Ecological Adaptive Cruise Control for Urban Environments using SPaT Information

This paper proposes an ecological adaptive cruise control (EACC) strategy to minimize the energy consumption of an electric vehicle using two linear model predictive controllers (MPCs). In the absence of a preceding vehicle, the first MPC uses the upcoming traffic light signal phase and timing (SPaT) information to track an optimal green-wave velocity to reach the next traffic light signal during green phase. For the preceding vehicle in range scenario, the second MPC follows the leading vehicle by maintaining a desired inter-vehicle distance and strictly adheres to road speed limits. If the upcoming traffic light signal phase is changing to red, the controller uses the SPaT information to plan an energy-efficient stop near the traffic light signal. To evaluate the performance of the proposed strategy, both controllers are tested in a realistic scenario against a baseline controller and furthermore their energy saving benefits are explored. Finally, investigations on computation time reveal that the proposed strategy is capable for online implementation.