| Title |
A smart algorithm for traffic lights intersections control in developing countries |
| ID_Doc |
44323 |
| Authors |
Olaya-Quiñones, JD; Perafan-Villota, JC |
| Title |
A smart algorithm for traffic lights intersections control in developing countries |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/ColCACI52978.2021.9469581 |
| Abstract |
Traffic jam is a problem that directly affects the quality of life of the population in large cities. This problem exacerbates at road intersections, where obsolete traffic control systems based on a static set of rules remain in use. We propose an algorithm that improves vehicular flow control at traffic-light intersections by optimizing a dynamic allocation of times. We train our own YOLO detector using a set of images captured from traffic cameras installed at a cross-road. Based on the number of vehicles detected in each intersection road, one set of rules was created and used by a fuzzy control. Since, at the local level, there are few traffic cameras installed on intersections. We build a simulated environment both to train our detector system and verify the efficiency of our algorithm. |
| Author Keywords |
Smart city; Traffic jam; Deep learning; Fuzzy Logic; YOLO; Unit3D |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000853145100011 |
| WoS Category |
Computer Science, Artificial Intelligence |
| Research Area |
Computer Science |
| PDF |
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