelo, Ljubo B. Vlacic, J. W.c. Van Lint, Urbano Nunes, Mashrur Chowdhury
    Abstract:

    The ten papers in this special issue cover the full range of cooperative technologies in Intelligent Transportation Systems, from V2V and V2I, including cooperative traffic management to vehicle-to-driver cooperation. These papers are summarized here.

  • Meeting privacy challenges while advancing Intelligent Transportation Systems
    Transportation Research Part C: Emerging Technologies, 2012
    Co-Authors: Ryan Fries, Mashrur Chowdhury, Mostafa Reisi Gahrooei, Alison Conway
    Abstract:

    Abstract As Transportation engineers and practitioners continue to advance the scope and breadth of Intelligent Transportation Systems (ITS) applications, privacy is a primary concern of Transportation agencies in the United States (US) when tracking people, vehicles and goods within the nation’s Transportation grid. As a number of technologies have rapidly advanced, including photo enforcement, electronic tolling, vehicle-mile taxing, weigh-in-motion, and Connected Vehicle technologies, research examining the privacy implications of system applications has lagged. In a recent national survey to determine how state departments of Transportation (DOTs) are meeting the privacy needs of the traveling public, it was determined that DOTs favor aggregating and masking data for protecting privacy of motorists while collecting travel times and speeds. For capturing video surveillance, abiding by legislation or agency policies was the preferred method of protecting privacy. Unfortunately, there are no national standards in the US for the privacy protection of travelers as most privacy information merely takes the form of poorly defined precepts. With the increasing use of ITS applications, which are becoming more interwoven into the US Transportation grid, there is a need to develop a national policy and related standards to ensure the privacy protection of the traveling public to ensure broader acceptance of ITS applications. The findings presented in this paper aim to provide direction on how to address the current and future privacy challenges that face the Transportation industry.

  • fundamentals of Intelligent Transportation Systems planning
    2003
    Co-Authors: Mashrur Chowdhury, Adel W Sadek
    Abstract:

    This book presents the essential information necessary for the successful planning of Intelligent Transportation Systems (ITS). The book is appropriate for upper-level undergraduate and undergraduate courses, and also serves as a practical reference for Transportation operations/planning practitioners. Chapters address the fundamentals of traffic flow and control, ITS user services, ITS applications and benefits, ITS architecture, ITS planning, ITS standards, ITS evaluation and ITS challenges and opportunities.

F Y Wang - One of the best experts on this subject based on the ideXlab platform.

  • Towards Blockchain-based Intelligent Transportation Systems
    2016 Ieee 19th International Conference on Intelligent Transportation Systems (Itsc), 2016
    Co-Authors: Yong Yuan, F Y Wang
    Abstract:

    Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized Intelligent Transportation Systems (ITS) in applications. Blockchain can be utilized to establish a secured, trusted and decentralized autonomous ITS ecosystem, creating better usage of the legacy ITS infrastructure and resources, especially effective for crowdsourcing technology. This paper conducts a preliminary study of Blockchain-based ITS ((BITS)-I-2). We outline an ITS-oriented, seven-layer conceptual model for blockchain, and on this basis address the key research issues in (BITS)-I-2. We consider that blockchain is one of the secured and trusted architectures for building the newly developed parallel Transportation management Systems (PtMS), and thereby discuss the relationship between (BITS)-I-2 and PtMS. Finally, we present a case study for blockchain-based realtime ride-sharing services. In our viewpoint, (BITS)-I-2 represents the future trend of ITS research and practice, and this paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.

  • Data-driven Intelligent Transportation Systems: A survey
    IEEE Transactions on Intelligent Transportation Systems, 2011
    Co-Authors: Junping Zhang, Wei Hua Lin, Kunfeng Wang, Xin Xu, F Y Wang, Cheng Chen
    Abstract:

    For the last two decades, Intelligent Transportation Systems (ITS) have emerged as an efficient way of improving the performance of Transportation Systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven Intelligent Transportation system $(\hbox{D}^{2}\hbox{ITS})$: a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, $ \hbox{D}^{2}\hbox{ITS}$ is trending to become a privacy-aware people-centric more Intelligent system. In this paper, we provide a survey on the development of $\hbox{D}^{2} \hbox{ITS}$, discussing the functionality of its key components and some deployment issues associated with $\hbox{D}^{2}\hbox{ITS}$. Future research directions for the development of $\hbox{D}^{2}\hbox{ITS}$ is also presented.

