211 related articles for article (PubMed ID: 36502597)
1. Automated vehicle data pipeline for accident reconstruction: New insights from LiDAR, camera, and radar data.
Beck J; Arvin R; Lee S; Khattak A; Chakraborty S
Accid Anal Prev; 2023 Feb; 180():106923. PubMed ID: 36502597
[TBL] [Abstract][Full Text] [Related]
2. Analysis of pre-crash scenarios and contributing factors for autonomous vehicle crashes at intersections.
Liu Q; Wang X; Liu S; Yu C; Glaser Y
Accid Anal Prev; 2024 Feb; 195():107383. PubMed ID: 37984113
[TBL] [Abstract][Full Text] [Related]
3. How would autonomous vehicles behave in real-world crash scenarios?
Zhou R; Zhang G; Huang H; Wei Z; Zhou H; Jin J; Chang F; Chen J
Accid Anal Prev; 2024 Jul; 202():107572. PubMed ID: 38657314
[TBL] [Abstract][Full Text] [Related]
4. 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
[TBL] [Abstract][Full Text] [Related]
5. 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
[TBL] [Abstract][Full Text] [Related]
6. 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
[TBL] [Abstract][Full Text] [Related]
7. Identifying typical pre-crash scenarios based on in-depth crash data with deep embedded clustering for autonomous vehicle safety testing.
Zhou R; Huang H; Lee J; Huang X; Chen J; Zhou H
Accid Anal Prev; 2023 Oct; 191():107218. PubMed ID: 37467602
[TBL] [Abstract][Full Text] [Related]
8. 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; 84():251-260. PubMed ID: 36868654
[TBL] [Abstract][Full Text] [Related]
9. A Survey on Ground Segmentation Methods for Automotive LiDAR Sensors.
Gomes T; Matias D; Campos A; Cunha L; Roriz R
Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679414
[TBL] [Abstract][Full Text] [Related]
10. The real-world safety potential of connected vehicle technology.
Doecke S; Grant A; Anderson RW
Traffic Inj Prev; 2015; 16 Suppl 1():S31-5. PubMed ID: 26027973
[TBL] [Abstract][Full Text] [Related]
11. Exploratory analysis of automated vehicle crashes in California: A text analytics & hierarchical Bayesian heterogeneity-based approach.
Boggs AM; Wali B; Khattak AJ
Accid Anal Prev; 2020 Feb; 135():105354. PubMed ID: 31790970
[TBL] [Abstract][Full Text] [Related]
12. What can we learn from the AV crashes? - An association rule analysis for identifying the contributing risky factors.
Liu P; Guo Y; Liu P; Ding H; Cao J; Zhou J; Feng Z
Accid Anal Prev; 2024 May; 199():107492. PubMed ID: 38428241
[TBL] [Abstract][Full Text] [Related]
13. Assessing the collective safety of automated vehicle groups: A duration modeling approach of accumulated distances between crashes.
Sohrabi S; Lord D; Dadashova B; Mannering F
Accid Anal Prev; 2024 Apr; 198():107454. PubMed ID: 38290409
[TBL] [Abstract][Full Text] [Related]
14. Potential occupant injury reduction in the U.S. vehicle fleet for lane departure warning-equipped vehicles in single-vehicle crashes.
Kusano K; Gorman TI; Sherony R; Gabler HC
Traffic Inj Prev; 2014; 15 Suppl 1():S157-64. PubMed ID: 25307382
[TBL] [Abstract][Full Text] [Related]
15. 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
[TBL] [Abstract][Full Text] [Related]
16. Automated vehicle crash sequences: Patterns and potential uses in safety testing.
Song Y; Chitturi MV; Noyce DA
Accid Anal Prev; 2021 Apr; 153():106017. PubMed ID: 33578268
[TBL] [Abstract][Full Text] [Related]
17. Agricultural vehicles and rural road safety: tackling a persistent problem.
Jaarsma CF; De Vries JR
Traffic Inj Prev; 2014; 15(1):94-101. PubMed ID: 24279972
[TBL] [Abstract][Full Text] [Related]
18. Deriving functional safety (ISO 26262) S-parameters for vulnerable road users from national crash data.
Krampe J; Junge M
Accid Anal Prev; 2021 Feb; 150():105884. PubMed ID: 33360036
[TBL] [Abstract][Full Text] [Related]
19. Speed enforcement detection devices for preventing road traffic injuries.
Wilson C; Willis C; Hendrikz JK; Bellamy N
Cochrane Database Syst Rev; 2006 Apr; (2):CD004607. PubMed ID: 16625608
[TBL] [Abstract][Full Text] [Related]
20. Quantifying the Impact of Deployments of Autonomous Vehicles and Intelligent Roads on Road Safety in China: A Country-Level Modeling Study.
Tan H; Zhao F; Song H; Liu Z
Int J Environ Res Public Health; 2023 Feb; 20(5):. PubMed ID: 36901079
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]