Integration of machine learning and statistical models for crash frequency modeling-Reference-Cited by-同舟云学术

Integration of machine learning and statistical models for crash frequency modeling

Published:2022-12-17 Issue: Volume: Page:1-12
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Zhou Dongqin¹,Gayah Vikash V.¹,Wood Jonathan S.²

Affiliation:

1. Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA 16802, USA

2. Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA

Funder

Seed grant through the Penn State Institute of CyberScience

supported by the

Publisher

Informa UK Limited

Subject

Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2022.2158257

Reference69 articles.

1. Analysis of Road Crash Frequency with Spatial Models

2. Albin, R., V. Brinkly, J. Cheung, F. Julian, C. Satterfield, W. J. Stein, and F. R. Hanscom. 2016. Low-cost treatments for horizontal curve safety 2016 (No. FHWA-SA-15-084).” https://rosap.ntl.bts.gov/view/dot/50421

3. Permutation importance: a corrected feature importance measure

4. A note on modeling vehicle accident frequencies with random-parameters count models

5. Cross-Validation Methods

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