An Autonomous Parking Space Planning System Based on Pattern Searching Algorithm

Xinxin Huang, Yingguo Gao, Xiaohui Duan
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引用次数: 2

Abstract

In the field of static traffic, parking space planning and moving line planning are currently carried out manually over a period of more than one week, which is inefficient and cannot be optimized automatically. Therefore, this paper proposes and implements an autonomous parking space planning system based on pattern searching algorithm, which is divided into four modules: image preprocessing module, parking area segmentation module, parking space planning module, and image post-processing module. We use the system proposed in this paper to test the simulated parking lots of the same area. The result is that the parking space plot ratio can reach 48.68%. We also optimize an existing actual parking lot. The number of parking spaces in the optimized parking lot has increased by 20% compared with the original parking lot.
基于模式搜索算法的自主车位规划系统
在静态交通领域,目前的停车空间规划和移动线路规划都是人工进行的,周期超过一周,效率低下,无法自动优化。为此,本文提出并实现了一个基于模式搜索算法的自主车位规划系统,该系统分为四个模块:图像预处理模块、车位分割模块、车位规划模块和图像后处理模块。我们利用本文提出的系统对同一区域的模拟停车场进行了测试。其结果是,停车场容积率可达48.68%。我们还优化了一个现有的实际停车场。优化后的停车场停车位数量比原停车场增加了20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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