Many significant advances have been made in autonomous vehicle technology over the recent decades. This includes platooning of heavy trucks. As such, many institutions have created their own version of the basic platooning platform. This includes the California PATH program [1], Japan’s ”Energy ITS” project [2], and Auburn University’sCACC Platform [3]. One thing these platforms have in common is a strong dependence on GPS based localization solutions. Issues arise when the platoon navigates into challenging environments, including rural areas with foliage which might block receptions, or more populated areas which might present urban canyon effects. Recent research focus has shifted to handling these situations through the use of alternative sensors, including cameras. The perception method proposed in this paper utilizes the You Only Look Once (YOLO) real-time object detection algorithm in order to bound the lead vehicle using both RGB and IR cameras. Range and bearing are determined using various methods. The methods are then tested on real world data.