预测印度的道路交通事故:一种包含COVID-19影响的SARIMAX方法
Sanjay Kumar Singh1, Vijay Lakshmi Singh2
1Indian Institute of Management, Lucknow, India.
International journal of injury control and safety promotion
|August 1, 2025
概括
印度的道路交通事故 (RTA) 越来越令人担忧,死亡人数从2012年到2022年增加了23%. 如果没有干预,预测每年会发生超过44万起交通事故,这凸显了加强道路安全措施的必要性.
科学领域:
- 公共卫生 公共卫生
- 运输安全运输安全
- 数据科学数据科学数据科学
背景情况:
- 道路交通事故 (RTA) 在印度是一个重大的公共卫生挑战,不成比例地导致全球死亡.
- 印度在2012年至2022年间,RTA死亡人数上升了23%,与全球的下降形成鲜明对比.
研究的目的:
- 使用先进的统计建模,预测印度未来的RTA趋势.
- 将COVID-19大流行的影响作为RTA预测中的外部因素纳入其中.
- 为开发有效的道路安全干预提供数据驱动的见解.
主要方法:
- 使用了带有外源变量的季节性自回归集成移动平均线 (SARIMAX) 模型.
- 从2010年到2022年分析了每月的RTA数据.
- 综合COVID-19大流行数据作为外源变量来解释移动性变化.
主要成果:
- 萨里马克斯模型提供了比传统模型更可靠的预测,因为它包括了流行病等外部冲击.
- 如果没有有针对性的干预措施,印度每年的道路交通事故案件预计将超过44万.
- 该研究强调,在后疫情时代,全面的道路安全战略的必要性至关重要.
结论:
- 紧急实施全面的道路安全措施对于减轻印度未来的RTA趋势至关重要.
- 建议包括加强政策,改善基础设施,加强执法和采用人工智能驱动技术.
- 积极主动和基于数据的策略对于提高道路安全和减少流行病后的死亡人数至关重要.
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