AI-BASED TRAFFIC CONTROLLING SYSTEM : A Literature Review of Computer Vision, Reinforcement Learning, and IoT Approaches
Traffic jams become a frequent issue in rapidly growing cities; however, the time-fixed lights do not adjust properly to changing car traffic. In this paper, different approaches using the following elements: artificial intelligence, computer vision, reinforcement learning, deep learning, and Internet of Things have been discussed in the field of traffic control. With these methods, traffic can be detected and adjusted for in real time. However, there are several issues which should be resolved in the future, such as bad weather conditions, different traffic, high computational requirements, and others.
Authors
- Supriya Survase
- Tejas Pavali
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-26
- DOI
- https://doi.org/10.5281/zenodo.23656131
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.00