Pedestrian Intention Prediction in Autonomous Vehicles: A Review on Context-Aware Features Importance

This is a preprint and may not have undergone formal peer review

Azarmi, M., Rezaei, M. orcid.org/0000-0003-3892-421X, Wang, H. et al. (1 more author) (2025) Pedestrian Intention Prediction in Autonomous Vehicles: A Review on Context-Aware Features Importance. [Preprint - SSRN]

Abstract

Metadata

Item Type: Preprint
Authors/Creators:
Keywords: Autonomous Vehicles; Pedestrian Crossing Behaviour; Pedestrian Intention Prediction; Computer Vision; Deep Neural Networks; Permutation Importance; Feature Importance Analysis
Dates:
  • Published: 15 February 2025
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 08 Jul 2025 10:40
Last Modified: 08 Jul 2025 10:40
Identification Number: 10.2139/ssrn.5139506
Open Archives Initiative ID (OAI ID):

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