Energy-optimal Speed Trajectories between Stops and Their Parameter Dependence

Abstract

This paper addresses the problem of energy-optimal vehicle-speed trajectories between stops. The ideal parameter-dependent trajectory is introduced, and it is shown that it reduces transportation energy drastically relative to “typical trajectories” seen in traffic. The resulting trajectories can easily be implemented in self-driving cars and have the potential to significantly reduce transportation energy in networked vehicles and cities. The usage of this energy-optimal speed trajectories between stops can save significant amounts of energy, sometimes in excess of 30% when comparing to conventional traffic flow speed profiles. This paper also addresses the impact that vehicle and segment parameters have on the savings. The role of parameters such as the air drag coefficient, cross-sectional area, vehicle mass, efficiency, segment length, average speed, as well as acceleration capability are investigated. It is shown that optimizing speed trajectories to minimize transportation energy consistently results in energy savings. However, diminishing returns are observed for certain scenarios, such as long, low-speed segments.