BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

367 related articles for article (PubMed ID: 33128992)

  • 1. Rear-end collision warning of connected automated vehicles based on a novel stochastic local multivehicle optimal velocity model.
    Wen J; Wu C; Zhang R; Xiao X; Nv N; Shi Y
    Accid Anal Prev; 2020 Dec; 148():105800. PubMed ID: 33128992
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Influence of the feedback links of connected and automated vehicle on rear-end collision risks with vehicle-to-vehicle communication.
    Qin Y; Wang H
    Traffic Inj Prev; 2019; 20(1):79-83. PubMed ID: 30715915
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Risk perception and the warning strategy based on safety potential field theory.
    Li L; Gan J; Yi Z; Qu X; Ran B
    Accid Anal Prev; 2020 Dec; 148():105805. PubMed ID: 33120182
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways.
    Yao Z; Hu R; Jiang Y; Xu T
    J Safety Res; 2020 Dec; 75():262-274. PubMed ID: 33334485
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Effects of collision warning characteristics on driving behaviors and safety in connected vehicle environments.
    Zhao W; Gong S; Zhao D; Liu F; Sze NN; Huang H
    Accid Anal Prev; 2023 Jun; 186():107053. PubMed ID: 37030178
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems.
    Kusano KD; Gabler HC
    Traffic Inj Prev; 2015; 16 Suppl 2():S109-14. PubMed ID: 26436219
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator.
    Lee JD; McGehee DV; Brown TL; Reyes ML
    Hum Factors; 2002; 44(2):314-34. PubMed ID: 12452276
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A comparison of tactile, visual, and auditory warnings for rear-end collision prevention in simulated driving.
    Scott JJ; Gray R
    Hum Factors; 2008 Apr; 50(2):264-75. PubMed ID: 18516837
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An improved automated braking system for rear-end collisions: A study based on a driving simulator experiment.
    Hang J; Yan X; Li X; Duan K; Yang J; Xue Q
    J Safety Res; 2022 Feb; 80():416-427. PubMed ID: 35249623
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Guidance-oriented advanced curve speed warning system in a connected vehicle environment.
    Wang S; Wang Y; Zheng Q; Li Z
    Accid Anal Prev; 2020 Dec; 148():105801. PubMed ID: 33128990
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Reducing the risk of rear-end collisions with infrastructure-to-vehicle (I2V) integration of variable speed limit control and adaptive cruise control system.
    Li Y; Wang H; Wang W; Liu S; Xiang Y
    Traffic Inj Prev; 2016 Aug; 17(6):597-603. PubMed ID: 26761633
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comprehensive safety assessment in mixed fleets with connected and automated vehicles: A crash severity and rate evaluation of conventional vehicles.
    Sinha A; Chand S; Wijayaratna KP; Virdi N; Dixit V
    Accid Anal Prev; 2020 Jul; 142():105567. PubMed ID: 32361477
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Modeling the influence of safety aid market penetration on traffic safety: Case of collision warning system for powered two-wheelers.
    Barbo M; Rodič B
    Accid Anal Prev; 2023 Nov; 192():107240. PubMed ID: 37572423
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fuzzy Surrogate Safety Metrics for real-time assessment of rear-end collision risk. A study based on empirical observations.
    Mattas K; Makridis M; Botzoris G; Kriston A; Minarini F; Papadopoulos B; Re F; Rognelund G; Ciuffo B
    Accid Anal Prev; 2020 Dec; 148():105794. PubMed ID: 33032008
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Impact of heterogeneity of car-following behavior on rear-end crash risk.
    Zhang J; Wang Y; Lu G
    Accid Anal Prev; 2019 Apr; 125():275-289. PubMed ID: 30802778
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A rear-end collision risk assessment model based on drivers' collision avoidance process under influences of cell phone use and gender-A driving simulator based study.
    Li X; Yan X; Wu J; Radwan E; Zhang Y
    Accid Anal Prev; 2016 Dec; 97():1-18. PubMed ID: 27565040
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Effects of lead time of verbal collision warning messages on driving behavior in connected vehicle settings.
    Wan J; Wu C; Zhang Y
    J Safety Res; 2016 Sep; 58():89-98. PubMed ID: 27620938
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Age and gender differences in time to collision at braking from the 100-Car Naturalistic Driving Study.
    Montgomery J; Kusano KD; Gabler HC
    Traffic Inj Prev; 2014; 15 Suppl 1():S15-20. PubMed ID: 25307380
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Optimal jam-absorption driving strategy for mitigating rear-end collision risks with oscillations on freeway straight segments.
    Zheng Y; Zhang G; Li Y; Li Z
    Accid Anal Prev; 2020 Feb; 135():105367. PubMed ID: 31813474
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluation of cooperative systems on driver behavior in heavy fog condition based on a driving simulator.
    Chang X; Li H; Qin L; Rong J; Lu Y; Chen X
    Accid Anal Prev; 2019 Jul; 128():197-205. PubMed ID: 31054492
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.