A Terminal-Velocity Heuristic Method for Speed Optimization of EVs in Multi-Intersection Scenarios

Abstract

<div class="section abstract"><div class="htmlview paragraph">The optimization of speed holds critical significance for pure electric vehicles. In multi-intersection scenarios, the determination of terminal velocity plays a crucial role in addressing the complexities of the speed optimization problem. However, prevailing methodologies documented in the literature predominantly adhere to a fixed speed constraint derived from traffic light regulations, serving as the primary basis for the terminal velocity constraint. Nevertheless, this strategy can result in unnecessary acceleration and deceleration maneuvers, consequently leading to an undesirable escalation in energy consumption. To mitigate these issues and attain an optimal terminal velocity, this paper proposes an innovative speed optimization method that incorporates a terminal-velocity heuristic. Firstly, a traffic light state model is established to determine the speed range required to avoid coming to a stop at signalized intersections. Subsequently, by addressing the effect of vehicle spacing and utilizing a fitted model of energy consumption within the permissible speed range, an optimal cruising speed trajectory that minimizes energy usage is derived. Finally, the optimal cruising speed becomes a terminal velocity constraint term in the optimization problem, which is solved using a model predictive control algorithm. To assess the effectiveness of the proposed speed planning algorithm, a benchmark algorithm is selected for comparison, which traverses a traffic intersection at the onset of the green light window. Both the proposed algorithm and the benchmark algorithm are tested in two distinct traffic flow scenarios, and the results demonstrate that the proposed optimization algorithm achieves energy savings of 1.5704% and 1.1583%, respectively, making it energy efficient.</div></div>