Energy-Efficient Connected and Automated Vehicles: Real-Time Traffic Prediction-Enabled Co-Optimization of Vehicle Motion and Powertrain Operation
Yunli Shao, Zongxuan Sun
Abstract
Connected and automated vehicles (CAVs) can bring energy, mobility, and safety benefits to transportation. Energy savings can be achieved by solving a mathematical optimization problem for a lookahead horizon using previewed traffic information enabled by connectivity. However, it is challenging to predict shortterm traffic, especially for mixed-traffic scenarios, where both connected and unconnected vehicles are on the road.
Topics & Concepts
PowertrainAutomotive engineeringEnergy (signal processing)EngineeringComputer scienceTransport engineeringReal-time computingPhysicsTorqueStatisticsThermodynamicsMathematicsTraffic control and managementVehicle emissions and performanceVehicular Ad Hoc Networks (VANETs)