136 related articles for article (PubMed ID: 34612168)
1. Spatial statistics and random forest approaches for traffic crash hot spot identification and prediction.
Atumo EA; Fang T; Jiang X
Int J Inj Contr Saf Promot; 2022 Jun; 29(2):207-216. PubMed ID: 34612168
[TBL] [Abstract][Full Text] [Related]
2. Spatial pattern identification and crash severity analysis of road traffic crash hot spots in Ohio.
Alam MS; Tabassum NJ
Heliyon; 2023 May; 9(5):e16303. PubMed ID: 37305499
[TBL] [Abstract][Full Text] [Related]
3. A spatial autocorrelation analysis of road traffic crash by severity using Moran's I spatial statistics: A comparative study of Addis Ababa and Berlin cities.
Gedamu WT; Plank-Wiedenbeck U; Wodajo BT
Accid Anal Prev; 2024 Jun; 200():107535. PubMed ID: 38489942
[TBL] [Abstract][Full Text] [Related]
4. Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile.
Blazquez CA; Picarte B; Calderón JF; Losada F
Accid Anal Prev; 2018 Nov; 120():195-210. PubMed ID: 30170294
[TBL] [Abstract][Full Text] [Related]
5. Exploring spatial autocorrelation of traffic crashes based on severity.
Soltani A; Askari S
Injury; 2017 Mar; 48(3):637-647. PubMed ID: 28126318
[TBL] [Abstract][Full Text] [Related]
6. Spatial patterns of off-the-system traffic crashes in Miami-Dade County, Florida, during 2005-2010.
Chance Scott M; Sen Roy S; Prasad S
Traffic Inj Prev; 2016 Oct; 17(7):729-35. PubMed ID: 26890148
[TBL] [Abstract][Full Text] [Related]
7. Comparison of Multivariate Poisson lognormal spatial and temporal crash models to identify hot spots of intersections based on crash types.
Cheng W; Gill GS; Dasu R; Xie M; Jia X; Zhou J
Accid Anal Prev; 2017 Feb; 99(Pt A):330-341. PubMed ID: 28043069
[TBL] [Abstract][Full Text] [Related]
8. Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots.
Washington S; Haque MM; Oh J; Lee D
Accid Anal Prev; 2014 May; 66():136-46. PubMed ID: 24531115
[TBL] [Abstract][Full Text] [Related]
9. Crash proximity and equivalent property damage calculation techniques: An investigation using a novel horizontal curve dataset.
Ryan A; Ai C; Fitzpatrick C; Knodler M
Accid Anal Prev; 2022 Mar; 166():106550. PubMed ID: 34971921
[TBL] [Abstract][Full Text] [Related]
10. Spatial analysis to identify high risk areas for traffic crashes resulting in death of pedestrians in Tehran.
Moradi A; Soori H; Kavousi A; Eshghabadi F; Jamshidi E; Zeini S
Med J Islam Repub Iran; 2016; 30():450. PubMed ID: 28210615
[No Abstract] [Full Text] [Related]
11. Hot spot analysis and evaluation of influencing factors on regional road crash safety and severity indices: insights from Iran.
Ahmadpur M; Yasar I
Int J Inj Contr Saf Promot; 2023 Dec; 30(4):629-642. PubMed ID: 37585710
[TBL] [Abstract][Full Text] [Related]
12. Applying a joint model of crash count and crash severity to identify road segments with high risk of fatal and serious injury crashes.
Afghari AP; Haque MM; Washington S
Accid Anal Prev; 2020 Sep; 144():105615. PubMed ID: 32534289
[TBL] [Abstract][Full Text] [Related]
13. Using spatial interpolation to determine impacts of annual snowfall on traffic crashes for limited access freeway segments.
Heqimi G; Gates TJ; Kay JJ
Accid Anal Prev; 2018 Dec; 121():202-212. PubMed ID: 30261363
[TBL] [Abstract][Full Text] [Related]
14. Traffic crash analysis with point-of-interest spatial clustering.
Jia R; Khadka A; Kim I
Accid Anal Prev; 2018 Dec; 121():223-230. PubMed ID: 30265908
[TBL] [Abstract][Full Text] [Related]
15. Pattern of road traffic crash hot zones versus probable hot zones in Tunisia: A geospatial analysis.
Ouni F; Belloumi M
Accid Anal Prev; 2019 Jul; 128():185-196. PubMed ID: 31051409
[TBL] [Abstract][Full Text] [Related]
16. Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation.
Chen C; Zhang G; Liu XC; Ci Y; Huang H; Ma J; Chen Y; Guan H
Accid Anal Prev; 2016 Dec; 97():69-78. PubMed ID: 27591415
[TBL] [Abstract][Full Text] [Related]
17. Exploring pedestrian injury severities at pedestrian-vehicle crash hotspots with an annual upward trend: A spatiotemporal analysis with latent class random parameter approach.
Song L; Fan WD; Li Y; Wu P
J Safety Res; 2021 Feb; 76():184-196. PubMed ID: 33653550
[TBL] [Abstract][Full Text] [Related]
18. Geographically weighted machine learning for modeling spatial heterogeneity in traffic crash frequency and determinants in US.
Wang S; Gao K; Zhang L; Yu B; Easa SM
Accid Anal Prev; 2024 May; 199():107528. PubMed ID: 38447355
[TBL] [Abstract][Full Text] [Related]
19. A two-phase clustering approach for traffic accident black spots identification: integrated GIS-based processing and HDBSCAN model.
Wang D; Huang Y; Cai Z
Int J Inj Contr Saf Promot; 2023 Jun; 30(2):270-281. PubMed ID: 36608271
[TBL] [Abstract][Full Text] [Related]
20. Measuring the spatiotemporal evolution of accident hot spots.
Al Hamami M; Matisziw TC
Accid Anal Prev; 2021 Jul; 157():106133. PubMed ID: 33989871
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
