Applying machine learning approaches to analyze the vulnerable road-users' crashes at statewide traffic analysis zones.

Rahman, Md Sharikur; Abdel-Aty, Mohamed; Hasan, Samiul; Cai, Qing

Rahman, Md Sharikur; Abdel-Aty, Mohamed; Hasan, Samiul; Cai, Qing.

Rahman MS; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA. Electronic address: sharikur@knights.ucf.edu.
Abdel-Aty M; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA.
Hasan S; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA.
Cai Q; Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA.

J Safety Res ; 70: 275-288, 2019 09.

Article en En | MEDLINE | ID: mdl-31848006

Asunto(s)

Accidentes de Tránsito/prevención & control; Ciclismo; Aprendizaje Automático; Modelos Estadísticos; Vehículos a Motor; Peatones; Seguridad; Conducción de Automóvil; Planificación Ambiental; Humanos; Factores Socioeconómicos; Transportes

Palabras clave

Decision tree regression; Ensemble technique; Machine learning; Macro-level; Statewide traffic analysis zone

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Seguridad / Ciclismo / Accidentes de Tránsito / Modelos Estadísticos / Vehículos a Motor / Aprendizaje Automático / Peatones Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2019 Tipo del documento: Article

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