SkyGrid: Energy-Flow Optimization at Harmonized Aerial Intersections

TL;DR

This paper addresses energy-efficient, high-throughput management of aerial intersections for urban air mobility using rhythmic control. It builds a multi-objective framework that jointly optimizes intersection flow and energy consumption by selecting path distributions and polynomial segment trajectories within a harmonized intersection grid, while enforcing safety via virtual platoons and platoon spacing. The contributions include (i) a formal system model with a grid-based intersection graph and left-turn handling, (ii) a tractable energy-flow formulation across straight and curved segments, and (iii) an optimization approach solved with COBYLA that demonstrates Pareto-optimal trade-offs under varying demand and safety parameters. The findings show that the method can increase throughput while reducing average power, with clear safety-energy-throughput trade-offs that inform practical UAM corridor design and real-time traffic management.

Abstract

The rapid evolution of urban air mobility (UAM) is reshaping the future of transportation by integrating aerial vehicles into urban transit systems. The design of aerial intersections plays a critical role in the phased development of UAM systems to ensure safe and efficient operations in air corridors. This work adapts the concept of rhythmic control of connected and automated vehicles (CAVs) at unsignalized intersections to address complex traffic control problems. This control framework assigns UAM vehicles to different movement groups and significantly reduces the computation of routing strategies to avoid conflicts. In contrast to ground traffic, the objective is to balance three measures: minimizing energy utilization, maximizing intersection flow (throughput), and maintaining safety distances. This optimization method dynamically directs traffic with various demands, considering path assignment distributions and segment-level trajectory coefficients for straight and curved paths as control variables. To the best of our knowledge, this is the first work to consider a multi-objective optimization approach for unsignalized intersection control in the air and to propose such optimization in a rhythmic control setting with time arrival and UAM operational constraints. A sensitivity analysis with respect to inter-platoon safety and straight/left demand balance demonstrates the effectiveness of our method in handling traffic under various scenarios.

Figures (12)

• Figure 1: An abstract model for an aerial intersection; the shared airspace of two crossing air corridors.
• Figure 2: Right-of-way allocation for a sample node. Blue and red colors represent NS and EW movement.
• Figure 3: Right-of-way allocation for NS and EW movement groups considering a guard band of $l_g$ and following distance of $d^{p}_f$.
• Figure 4: A 4-way Intersection graph, a discretized rhythm reference for rhythmic control on an aerial intersection cube.
• Figure 5: Seat-based platooning model, $l_v$ is the length of the vehicle and $d_f^{min}$ represents the minimum following distance.