An innovative new technique cloud-based adaptive cruise control (ACC) uses data analysis and cloud computing to make driving safer and more efficient. Current ACC systems in the cloud depend on static models or rules, to handle the ever-changing nature of traffic. It provide a data-driven method for ACC in the cloud that makes use of the k-nearest neighbours (KNN) algorithm to adapt the vehicle's speed and distance based on learning from both past and present driving data. For this ACC system in the cloud and develop a protocol for communication between vehicles and the cloud, as well as a distance and speed controller based on KNN. It tests the method against both traditional ACC and human drivers in a simulated environment to view how well it performs. In a number of traffic situations, the method outperforms both the human driver and traditional ACC in terms of safety, comfort, and fuel economy. The system's cloud-based architecture allows it to access and understand vast volumes of real-time data, providing drivers with an exhaustive and current data of the environment ahead. The system simulates real-world studies to test the effectiveness of the proposed method, demonstrating how it may improve road safety and traffic flow. When data-driven decision-making is combined with ACC it demonstrates how cloud-based technology may be used to improve road safety and advance the field of intelligent transportation.
Data-Driven Drive Safety with Cloud-based Adaptive Cruise Control using K-Nearest Neighbors Algorithm
18.04.2024
289245 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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