Bi-layer eco-driving control design of autonomous electric vehicles in presence of signalized intersections and preceding vehicles

Abstract

Adjusting the behavior of vehicles that approach a signalized intersection significantly reduces energy consumption. By virtue of connectivity, eco-driving can help managing a vehicle’s speed profile, resulting in higher energy efficiency. The present research studies the case of autonomous electric vehicles (AEVs) speed control in the presence of a preceding vehicle approaching and departing from a signalized intersection. A real-time dynamic bi-layer predictive cruise control eco-driving (eco-PCC) framework is developed that automatically switches its optimization layer by a switching logic based on a dynamic inter-vehicle safe distance. The lower layer uses a model predictive control (MPC)-based eco-driving model whose convexity is mathematically proved. The Gipps and eco-approach-and-departure (EAD) models are used as benchmarks to compare the performance of the proposed algorithm. Furthermore, real-world measurements study detailed practical scenarios. The results indicate that the proposed bi-layer control algorithm could notably contribute in reducing the energy consumption compared to conventional methods. The outcomes through assessing a broad number of scenarios targets to bring insights to AEV energy management strategy designers and control framework developers from all respects.