Investigating contributing factors to injury severity levels in crashes involving pedestrians and cyclists using latent class clustering analysis and mixed logit models-Reference-Cited by-同舟云学术

Investigating contributing factors to injury severity levels in crashes involving pedestrians and cyclists using latent class clustering analysis and mixed logit models

Published:2021-07-28 Issue: Volume: Page:1-28
ISSN:1943-9962
Container-title:Journal of Transportation Safety & Security
language:en
Short-container-title:Journal of Transportation Safety & Security

Author:

Liu Shaojie¹^ORCID,Lin Zijing²,Fan Wei (David)¹^ORCID

Affiliation:

1. USDOT Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE), Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, Charlotte, North Carolina, USA

2. School of Transportation & Logistics, Dalian University of Technology, Dalian, Liaoning Province, China

Funder

U.S. Department of Transportation

Publisher

Informa UK Limited

Subject

Safety Research,Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19439962.2021.1958037

Reference60 articles.

1. Adminaite, D., Allsop, R. & Jost, G. (2015). Making walking and cycling on Europe's roads safer. Italy: European Transport Safety Council.

2. Exploring the determinants of pedestrian–vehicle crash severity in New York City