Unfolding the dynamics of driving behavior: a machine learning analysis from Germany and Belgium-Reference-Cited by-同舟云学术

Unfolding the dynamics of driving behavior: a machine learning analysis from Germany and Belgium

Published:2024-07-01 Issue:1 Volume:16 Page:
ISSN:1866-8887
Container-title:European Transport Research Review
language:en
Short-container-title:Eur. Transp. Res. Rev.

Author:

Roussou Stella^ORCID,Michelaraki Eva,Katrakazas Christos,Afghari Amir Pooyan,Al Haddad Christelle,Alam Md Rakibul,Antoniou Constantinos,Papadimitriou Eleonora,Brijs Tom,Yannis George

Abstract

AbstractThe i-DREAMS project focuses on establishing a framework known as the ‘Safety Tolerance Zone (STZ)’ to ensure drivers operate within safe boundaries. This study compares Long-Short-Term-Memory Networks and shallow Neural Networks to assess participants’ safety levels during i-DREAMS on-road trials. Thirty German drivers’ trips and Forty-Three Belgian drivers were analyzed using these methods, revealing factors contributing to risky behavior. Results indicate i-DREAMS interventions significantly enhance driving behavior, with Neural Networks displaying superior performance among the algorithms considered.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1186/s12544-024-00655-z.pdf

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