Decentralized Optimal Control for Energy-Efficient Mobility Systems

Systems Conversation with Andreas A. Malikopoulos, University of Delaware

We are currently witnessing an increasing integration of energy and transportation, which, coupled with human interactions, is giving rise to a new level of complexity in the next generation of transportation systems. Connected and automated vehicles (CAVs) provide the most intriguing and promising opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to reduce energy consumption, greenhouse gas (GHG) emissions, travel delays and improve safety. While several studies have shown the benefits of CAVs to alleviate traffic congestion and reduce fuel consumption in specific transportation scenarios, one key question that remains unanswered is “how much can we improve fuel consumption, if we assume that the vehicles are connected and can exchange information with each other and with infrastructure?” In this talk, Andreas will present a decentralized optimal control framework whose closed-form solution exists under certain conditions, and which, based on Hamiltonian analysis, yields for each vehicle the optimal acceleration/deceleration at any time in the sense of minimizing fuel consumption. The solution allows the vehicles to cross the intersections and merging roadways without the use of traffic lights, without creating congestion, and under the hard safety constraint of collision avoidance.