Injury severity analysis of e-bike riders in China based on the in-vehicle recording video crash data: a random parameter ordered logit model-Reference-Cited by-同舟云学术

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Injury severity analysis of e-bike riders in China based on the in-vehicle recording video crash data: a random parameter ordered logit model

Published:2024-07-29 Issue: Volume: Page:1-11
ISSN:1745-7300
Container-title:International Journal of Injury Control and Safety Promotion
language:en
Short-container-title:International Journal of Injury Control and Safety Promotion

Author:

Wang Changshuai¹²,Shao Yongcheng¹,Ye Fei³,Zhu Tong⁴

Affiliation:

1. School of Transportation, Southeast University, Nanjing, China

2. Institute of Transport Studies, Monash University, Clayton, VIC, Australia

3. School of Rail Transit, Zhejiang Institute of Communications, Hangzhou, China

4. College of Transportation Engineering, Chang’an University, Xi’an, China

Funder

China Scholarship Council

Postgraduate Research & Practice Innovation Program of Jiangsu Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17457300.2024.2385102

Reference59 articles.

1. A multinomial logit model of motorcycle crash severity at Australian intersections

2. Learning about injury severity from no-injury crashes: A random parameters with heterogeneity in means and variances approach

3. Accounting for unobserved heterogeneity and spatial instability in the analysis of crash injury-severity at highway-rail grade crossings: A random parameters with heterogeneity in the means and variances approach

4. Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review

5. Severity analysis for large truck rollover crashes using a random parameter ordered logit model

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