| Autor: |
Ishita Agarwal, Aanchal Singh, Aran Agarwal, Shruti Mishra, Sandeep Kumar Satapathy, Sung-Bae Cho, Manas Ranjan Prusty, Sachi Nandan Mohanty |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 9963-9975 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3350271 |
| Popis: |
With the increasing reliance on technology in traffic management systems, ensuring road safety and protecting the integrity of these systems against cyber threats have become critical concerns. This research paper investigates the potential of reinforcement learning techniques in enhancing both road safety and cyber security of traffic management systems. The paper explores the theoretical foundations of reinforcement learning, discusses its applications in traffic management, and presents case studies and empirical evidence demonstrating its effectiveness in improving road safety and mitigating cyber security risks. The findings indicate that reinforcement learning can contribute to the development of intelligent and secure traffic management systems, thus minimizing accidents and protecting against cyber-attacks. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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