无需移动车辆即可高效停取车，提升停车场空间利用率。
High-Density Automated Valet Parking with Relocation-Free Sequential Operations
- 设计无车位挪动的连续停取车序列，结合高效布局
- 实测在高密度场景下显著提升空间利用率
- 适合智能停车系统与自动驾驶泊车场景
本文提出DROP框架，实现高密度自动代客泊车中的无挪车连续操作。该方法通过联合设计空间高效的车位布局与无挪车的停取车序列，兼顾可达性与连续操作约束。为生成此类序列，将无挪车约束形式化为布尔变量的逻辑条件，并采用递归搜索策略推导逻辑条件并枚举满足顺序约束的无挪车序列。大量仿真结果表明，该框架在保持无挪车条件下显著提升空间利用率。同时，针对具有预定操作顺序的应用问题进行了可行性验证。所有实验结果可于 https://drop-park.github.io 公开获取。
原文摘要 · Abstract (English)
In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges in high-density parking & vehicle retrieval without relocations. Each challenge is handled by jointly providing area-efficient layouts and relocation-free parking & exit sequences, considering accessibility with relocation-free sequential operations. To generate such sequences, relocation-free constraints are formulated as explicit logical conditions expressed in boolean variables. Recursive search strategies are employed to derive the logical conditions and enumerate relocation-free sequences under sequential constraints. We demonstrate the effectiveness of our framework through extensive simulations, showing its potential to significantly improve area utilization with relocation-free constraints. We also examine its viability on an application problem with prescribed operational order. The results from all experiments are available at: https://drop-park.github.io.
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