This project develops and demonstrates a variety of smart-transport technologies, policies, and practices for highways and freeways using connected autonomous vehicles (CAVs), smartphones, roadside equipment, and related technologies. The intent is to maximize the benefit of these technologies in terms of improved driver safety, reduced congestion, and agency cost savings. For example, in a well-implemented system, advanced CAV technologies may reduce current crash costs by at least $390 billion per year. A poorly implemented system could significantly detract from or reverse these benefits. The project’s Phase 1, documented in this report, showcased DSRC-instrumented vehicles for wrong-way driving alerts, vehicle guidance, and road-surface condition monitoring demonstrations. It developed algorithms for more accurate vehicle-position information and real-time traffic flow monitoring. It delivered statewide and national forecasts of fleet evolution, consumer preferences, and Texans’ opinions of CAV policies and technologies. It also simulated various strategies for smart ramp merges and smart intersection and network operations, under thousands of case settings, with calculated delay reductions. It anticipated emissions savings from more thoughtful automated driving and crash savings from more conflict-aware driving. It also analyzed the benefits of shared autonomous vehicle transit. Recommendations are provided for guiding TxDOT as technologies increasingly become available to the public, estimated to impact the U. S. economy by as much as $1.3 trillion per year. Recommendations focus on the need for increasing TxDOT in-house expertise, simulating new systems, developing policy, and updating design manuals.


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    Titel :

    Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas – Final Report


    Beteiligte:
    K. Kockelman (Autor:in) / S. Boyles (Autor:in) / P. Avery (Autor:in) / C. Claudel (Autor:in) / L. Loftus-Otway (Autor:in) / D. Fagnant (Autor:in) / P. Bansal (Autor:in) / M. W. Levin (Autor:in) / Y. Zhao (Autor:in) / J. Liu (Autor:in)

    Erscheinungsdatum :

    2016


    Format / Umfang :

    631 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch





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