294 related articles for article (PubMed ID: 29776524)
1. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.
Chen F; Chen S; Ma X
J Safety Res; 2018 Jun; 65():153-159. PubMed ID: 29776524
[TBL] [Abstract][Full Text] [Related]
2. Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models.
Chen F; Chen S; Ma X
Int J Environ Res Public Health; 2016 Jun; 13(6):. PubMed ID: 27322306
[TBL] [Abstract][Full Text] [Related]
3. Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data.
Chen F; Ma X; Chen S; Yang L
Int J Environ Res Public Health; 2016 Oct; 13(11):. PubMed ID: 27792209
[TBL] [Abstract][Full Text] [Related]
4. Identifying crash-prone traffic conditions under different weather on freeways.
Xu C; Wang W; Liu P
J Safety Res; 2013 Sep; 46():135-44. PubMed ID: 23932695
[TBL] [Abstract][Full Text] [Related]
5. Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach.
Fountas G; Sarwar MT; Anastasopoulos PC; Blatt A; Majka K
Accid Anal Prev; 2018 Apr; 113():330-340. PubMed ID: 29494994
[TBL] [Abstract][Full Text] [Related]
6. Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects.
Xie M; Cheng W; Gill GS; Zhou J; Jia X; Choi S
Traffic Inj Prev; 2018 Feb; 19(2):207-213. PubMed ID: 28837362
[TBL] [Abstract][Full Text] [Related]
7. Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data.
Yu R; Abdel-Aty M
Accid Anal Prev; 2014 Jan; 62():161-7. PubMed ID: 24172082
[TBL] [Abstract][Full Text] [Related]
8. Refined-scale panel data crash rate analysis using random-effects tobit model.
Chen F; Ma X; Chen S
Accid Anal Prev; 2014 Dec; 73():323-32. PubMed ID: 25269099
[TBL] [Abstract][Full Text] [Related]
9. Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events-Concept of event-based driving volatility.
Wali B; Khattak AJ; Karnowski T
Accid Anal Prev; 2019 Nov; 132():105277. PubMed ID: 31514087
[TBL] [Abstract][Full Text] [Related]
10. Effect of driver's age and side of impact on crash severity along urban freeways: a mixed logit approach.
Haleem K; Gan A
J Safety Res; 2013 Sep; 46():67-76. PubMed ID: 23932687
[TBL] [Abstract][Full Text] [Related]
11. A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.
Zeng Z; Zhu W; Ke R; Ash J; Wang Y; Xu J; Xu X
Accid Anal Prev; 2017 Feb; 99(Pt A):51-65. PubMed ID: 27870986
[TBL] [Abstract][Full Text] [Related]
12. Contributing factors to vehicle to vehicle crash frequency and severity under rainfall.
Jung S; Jang K; Yoon Y; Kang S
J Safety Res; 2014 Sep; 50():1-10. PubMed ID: 25142355
[TBL] [Abstract][Full Text] [Related]
13. How to determine an optimal threshold to classify real-time crash-prone traffic conditions?
Yang K; Yu R; Wang X; Quddus M; Xue L
Accid Anal Prev; 2018 Aug; 117():250-261. PubMed ID: 29727862
[TBL] [Abstract][Full Text] [Related]
14. Road safety from the perspective of driver gender and age as related to the injury crash frequency and road scenario.
Russo F; Biancardo SA; Dell'Acqua G
Traffic Inj Prev; 2014; 15(1):25-33. PubMed ID: 24279963
[TBL] [Abstract][Full Text] [Related]
15. Contributing factors of crash injury severity at public highway-railroad grade crossings in the U.S.
Haleem K; Gan A
J Safety Res; 2015 Jun; 53():23-9. PubMed ID: 25933994
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. 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]
18. Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model.
Chen C; Zhang G; Huang H; Wang J; Tarefder RA
Accid Anal Prev; 2016 Nov; 96():79-87. PubMed ID: 27505099
[TBL] [Abstract][Full Text] [Related]
19. Analysis of real-time crash risk for expressway ramps using traffic, geometric, trip generation, and socio-demographic predictors.
Wang L; Abdel-Aty M; Lee J; Shi Q
Accid Anal Prev; 2019 Jan; 122():378-384. PubMed ID: 28689932
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