  • smart cars on smart roads an ieee Intelligent Transportation Systems society update
    IEEE Pervasive Computing, 2006
    Co-Authors: F Y Wang, Daniel Zeng, Liuqing Yang
    Abstract:

    To promote tighter collaboration between the IEEE Intelligent Transportation Systems Society and the pervasive computing research community, the authors introduce the ITS Society and present several pervasive computing-related research topics that ITS Society researchers are working on. This department is part of a special issue on Intelligent Transportation.

  • guest editorial developing and improving Transportation Systems the structure and operation of ieee Intelligent Transportation Systems society
    IEEE Transactions on Intelligent Transportation Systems, 2005
    Co-Authors: F Y Wang, C J Herget, Daniel Zeng
    Abstract:

    This editorial introduces the structure and operation of the IEEE Intelligent Transportation Systems Society (ITSS). A brief history of the ITSS is presented, along with its mission, organizational structure, and a recently approved plan to streamline its operation for various technical activities.

  • toward Intelligent Transportation Systems for the 2008 olympics
    IEEE Intelligent Systems, 2003
    Co-Authors: F Y Wang, Shuming Tang, Yagang Sui, Xiaojing Wang
    Abstract:

    Deployment of Intelligent Transportation Systems (ITS) is one of the 12 key areas of research and development in China's 10th five-year plan, lasting from 2000 to 2005. China's highway system has grown significantly over the last decade. Traffic congestion and air pollution have been the two major problems facing Beijing for decades and are the two central concerns for the successful execution of the 2008 Olympics. Recently, Beijing's government has made tremendous efforts toward solving those problems, and ITS technology will likely play an important role in the solutions. This installment deals with ITS issues in China. Clearly, ITS will play a role in the future, and all major cities are working on integrating Systems into their current scenarios. Along with this, we're witnessing the boost of China's economy and, particularly, its great effort constructing its new Transportation network. This installment presents the architecture and the technology that will be the starting point for the construction of the ITS, that will be used in Beijing 2008 Olympics.

Daniel Zeng - One of the best experts on this subject based on the ideXlab platform.

Juan Contreras-castillo - One of the best experts on this subject based on the ideXlab platform.

  • Sensor Technologies for Intelligent Transportation Systems.
    Sensors, 2018
    Co-Authors: Juan Antonio Guerrero-ibanez, Sherali Zeadally, Juan Contreras-castillo
    Abstract:

    Modern society faces serious problems with Transportation Systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern Transportation Systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and Intelligent Transportation Systems. We discuss how sensor technology can be integrated with the Transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

Medhat Moussa - One of the best experts on this subject based on the ideXlab platform.

  • deep learning for Intelligent Transportation Systems a survey of emerging trends
    IEEE Transactions on Intelligent Transportation Systems, 2020
    Co-Authors: Matthew Veres, Medhat Moussa
    Abstract:

    Transportation Systems operate in a domain that is anything but simple. Many exhibit both spatial and temporal characteristics, at varying scales, under varying conditions brought on by external sources such as social events, holidays, and the weather. Yet, modeling the interplay of factors, devising generalized representations, and subsequently using them to solve a particular problem can be a challenging task. These situations represent only a fraction of the difficulties faced by modern Intelligent Transportation Systems (ITS). In this paper, we present a survey that highlights the role modeling techniques within the realm of deep learning have played within ITS. We focus on how practitioners have formulated problems to address these various challenges, and outline both architectural and problem-specific considerations used to develop solutions. We hope this survey can help to serve as a bridge between the machine learning and Transportation communities, shedding light on new domains and considerations in the future.