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This paper presents the design and implementation results of an ecologicaladaptive cruise controller (ECO-ACC) which exploits driving automation andconnectivity. The controller avoids front collisions and traffic lightviolations, and is designed to reduce the energy consumption of connectedautomated vehicles by utilizing historical and real-time signal phase andtiming data of traffic lights that adapt to the current traffic conditions. Wepropose an optimization-based generation of a reference velocity, and avelocity-tracking model predictive controller that avoids front collisions andviolations. We present an experimental setup encompassing the real vehicle andcontroller in the loop, and an environment simulator in which the traffic flowand the traffic light patterns are calibrated on real-world data. We presentand analyze simulation and experimental results, finding a significantpotential for energy consumption reduction, even in the presence of traffic.

Design and Implementation of Ecological Adaptive Cruise Control for Autonomous Driving with Communication to Traffic Lights