Energy-Optimal Control with Intelligent Crossing Decisions for Dilemma Zones at Signalized Intersections

Abstract

Connected automated vehicles (CAVs) can improve energy efficiency through eco-driving at signalized intersections by avoiding energy-wasting stop-and-go patterns. However, when a lead vehicle's behavior prevents safe non-stop passage, energy-optimal crossing may conflict with rear-end collision avoidance, creating a CAV-specific dilemma zone problem. This paper presents a novel control framework that couples energy-optimal trajectory planning with collision avoidance constraints. Using pontryagin's minimum principle, we derive analytical solutions that minimize energy while satisfying both green phase passage and rear-end safety constraints. The framework provides real-time feasibility verification to establish explicit go-or-stop decision criteria, transitioning to safe fallback modes when energy-optimal intersection crossing is infeasible. Simulation results demonstrate that the proposed approach achieves energy-efficient operation while ensuring collision-free fallback mode transitions across various dilemma zone scenarios.