首页> 外文期刊>Computers & Graphics >AUTOSIGN: A multi-criteria optimization approach to computer aided design of signage layouts in complex buildings
【24h】

AUTOSIGN: A multi-criteria optimization approach to computer aided design of signage layouts in complex buildings

机译:AutoSign:复杂建筑中标牌布局的计算机辅助设计的多标准优化方法

获取原文
获取原文并翻译 | 示例
           

摘要

To improve the efficiency and effectiveness of designing signage systems in buildings, we present AUTOSIGN - a design tool that supports user-in-the-loop and multi-criteria optimization of signage layouts in complex buildings. We formulate signage placement as a multi-objective optimization problem with competing objectives (i.e., total distance travelled, total number of turns, the centrality of decision points, path overlap, and number of decision taken) and constraints (i.e., user-specified sign location and orientation threshold), which we solve using a two-step approach. Firstly, an evolutionary method is used to optimize all combination of navigation paths based on cognitively inspired objective functions weighted by the designers. Secondly, a particle swarm optimization is used to optimize individual sign placement to maximize the exposure of wayfinding information (i.e., signage coverage area) from the optimized navigation graph generated. To evaluate the effectiveness of the tool, we apply it to the design of signage systems across two virtual 3D buildings. We generate signage layouts for both buildings and optimize each of them for user-defined criteria. Both optimized and non-optimized layouts are evaluated using an agent-based simulation. The simulation results demonstrate that even with fewer signs, the signage coverage area for the optimized layout increased by 18% on average. Finally, an expert-based VR walk-through and a System Usability Study is performed to further evaluate AUTOSIGN. (C) 2020 Elsevier Ltd. All rights reserved.
机译:为了提高建筑物中设计标牌系统的效率和有效性,我们呈现AutoSign - 一种支持复杂建筑物中的循环循环和多标准优化的设计工具。我们将标志展示位置作为竞争目标的多目标优化问题(即,行驶总距离,匝数总数,决策点的中心,路径重叠和决定的次数)和约束(即用户指定的标志)位置和方向阈值),我们使用两步方法解决。首先,使用进化方法基于设计人员加权的认知灵感的客观函数来优化导航路径的所有组合。其次,粒子群优化用于优化单个签名放置,以最大限度地从所生成的优化导航图中最大限度地曝光WayFinding信息(即标牌覆盖范围)。为了评估该工具的有效性,我们将其应用于两个虚拟3D建筑物的标牌系统设计。我们为两个建筑物生成标牌布局,并针对用户定义的标准优化它们中的每一个。使用基于代理的仿真来评估优化和非优化布局。仿真结果表明,即使具有较少的标志,优化布局的标牌覆盖范围平均增加了18%。最后,执行基于专家的VR步行和系统可用性研究以进一步评估AutoSign。 (c)2020 elestvier有限公司保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号