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Pubmed for Handhelds

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Journal Abstract Search

295 related items for PubMed ID: 36901079

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  • 5. Approaching autonomous driving with cautious optimism: analysis of road traffic injuries involving autonomous vehicles based on field test data.
    Ye W, Wang C, Chen F, Yan S, Li L.
    Inj Prev; 2021 Feb; 27(1):42-47. PubMed ID: 31915269
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  • 6. Advancing investigation of automated vehicle crashes using text analytics of crash narratives and Bayesian analysis.
    Lee S, Arvin R, Khattak AJ.
    Accid Anal Prev; 2023 Mar; 181():106932. PubMed ID: 36580765
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  • 7. Development and validation of a questionnaire to assess public receptivity toward autonomous vehicles and its relation with the traffic safety climate in China.
    Qu W, Xu J, Ge Y, Sun X, Zhang K.
    Accid Anal Prev; 2019 Jul; 128():78-86. PubMed ID: 30986638
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  • 9. Sharing roads with automated vehicles: A questionnaire investigation from drivers', cyclists' and pedestrians' perspectives.
    Li X, Kaye SA, Afghari AP, Oviedo-Trespalacios O.
    Accid Anal Prev; 2023 Aug; 188():107093. PubMed ID: 37150131
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  • 12. What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach.
    Zhu S, Meng Q.
    Accid Anal Prev; 2022 Sep; 174():106769. PubMed ID: 35858521
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  • 13. Mining patterns of autonomous vehicle crashes involving vulnerable road users to understand the associated factors.
    Kutela B, Das S, Dadashova B.
    Accid Anal Prev; 2022 Feb; 165():106473. PubMed ID: 34774280
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  • 14. Crash comparison of autonomous and conventional vehicles using pre-crash scenario typology.
    Liu Q, Wang X, Wu X, Glaser Y, He L.
    Accid Anal Prev; 2021 Sep; 159():106281. PubMed ID: 34273622
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  • 15. An intelligent dynamic cyber physical system threat detection system for ensuring secured communication in 6G autonomous vehicle networks.
    M S, R S P.
    Sci Rep; 2024 Sep 05; 14(1):20795. PubMed ID: 39242659
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  • 16. Trajectory planning framework for autonomous vehicles based on collision injury prediction for vulnerable road users.
    Guo Y, Liu Y, Wang B, Huang P, Xu H, Bai Z.
    Accid Anal Prev; 2024 Aug 05; 203():107610. PubMed ID: 38749269
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  • 17. A comparative study of collision types between automated and conventional vehicles using Bayesian probabilistic inferences.
    Novat N, Kidando E, Kutela B, Kitali AE.
    J Safety Res; 2023 Feb 05; 84():251-260. PubMed ID: 36868654
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  • 18. Network-wide safety impacts of dedicated lanes for connected and autonomous vehicles.
    Sha H, Singh MK, Haouari R, Papazikou E, Quddus M, Quigley C, Chaudhry A, Thomas P, Weijermars W, Morris A.
    Accid Anal Prev; 2024 Feb 05; 195():107424. PubMed ID: 38091887
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  • 19. Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles.
    Ko W, Park S, Yun J, Park S, Yun I.
    Sensors (Basel); 2022 Aug 12; 22(16):. PubMed ID: 36015798
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  • 20. Pedestrians' road-crossing behavior towards eHMI-equipped autonomous vehicles driving in segregated and mixed traffic conditions.
    Song Y, Jiang Q, Chen W, Zhuang X, Ma G.
    Accid Anal Prev; 2023 Aug 12; 188():107115. PubMed ID: 37209555
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