Vehicle Speed Prediction in a Convoy using V2V Communication

This paper proposes a speed prediction scheme for multi-vehicle car-following scenarios, which involves vehicle intelligence, human drivers, and vehicle dynamics interacting with one another, under low vehicular communication penetration rates. The algorithm relies on a small number of vehicles equipped with communication capabilities and utilizes car-following models to predict the targeted vehicle's states for a horizon of seconds. Information gained through the proposed prediction/deduction method is useful for applications such as extensions of Adaptive Cruise Control (ACC) or Cooperative Adaptive Cruise Control (CACC), especially for the development of ACC/CACC with optimal fuel economy or improved safety objectives. The developed methodology is illustrated and verified through simulation examples.