A sensitivity-based heuristic for economic optimal CAVs coordination in mixed traffic at intersections

This paper addresses the coordination problem of Connected and Automated Vehicles (CAVs) at unsignalized intersections in mixed traffic with Human-Driven Vehicles (HDVs). The proposed formulation targets traffic-efficient and energy-efficient objectives, while ensuring safety, thus resulting into a Mixed-Integer Nonlinear Program (MINLP), which is hardly solved in reasonable time. Hence a computationally-efficient heuristic is proposed in this paper, which relies on the predictor-corrector method from sensitivity analysis tools. We perform numerical simulations to evaluate the economic and computational performance of the proposed Sensitivity-based Heuristic (SH) against MINLP, First-Come, First-Serve (FCFS), and an Exact Heuristic (EH) and show that SH can reach close-to-economic optimal solutions while consistently being computationally fast across different mixed-traffic scenarios.