根据严重程度对道路交通事故进行空间自相关分析,使用莫兰的I空间统计:亚的斯亚贝巴和柏林城市的比较研究
Wondwossen Taddesse Gedamu1, Uwe Plank-Wiedenbeck2, Bikila Teklu Wodajo3
1Chair of Transport System Planning, Faculty of Civil Engineering, Bauhaus University Weimar, Schwanseestr. 13, 99423 Weimar, Germany; School of Civil & Environmental Engineering, Addis Ababa Institute of Technology, AAiT, Addis Ababa University, Addis Ababa, Ethiopia.
Accident; analysis and prevention
|March 15, 2024
概括
这项研究分析了亚的斯亚贝巴和柏林的交通事故严重程度模式,揭示了显著的空间聚类. 确定了事故严重性热点,特别是在两座城市的郊区,突出了针对性安全干预的领域.
科学领域:
- 道路交通安全问题 道路安全问题
- 空间分析是一种空间分析.
- 城市规划是城市规划.
背景情况:
- 道路安全研究越来越多地使用空间方法来识别热点和分析模式.
- 之前的研究往往忽视了碰撞严重程度及其空间自相关性,限制了对碰撞模式的洞察力.
- 了解空间撞车严重性模式对于有效的道路安全干预至关重要.
研究的目的:
- 调查亚的斯亚贝巴和柏林道路事故严重性的空间自相关性.
- 为了比较低收入和高收入国家的首都之间的崩严重性模式.
- 使用空间统计数据识别高风险和低风险撞车严重程度集群.
主要方法:
- 利用了来自亚的斯亚贝巴和柏林的三年撞车数据.
- 使用的近邻平均距离 (ANND) 来评估按严重程度对撞车事件的空间聚类.
- 应用了全球莫兰的I用于整体空间自相关性和局部莫兰的I用于集群识别 (高高和低低严重程度).
主要成果:
- 在这两座城市 (除了柏林的致命事故外) 都发现了严重程度的交通事故的显著空间聚类.
- 亚的斯亚贝巴显示出比柏林更强大和更具有统计意义的空间自相关性 (全球莫兰的I).
- 当地Moran's I发现了不同的模式:亚的斯亚贝巴显示中心的低低集群和郊区的高高集群;柏林的集群更混合,边缘的高高区域.
结论:
- 对碰撞严重性的空间分析揭示了由社会经济,行为和道路因素影响的独特模式.
- 在亚的斯亚贝巴和柏林的城市郊区连续发现高高严重程度的集群表明存在共同的潜在问题.
- 建议在不同地点进行进一步的研究,以验证和概括这些发现,以改善道路安全策略.
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