Pennsylvania State University (Penn State)

Modern drivers are skilled at anticipating and reacting to the behavior of nearby vehicles and the environment in order to travel safely. Nevertheless, all drivers operate with an information gap – a level of uncertainty that limits vehicle energy efficiency. For instance, safe driving demands that drivers leave appropriate space between vehicles and cautiously approach intersections, because one can never fully know the intentions of nearby vehicles or yet unseen traffic conditions. Closing this information gap can enable vehicles to operate in more energy efficient ways. The increased development of connected and automated vehicle systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles. Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X) technologies will allow a vehicle to “know” its future operating environment with some degree of certainty, greatly narrowing previous information gaps. By providing the ability to predict driving conditions, these technologies could operate the vehicle powertrain (including the engine, transmission, and other components) more intelligently, generating significant vehicle energy savings.

Pennsylvania State University (Penn State) will develop a predictive control system that will use vehicle connectivity to reduce fuel consumption for a heavy duty diesel vehicle by at least 20% without compromising emissions, drivability, mobility, or safety. The technology will work to achieve four individual and complementary goals that co-optimize vehicle dynamic and powertrain control. First, it will exploit connected communication to anticipate traffic/congestion patterns on different roads, traffic light timing, and the speed trajectories of surrounding vehicles. Second, the system will coordinate with surrounding vehicles to achieve platooning on the highway, coordinated departures/arrivals at intersections, and consistency in the speed trajectories both within vehicle platoons and among neighboring vehicles that are not in a platoon. Platooning will allow vehicles to collectively reduce their aerodynamic losses, thereby reducing their fuel consumption. Coordinating vehicle departures and arrivals at intersections will minimize energy loss due to braking, idling, and inefficient departures. As its third goal, the technology will optimize vehicle dynamic control decisions such as the choice of route, the trajectory of vehicle speed versus time in a given road segment, and the choice of whether the vehicle is in an acceleration, deceleration, or coasting state at different points in time. Optimal routing will reduce fuel consumption by avoiding the fuel penalties associated with congestion and/or hilly terrains as much as possible. Finally, the technology will also optimize powertrain control decisions to eliminate unnecessary engine idling. Software for each of the goals will constitute a standalone product that can be commercialized independently of the others, but together, they will operate in an integrated manner to achieve co-optimized and coordinated vehicle control. If successful, this will result in vehicles that operate in a predictive manner, taking into account all the available data and information to produce the best outcome for vehicle fuel consumption, drivability, mobility, emissions, and safety.

If successful, Penn State’s project will enable at least an additional 20% reduction in energy consumption of future connected and automated vehicles.