A Platooning Strategy for Automated Vehicles in the Presence of Speed Limit Fluctuations

Abstract

Platooning is expected to enhance the efficiency of operating automated vehicles. The positive impacts of platooning on travel time reliability, congestion, emissions, and energy consumption have been shown for homogenous roadway segments. However, the transportation system consists of inhomogeneous segments, and understanding the full impacts of platooning requires investigation in a realistic setup. One of the main reasons for inhomogeneity is speed limit fluctuations. Speed limit changes frequently throughout the transportation network, due to safety-related considerations (e.g., changes in geometry and workzone operations) or congestion management schemes (e.g., speed harmonization systems). In the current transportation systems with human-driven vehicles, these speed drops can potentially result in shockwave formation, which can cause travel time unreliability. Automated vehicles, however, have the potential to prevent shockwave formation and propagation and, therefore, enhance travel time reliability. Accordingly, this study presents a constant time headway strategy for automated vehicle platooning to ensure accurate tracking of any velocity profile in the presence of speed limit fluctuations. The performance of the presented platooning strategy is compared with Gipps’ car-following model and intelligent driver model, as representatives of regular non-automated vehicles. Simulation results show that implementing a fully autonomous system prevents shockwave formation and propagation, and enhances travel time reliability by accurately tracking the desired velocity profile. Moreover, the performance of platoons of regular and automated vehicles is investigated in the presence of a speed drop. The results show that as the market penetration rate of automated vehicles increases, the platoon can track the velocity profile more accurately.