Efficient Driving with Automated and Connected Vehicles Algorithms, Microsimulations, and Cyber-Physical Experiments

The shift that we are witnessing toward automated, connected, electric, and shared vehicular transportation is likely to be the most disruptive since the early days of automobiles. Improved safety, increased comfort, and time saving potential are among the most anticipated positive impacts of automated and connected vehicles. With much easier access to information, increased processing power, and precision control, automated and connected vehicles also offer unprecedented opportunities for energy efficient movement of people and goods and enable more efficient road use. This talk takes a closer look at the energy saving and traffic efficiency potentials of automated and connected vehicles based on first principles of motion, optimal control theory, and practical examples from our past and ongoing research. For instance, the talk shows through experiments on streets of San Francisco, that considerable energy can be saved by coordinated movement at traffic lights. In highway driving, our optimal motion planning algorithms that adjust the speed and select the best lane via mixed integer optimization, save energy by anticipating the motion of human drivers or by wirelessly receiving the intentions of neighboring automated vehicles. Energy efficient motion of these automated vehicles has a harmonizing effect on mixed traffic, leading to additional benefits for upstream human-driven vehicles. Opportunities for cooperative driving further increases efficiency of a group of vehicles by allowing them to move in a coordinated manner. In this talk, these benefits are shown in mixed traffic microsimulations, as well as shown in a novel cyber-physical experiment with virtual traffic surrounding real automated vehicles on a test track. Throughout the talk the gaps and future research directions are also highlighted.