Vehicle platooning has gained attention for its potential to increase road capacity and safety, and higher fuel efficiency. Platoon controls are implemented over Vehicle-to-Vehicle (V2V) wireless communication, in-vehicle networks and Electronic Control Units (ECUs). V2V communication has a low message rate imposed by the V2V standard compared to the rate of modern in-vehicle networks and ECUs. The platoon control strategy should take into account such multi-rate nature of the implementation architecture for higher performance. Current literature does not explicitly consider such real-life constraints. We propose a two-layered control framework for vehicle platoons wirelessly communicating complying with the industrial standard IEEE 802.11p. In the upper-layer, vehicles receive state information from the immediate preceding vehicle over a control channel at 10 Hz under the IEEE 802.11p standard with occasional packet drops. Using such information and the vehicle state information, the engine control system, i.e. the lower-layer, realizes the desired vehicle state (e.g., acceleration) over the fast and reliable in-vehicle networks (e.g., FlexRay, Ethernet). In this work, a distributed model predictive control framework is proposed for the upper-layer targeting a Predecessor-Follower (PF) topology. A state-feedback control scheme is proposed for realizing the desired vehicle states for the lower-layer. Our framework minimizes the inter-vehicle distance and the tracking error enforcing collision avoidance and robustness against packet drops at the upper-layer. We validate our algorithm in simulation using our co-simulation framework CReTS and on an embedded platform, developed by Cohda Wireless and NXP, running in real time and communicating through the IEEE 802.11p standard. With extensive simulations and experiments, we evaluate the performance and feasibility of the proposed framework under a number of practical constraints. Our approach is a step towards the implementation of platoon control in reality.
|Tijdschrift||Transportation Research Part C: Emerging Technologies|
|Status||Gepubliceerd - mrt 2021|