Adaptive Cruise Control Employing Taillight Tracking for a Platoon of Autonomous Vehicles

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Traffic congestions in urban cities unwantedly form platoons of vehicles running at low speeds. For vehicles operated by human drivers, reaction to speeding up or down requires some time, thus, increasing travel time. In this study, we present an adaptive cruise control for a group of autonomous vehicles that follow each other. We propose a taillight tracking system by utilizing low-cost dashboard cameras for detecting the position of the lead vehicle and then allow autonomous vehicles to correctly accelerate or decelerate depending on the nature of traffic. This is achieved by detecting the leading vehicle’s taillight via linear AND-ing of the the RGB and HSV color model representations. We evaluate the proposed system by employing real captured traffic images and tested by utilizing mobile robots for the platoon of vehicles testing.