使用随机参数二元逻辑方法模拟行人-车辆撞车故障归因中的异质性
1Department of Civil Engineering, Istanbul Aydın University, Istanbul, Türkiye.
Accident; analysis and prevention
|March 14, 2026
概括
城市车祸中的司机或行人过错取决于位置和天气等因素. 针对性的安全干预措施在减少交通事故方面比统一的措施更有效.
科学领域:
- 交通安全研究 交通安全研究
- 城市流动研究 城市流动研究
- 事故分析 事故分析
背景情况:
- 行人与车辆的碰撞是一个主要的城市安全问题.
- 了解错误归因对于有效干预至关重要.
- 现有的研究往往缺乏对影响因素的细粒度分析.
研究的目的:
- 分析城市车祸中影响驾驶员与行人错误的因素.
- 识别特定的道路,车辆,环境,时间和行为影响.
- 为目标交通安全策略提供信息.
主要方法:
- 利用了7213起伊斯坦布尔车祸 (2022-2023) 的数据.
- 采用二进制逻辑模型作为基准.
- 开发了一个随机参数二元逻辑模型来捕捉异质性.
主要成果:
- 十字路口,交通标志,恶劣天气和多辆车增加了司机故障的可能性.
- 交通信号灯和公共交通工具的参与增加了行人错误的可能性.
- "十字路口"",交通标志"",交通灯"",恶劣天气"",公共交通"和"车辆数量"被确定为关键的随机参数.
结论:
- 在行人与车辆相撞事故中的故障归因是复杂的,并且取决于背景.
- 司机错误更有可能发生在十字路口,交通标志,恶劣天气和多车辆事故.
- 行人故障更有可能发生在交通信号灯和涉及公共交通的交通工具上,因此需要量身定制的安全措施.
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