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Cited by 179Autonomous Vehicle Technology and SafetyReinforcement Learning in RoboticsAdvanced Neural Network Applications

A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving

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Elallid, Badr Ben, Benamar, Nabil, Hafid, Abdelhakim Senhaji, Rachidi, Tajjeeddine, Mrani, Nabil·2022·Journal of King Saud University - Computer and Information Sciences
DOI 10.1016/j.jksuci.2022.03.013
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Abstract

Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence (AI) have stimulated and paved the way toward the widespread introduction of Autonomous Vehicles (AVs). This has opened new opportunities for smart roads, intelligent traffic safety, and traveler comfort. Autonomous Vehicles have become a highly popular research topic in recent years because of their significant capability to reduce road accidents and human injuries. This paper is an attempt to survey all recent AI based techniques used to deal with major functions in AVs, namely scene understanding, motion planning, decision making, vehicle control, social behavior, and communication. Our survey focuses solely on deep learning and reinforcement learning based approaches; it does not include conventional (shallow) shallow based techniques, a subject that has been extensively investigated in the past. Our survey builds a taxonomy of DL and RL algorithms that have been used so far to bring solutions to the four main issues in autonomous driving. Finally, this survey highlights the open challenges and points out possible future research directions.

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Cited by

Sorted by citations

Authors
Elallid, B. B., Benamar, N., Hafid, A. S., Rachidi, T., & Mrani, N.
Affiliations
  • Université Moulay Ismail de Meknes (MA)
  • Université de Montréal (CA)
  • Al Akhawayn University (MA)
Corresponding author
  • Elallid, Badr Ben
  • Benamar, Nabil
ORCID
Venue
Journal of King Saud University - Computer and Information Sciences
Publisher
Springer Science and Business Media LLC
Published
2022-10
Volume
34
Issue
9
Pages
7366-7390
ISSN
1319-1578 (ISSN-L)
DOI
10.1016/j.jksuci.2022.03.013
OpenAlex
W4226286144
Cited by
179
References
5
Citations by year
2026: 23 · 2025: 64 · 2024: 56 · 2023: 34 · 2022: 2
FWCI
10.38
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of King Saud University - Computer and Information Sciences (publishedVersion, cc-by)
  • Greater South Information System
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords
autonomous driving, autonomous vehicles, deep learning, reinforcement learning, scene understanding, motion planning, decision-making, vehicle control, social behavior, vehicle-to-vehicle communication, intelligent transportation systems

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