Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{169701,
        author = {Kartik Singh and Aastha Adhikari and Diksha Khullar and Gungun Singh and Kirti},
        title = {Cruise Control Using Traffic Sign Recognition Model for Autonomous Vehicles},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2222-2229},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169701},
        abstract = {Autonomous vehicles (AVs) are changing how transportation works, however the recognition of traffic signs and ensuring His safety and reliability is a challenge in terms of AVs performance in uncontrolled environments which are highly dynamic. Definitely one of the most important things is the ability to recognize speed limit signs and to an extent the ability to react by adjusting the speed of the vehicle. The researchers suggest an invention of a new cruise control system that incorporates a Mask R-CNN model in order to detect, classify and control the vehicle’s speed automatically using traffic signs. The development has been tested in the laboratory and on real cars in road networks with quite good results. The model has shown good precision in finding traffic signs and decreasing speed of that vehicle, thus it can effectively contribute to the improvement of the driving safety in the context of autonomous vehicles.},
        keywords = {Autonomous vehicles, Cruise control, Traffic sign recognition, Mask R-CNN, Speed limit detection, Object detection, Deep learning, Intelligent transportation systems.},
        month = {November},
        }