一种模糊的集群方法来识别行人交通行为模式
Parisa Saeipour1, Parvin Sarbakhsh1, Saman Salemi2
1Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran.
Journal of research in health sciences
|February 5, 2024
概括
使用模糊集群识别了行人交通行为模式,揭示了不同的低风险和高风险群体. 年龄较小,教育程度较低,男性性别和公共交通使用与高风险行为有关.
科学领域:
- 交通安全研究 交通安全研究
- 行为科学 行为科学
- 城市规划 城市规划
背景情况:
- 识别行人交通行为模式可以提高管理效率和规划.
- 了解这些模式对于有针对性的干预和安全措施至关重要.
- 这项研究评估了行人行为模式和相关的风险因素.
研究的目的:
- 用模糊集群算法评估行人交通行为模式.
- 识别与高风险行人交通行为相关的因素.
- 为安全措施和行人培训计划提供信息.
主要方法:
- 在伊朗乌尔米亚市600名行人数据上使用模糊c-means (FCM) 聚类.
- 采用了行人行为问卷 (PBQ) 的5个领域.
- 应用多重物流回归来确定交通行为风险因素.
主要成果:
- 确定了两个不同的集群:低风险和高风险的行为.
- 大多数行人 (64.33%) 表现出较低风险的行为.
- 高风险行为与年龄较小 (≤33岁),教育程度较低 (≤6岁),男性性别,未婚状态和公共交通使用有显著的关联.
结论:
- 在乌尔米亚,模糊的c-means成功地确定了不同的低风险和高风险的行人行为模式.
- 调查结果为决策者提供了宝贵的见解,帮助他们制定有针对性的安全干预措施.
- 该研究强调了影响行人风险的人口和行为因素,有助于集中培训计划.
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