Modelling and predicting patterns of pedestrian movement: using robotics and machine learning to improve the design of urban space.

建模和预测行人运动模式：利用机器人技术和机器学习来改进城市空间的设计。

• 批准号: DP1092679
• 负责人: Prof Michael Ostwald
• 金额: $ 33.8万
• 依托单位: The University of Newcastle
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2010
• 资助国家: 澳大利亚
• 起止时间: 2010-02-01 至 2014-01-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP1092679
• 关键词: Modelling; predicting; patterns; pedestrian; movement

In a geographic region that is experiencing increasing urban density, the problems of the pedestrian are rarely considered from a design perspective. One reason for this is that there are few useful tools available for analysing the behaviour of pedestrians in existing urban spaces, and none to assist designers to optimise such spaces. As a result of this, there is an urgent need for the development of design tools to enable a higher level of understanding of pedestrians in public space. This project is a world-first combining urban design theory and machine-learning for creating more socially and culturally responsive environments.

在一个城市密度不断增加的地理区域，很少从设计的角度考虑行人的问题。其中一个原因是，几乎没有可用的有用工具来分析现有城市空间中行人的行为，也没有任何工具可以帮助设计师优化此类空间。因此，迫切需要开发设计工具，使人们能够更高水平地了解公共空间中的行人。这个项目是世界上第一个将城市设计理论和机器学习相结合的项目，旨在创造更具社会和文化响应性的环境。