Enabling Safe Co‐Existence of Connected/Autonomous Cars and Road Users Using Machine Learning and Deep Learning Algorithms
ABSTRACT As the number of vehicles increases in cities, traffic accidents continue to rise. Connected and Autonomous Cars have become important because they aim to be safer than non‐intelligent vehicles. Connected and Autonomous Cars can reduce up to 90% of vehicular accidents caused by human drivers. Connected and Autonomous Cars must interact safely with other cars and Vulnerable Road Users because the latter are more susceptible to injury after a road collision. Thus, careful interaction between Connected and Autonomous Cars and Vulnerable Road Users is necessary to create a safer road ecosystem for Vulnerable Road Users. We discuss several interaction challenges that must be addressed between Connected and Autonomous Cars and Vulnerable Road Users, and we propose solutions to each challenge to achieve the safe coexistence of both Connected and Autonomous Cars and Vulnerable Road Users.
Authors
- Sherali Zeadally (ORCID: https://orcid.org/0000-0002-5982-8190)
- Juan Contreras‐Castillo (ORCID: https://orcid.org/0000-0002-0021-7897)
- Iyad Katib (ORCID: https://orcid.org/0000-0003-3376-3218)
- Pedro Cesar Santana-Mancilla (ORCID: https://orcid.org/0000-0002-4184-0116)
- Juan Antonio Guerrero Ibáñez (ORCID: https://orcid.org/0000-0001-6517-4421)
Institutions
- University of Kentucky (US)
- King Abdulaziz University (SA)
- University of Johannesburg (ZA)
- Universidad de Colima (MX)
Publication Details
- Journal
- Transactions on Emerging Telecommunications Technologies
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/ett.70103
- Citations
- 3
- Primary Topic
- Autonomous Vehicle Technology and Safety
- Type
- article
- Field-Weighted Citation Impact
- 2.05