对宏观安全评估和贡献因素分析的系统方法,考虑交通事故和违规行为
Xuesong Wang1, Xueyu Zhang1, Yingying Pei1
1School of Transportation Engineering, Tongji University, Shanghai 201804, China; The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China.
Accident; analysis and prevention
|October 21, 2023
概括
在城市化过程中,了解交通安全至关重要. 这项研究联合模拟了车祸和违规行为,以确定热点,并确定了交通警察的号码和巡逻时间,作为减少事故的关键因素.
科学领域:
- 城市规划是城市规划.
- 运输工程 运输工程 运输工程
- 公共安全公共安全.
背景情况:
- 快速的城市化和增加的汽车化需要更好地了解交通安全.
- 交通事故和违法行为之间的关系是复杂的,限制了传统分析的可靠性.
- 确定宏观层面的贡献因素对于有效的政策建议至关重要.
研究的目的:
- 制定一个系统的方法,共同建模交通事故和违规行为.
- 识别崩和违规热点,并分析潜在的贡献因素.
- 为交通管理人员提供数据驱动的洞察力,以提高安全性.
主要方法:
- 收集了来自中国苏州115个城镇的社会经济,道路网络,公共设施,交通执法和土地使用数据.
- 采用了双变量负二项空间条件自回归模型 (BNB-CAR) 和安全改进潜力 (PSI) 方法.
- 使用可解释的机器学习框架来检查对已识别的问题领域的因素影响.
主要成果:
- 拟议的框架成功地确定了易发生事故和易发生违规的区域.
- 量化了关键因素的影响,特别是交通警察的数量及其每日巡逻时间.
- 证明,将警察数量和巡逻时间保持在特定门以下,可以同样有效地减少高碰撞和高违规地区.
结论:
- 联合建模方法有效地识别了问题交通区域的关键因素,特别是与执法相关的因素.
- 调查结果为交通管理人员提供了实施有针对性的改进的实际指南.
- 优化交通执法策略,如警察数量和巡逻时间,可以显著提高道路安全.
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