174 related articles for article (PubMed ID: 33653564)
1. Assessing the likelihood of secondary crashes on freeways with Adaptive Signal Control System deployed on alternate routes.
Salek MS; Jin W; Khan SM; Chowdhury M; Gerard P; Basnet SB; Torkjazi M; Huynh N
J Safety Res; 2021 Feb; 76():314-326. PubMed ID: 33653564
[TBL] [Abstract][Full Text] [Related]
2. Investigating the impacts of crash prediction models on quantifying safety effectiveness of Adaptive Signal Control Systems.
Jin W; Chowdhury M; Mahmud Khan S; Gerard P
J Safety Res; 2021 Feb; 76():301-313. PubMed ID: 33653563
[TBL] [Abstract][Full Text] [Related]
3. Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China.
Zhou Z; Meng F; Song C; Sze NN; Guo Z; Ouyang N
J Safety Res; 2021 Jun; 77():105-113. PubMed ID: 34092300
[TBL] [Abstract][Full Text] [Related]
4. Factors associated with consecutive and non-consecutive crashes on freeways: A two-level logistic modeling approach.
Zichu Z; Fanyu M; Cancan S; Richard T; Zhongyin G; Lili Y; Weili W
Accid Anal Prev; 2021 May; 154():106054. PubMed ID: 33667844
[TBL] [Abstract][Full Text] [Related]
5. Predicting crash likelihood and severity on freeways with real-time loop detector data.
Xu C; Tarko AP; Wang W; Liu P
Accid Anal Prev; 2013 Aug; 57():30-9. PubMed ID: 23628940
[TBL] [Abstract][Full Text] [Related]
6. Identifying the crash characteristics on freeway segments based on different ramp influence areas.
Yang B; Liu P; Chan CY; Xu C; Guo Y
Traffic Inj Prev; 2019; 20(4):386-391. PubMed ID: 31021664
[No Abstract] [Full Text] [Related]
7. Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.
Yu R; Abdel-Aty M
Accid Anal Prev; 2013 Sep; 58():97-105. PubMed ID: 23727550
[TBL] [Abstract][Full Text] [Related]
8. Exploring factors contributing to injury severity at freeway merging and diverging locations in Ohio.
Mergia WY; Eustace D; Chimba D; Qumsiyeh M
Accid Anal Prev; 2013 Jun; 55():202-10. PubMed ID: 23567212
[TBL] [Abstract][Full Text] [Related]
9. Investigating factors of crash frequency with random effects and random parameters models: New insights from Chinese freeway study.
Hou Q; Tarko AP; Meng X
Accid Anal Prev; 2018 Nov; 120():1-12. PubMed ID: 30075358
[TBL] [Abstract][Full Text] [Related]
10. Crash severity along rural mountainous highways in Malaysia: An application of a combined decision tree and logistic regression model.
Rusli R; Haque MM; Saifuzzaman M; King M
Traffic Inj Prev; 2018; 19(7):741-748. PubMed ID: 29932734
[TBL] [Abstract][Full Text] [Related]
11. Investigating hierarchical effects of adaptive signal control system on crash severity using random-parameter ordered regression models incorporating observed heterogeneity.
Jin W; Chowdhury M; Salek MS; Khan SM; Gerard P
Accid Anal Prev; 2021 Feb; 150():105895. PubMed ID: 33307479
[TBL] [Abstract][Full Text] [Related]
12. Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels.
Chung Y; Kim JJ
Int J Environ Res Public Health; 2023 Feb; 20(4):. PubMed ID: 36834419
[TBL] [Abstract][Full Text] [Related]
13. Assessment of Two-Vehicle and Multi-Vehicle Freeway Rear-End Crashes in China: Accommodating Spatiotemporal Shifts.
Wang C; Xia Y; Chen F; Cheng J; Wang Z
Int J Environ Res Public Health; 2022 Aug; 19(16):. PubMed ID: 36011914
[TBL] [Abstract][Full Text] [Related]
14. Scanning secondary derived crashes from disabled and abandoned vehicle incidents on uninterrupted flow highways.
Chimba D; Kutela B
J Safety Res; 2014 Sep; 50():109-16. PubMed ID: 25142367
[TBL] [Abstract][Full Text] [Related]
15. Investigating the different characteristics of weekday and weekend crashes.
Yu R; Abdel-Aty M
J Safety Res; 2013 Sep; 46():91-7. PubMed ID: 23932690
[TBL] [Abstract][Full Text] [Related]
16. Impact of traffic states on freeway crash involvement rates.
Yeo H; Jang K; Skabardonis A; Kang S
Accid Anal Prev; 2013 Jan; 50():713-23. PubMed ID: 22795398
[TBL] [Abstract][Full Text] [Related]
17. Assessing the safety impacts of raising the speed limit on Michigan freeways using the multilevel mixed-effects negative binomial model.
Kwayu KM; Kwigizile V; Oh JS
Traffic Inj Prev; 2020; 21(6):401-406. PubMed ID: 32496845
[No Abstract] [Full Text] [Related]
18. Using multivariate adaptive regression splines (MARS) to develop crash modification factors for urban freeway interchange influence areas.
Haleem K; Gan A; Lu J
Accid Anal Prev; 2013 Jun; 55():12-21. PubMed ID: 23510787
[TBL] [Abstract][Full Text] [Related]
19. Assessing factors causing severe injuries in crashes of high-deck buses in long-distance driving on freeways.
Chu HC
Accid Anal Prev; 2014 Jan; 62():130-6. PubMed ID: 24144498
[TBL] [Abstract][Full Text] [Related]
20. Exploring factors affecting the injury severity of freeway tunnel crashes: A random parameters approach with heterogeneity in means and variances.
Pervez A; Lee J; Huang H
Accid Anal Prev; 2022 Dec; 178():106835. PubMed ID: 36126361
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]