  Connected and Automated Vehicles (CAVs) have real-time information from the
surrounding environment by using local on-board sensors, V2X
(Vehicle-to-Everything) communications, pre-loaded vehicle-specific lookup
tables, and map database. CAVs are capable of improving energy efficiency by
incorporating these information. In particular, Eco-Cruise and Eco-Lane
Selection on highways and/or motorways have immense potential to save energy,
because there are generally fewer traffic controllers and the vehicles keep
moving in general. In this paper, we present a cooperative and energy-efficient
lane-selection strategy named MultiCruise, where each CAV selects one among
multiple candidate lanes that allows the most energy-efficient travel.
MultiCruise incorporates an Eco-Cruise component to select the most
energy-efficient lane. The Eco-Cruise component calculates the driving
parameters and prospective energy consumption of the ego vehicle for each
candidate lane, and the Eco-Lane Selection component uses these values. As a
result, MultiCruise can account for multiple data sources, such as the road
curvature and the surrounding vehicles' velocities and accelerations. The
eco-autonomous driving strategy, MultiCruise, is tested, designed and verified
by using a co-simulation test platform that includes autonomous driving
software and realistic road networks to study the performance under realistic
driving conditions. Our experimental evaluations show that our eco-autonomous
MultiCruise saves up to 8.5% fuel consumption.
