首页|融合数据支持与具身循证技术的街道步行安全感知研究——以上海市生活性街道为例

融合数据支持与具身循证技术的街道步行安全感知研究——以上海市生活性街道为例

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  • NETL
  • NSTL
  • 万方数据
行人交通安全是构建宜步行社区街道环境的基本要求,提高步行者在街道环境中行走的感知安全已经成为提升城市公共空间品质的关键措施.研究选取上海市29个典型街道采样点,综合运用街景数据、机器学习算法等新近涌现的分析技术,对步行者的交通安全感知展开定量化测度研究.结果表明:人行道宽度、道路机动化特征、近人尺度的界面要素和景观要素等对步行者的交通安全感知具有显著影响.研究结论可用于分析步行安全影响机制、构建步行安全评价体系和提供导控建议,为优化社区街道步行环境提供科学依据.
Research on Street Pedestrian Safety Perception Merging Data Support and Embodied Evidence-based Technology—Taking the Life Street of Shanghai Municipality as an Example
Pedestrian traffic safety is the basic requirement for constructing walkable community street environment,and improving the perceived safety of pedestrian who walks in street environment has become the key measure for improving urban public safety quality.Twenty-nine typical street sampling points in Shanghai Municipality are selected in this research,recent emerging analytical techniques are comprehensively utilized,including street view data and machine learning algorithms,so as to develop quantitative measurement research on the traffic safety perception of pedestrian.It is shown by the results:the sidewalk width,road motorization characteristics,the interface element and landscape elements of near-human scale have remarkable influence on the traffic safety perception of pedestrian.The conclusion of research can be used for analyzing the influence mechanism of walking safety,constructing walking safety evaluation system and providing guiding and control suggestions,so as to provide scientific basis for optimizing the walking environment of community streets.

pedestrian safety perceptionstreet public spacevirtual realitystreet view imagemachine learning algorithms

李琳、叶宇、陈泳

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同济大学建筑与城市规划学院

同济大学建筑与城市规划学院、同济大学生态化城市设计国际合作联合实验室

同济大学建筑与城市规划学院、高密度人居环境生态与节能教育部重点实验室

步行者安全感知 街道公共空间 虚拟现实 街景图像 机器学习算法

国家自然科学基金国家自然科学基金国际(地区)合作与交流项目国家自然科学基金广州市城市规划勘测设计研究院科研项目

5217802372361137008520783432022科研院136

2024

住宅科技
住房和城乡建设部住宅产业化促进中心,上海市房地产科学研究院

住宅科技

影响因子：0.402
ISSN：1002-0454
年,卷(期)：2024.44(4)
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