What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach

Author:

Zhu SiyingORCID,Meng QiangORCID

Funder

Ministry of Education - Singapore

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference142 articles.

1. A real-time crash prediction fusion framework: An imbalance-aware strategy for collision avoidance systems;Abou Elassad;Transp. Res. C,2020

2. Crash severity analysis of rear-end crashes in california using statistical and machine learning classification methods;Ahmadi;J. Transp. Saf. Secur.,2020

3. Crash themes in automated vehicles: A topic modeling analysis of the california department of motor vehicles automated vehicle crash database;Alambeigi,2020

4. IDDA: A large-scale multi-domain dataset for autonomous driving;Alberti;IEEE Robot. Autom. Lett.,2020

5. Apollo autonomous vehicle dataset;Apollo,2021

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