High-Density Automated Valet Parking with Relocation-Free Sequential Operations

A team of researchers has introduced DROP (high-Density Relocation-free sequential OPerations), a novel algorithmic framework designed to revolutionize automated valet parking systems. The core innovation addresses a critical inefficiency in current high-density robotic parking: the need to temporarily relocate multiple vehicles to retrieve a single car, which wastes time, energy, and space. DROP solves this by jointly optimizing both the physical layout of the parking area and the sequence of parking and retrieval operations from the start. It formulates the "no relocation" requirement as explicit logical conditions using boolean variables, allowing a computer to systematically plan every vehicle's path to ensure any car can leave without moving others.

The system employs recursive search strategies to derive these conditions and enumerate all possible relocation-free sequences under real-world operational constraints. The researchers validated DROP through extensive simulations, demonstrating its potential to dramatically improve parking lot area utilization while completely eliminating relocation shuffles. This isn't just a theoretical improvement; the team also tested its viability on application problems with prescribed operational orders, proving it works for practical scenarios like valet services or shared mobility hubs. The result is a system that can pack more cars into the same footprint while making retrieval instantaneous and efficient, a key step toward feasible, large-scale automated parking infrastructure.