Vehicle platooning is an advanced vehicle maneuver that allows for the simultaneous control of several vehicles traveling on the roadway cite{al2010experimental}. Automated platoons, when activated in tractor trailer convoys, have a high potential of increasing the fuel efficiency and improving the utilization of roadways by allowing more vehicles to share the road at the same time. The increased fuel efficiency translates to lower cost on goods and motivates a more environmentally friendly and sustainable economy. In order to achieve the promised fuel savings from vehicle platooning, the vehicles need to follow each other at shorter headways than in typical driving scenarios. The reduced separation distance between the lead and follow vehicle reduces visibility and the reaction time available for the follow vehicle; this renders most modern Active Driver Assist Systems (ADAS) ineffective since they are not designed for operation in such short headway conditions. The focus of this work is related to understanding and improving the failures of Lane Keep Assist (LKA) systems in the follow vehicles of a platoon. In this work, the source of lane detection degradation when using a monocular forward facing camera in short headway platooning is identified. Furthermore, a novel lane augmentation algorithm is proposed to improve the lane detection capability of follow vehicles in a platoon. The lane augmentation process utilizes a longitudinal transformation of lane parameters from the lead to the follow vehicles. The transformation utilizes an accurate understanding of the relative spatial position and orientation of the two vehicles. The transformation also requires a reliable communication system between the two vehicles such as a Vehicle-to-Vehicle (V2V) module. The work presented in this thesis develops theory, simulation and verification using real world data of the proposed cooperative lane augmentation. The results of this work indicate that it is possible to improve vehicle platooning performance by distributing the required sensing across multiple agents of the platoon. / Master of Science / Vehicle platooning is an advanced vehicle maneuver that allows for the simultaneous control of several vehicles traveling on the roadway cite{al2010experimental}. Automated platoons, when activated in tractor trailer convoys, have a high potential of increasing the fuel efficiency and improving the utilization of our roadways by allowing more vehicles to share the road at the same time. The increased fuel efficiency translates to lower cost on goods and motivates a more environmentally friendly and sustainable economy. In order to achieve the promised fuel savings from vehicle platooning, the vehicles need to follow each other at closer distances (headway) than in typical driving scenarios. The reduced separation distance between the lead and follow vehicle reduces visibility and the reaction time available for the follow vehicle; this renders most modern Active Driver Assist Systems (ADAS) ineffective since they are not designed for operation in such short headway conditions. The focus of this work is related to understanding and improving the failures of Lane Keep Assist (LKA) systems - the automated system used to keep the vehicle in the center of the lane - in the follow vehicles of a platoon. In the proposed scenario, the LKA uses a single forward facing camera to detect the lane lines ahead of the vehicle. The detected lanes serve as inputs to the lateral position (steering) controller in order to keep the vehicle in the center of the lane. In this work, the source of lane detection degradation in a follow vehicle of a short headway platoon is identified. Furthermore, a novel cooperative lane detection algorithm is proposed to improve the lane detection capability of the follow vehicles. The proposed algorithm utilizes lane information transformed from the lead to follow vehicle frame. The transformation utilizes the relative spatial position and orientation of the two vehicles. Additionally, a reliable communication protocol between the vehicles is required to transport the lane information. The work presented in this thesis develops theory, simulation and verification using real world data of the proposed algorithm. The results of this work indicate that lane keeping performance in a platoon can be improved using cooperative lane detection.