Predicting and explaining severity of road accident using artificial intelligence techniques, SHAP and feature analysis-Reference-Cited by-同舟云学术

Predicting and explaining severity of road accident using artificial intelligence techniques, SHAP and feature analysis

Published:2022-05-17 Issue:2 Volume:28 Page:186-201
ISSN:1358-8265
Container-title:International Journal of Crashworthiness
language:en
Short-container-title:International Journal of Crashworthiness

Author:

Panda Chakradhara¹,Mishra Alok Kumar²^ORCID,Dash Aruna Kumar³,Nawab Hedaytullah⁴

Affiliation:

1. Data Science, Publicis Sapient, Bengaluru, Karnataka, India

2. School of Economics, University of Hyderabad, Hyderabad, Telangana, India

3. Department of Economics, IBS Hyderabad, IFHE University, Telangana, India

4. Uber, Hyderabad, Telangana, India

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/13588265.2022.2074643

Reference63 articles.

1. WHO. Global status report on road safety 2018 summary. Geneva: World Health Organization; 2018. (WHO/NMH/NVI/18.20) License: CC BY-NC-SA 3.0 IGO).

2. Sustainable Development Goals. Road safety for all; 2019 Jan. [cited 2021 Jun 6]. Available from: https://unece.org/DAM/trans/roadsafe/publications/Road_Safety_for_All.pdf

3. WHO. Road traffic injuries. World Health Organization; 2020. [cited 2021 Jun 6]. Available from: https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries

4. The global macroeconomic burden of road injuries: estimates and projections for 166 countries

5. A novel Big Data analytics and intelligent technique to predict driver's intent

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