Given the rapid pace of modern technological advancements, the public should expect and demand measurable improvements to highway safety. Yet, it is not so clear how much improvement may be anticipated. Government organizations such as the U.S. Department of Transportation (U.S. DOT) and National Highway Traffic Safety Administration (NHTSA) have already spent decades and millions of dollars researching proper markings, alerting systems, and safety distances to help reduce collisions and other incidents on public roadways. While clearly this effort has had great impact, there are limiting factors that continually constrain the ability of traditional methods to significantly reduce the number of collisions. Such factors include driver behavior aspects such as reaction time, sudden maneuvers, and traffic violations, plus infrastructure aspects such as malfunctioning signals, inadequate signage, and non-standard road design. As increased numbers of connected and automated vehicles (CAV) are introduced into the traffic stream, and advanced safety applications are continually improving, the industry envisions a major decline in incidents across the board. This paper details the limiting factors to why a sizable reduction of incidents is not possible with conventional resources and introduces the framework for adding advanced warnings into connected safety applications in existing vehicles, such as red-light violation warning (RLVW), to achieve measurable results. Further, the paper then applies this same model for use within automated driving systems (ADS). More than just a technological examination, this paper also predicts the expected impact to roadway incidents.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Effective Advanced Warning for Connected Safety Applications - Supplementing Automated Driving Systems for Improved Vehicle Reaction


    Weitere Titelangaben:

    Sustain. Civil Infrastruct.


    Beteiligte:
    Akhnoukh, Amin (Herausgeber:in) / Kaloush, Kamil (Herausgeber:in) / Elabyad, Magid (Herausgeber:in) / Halleman, Brendan (Herausgeber:in) / Erian, Nihal (Herausgeber:in) / Enmon II, Samuel (Herausgeber:in) / Henry, Cherylyn (Herausgeber:in) / Baumgardner, Gregory M. (Autor:in) / Boyapati, Rama Krishna (Autor:in) / Kamaraj, Amudha Varshini (Autor:in)

    Kongress:

    International Road Federation World Meeting & Exhibition ; 2021 ; Dubai, United Arab Emirates November 07, 2021 - November 10, 2021



    Erscheinungsdatum :

    2022-04-21


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Driving Safety Monitoring and Warning for Connected and Automated Vehicles via Edge Computing

    Chang, Cheng / Zhang, Kunpeng / Zhang, Jiawei et al. | IEEE | 2022


    Study on the Influence of Connected Vehicle Fog Warning Systems on Driving Behavior and Safety

    Wei Guan / Haolin Chen / Xuewei Li et al. | DOAJ | 2022

    Freier Zugriff

    Vehicle safety driving pre-warning system

    ZHANG HONG | Europäisches Patentamt | 2015

    Freier Zugriff


    SAFETY TECHNOLOGIES FOR CONNECTED AUTOMATED VEHICLE HIGHWAY SYSTEMS

    CHENG YANG / RAN BIN / LI SHEN et al. | Europäisches Patentamt | 2020

    Freier Zugriff