An automated system for Accident Detection

Asad Ali, M. Eid
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引用次数: 26

Abstract

Major accidents on highways, freeways and local roads can lead to huge social and economic impacts. Minor accidents may be resolved by the passengers themselves and do not require escorting to hospitals whereas major accidents where airbags are deployed require immediate attention of authorities. Automatic Smart Accident Detection (ASAD) is an auto-detection unit system that immediately notifies an Emergency Contact through a text message when an instant change in acceleration, rotation and an impact force in an end of the vehicle is detected by the system, detailing the location and time of the accident. The idea is that as soon as an accident is detected by the system, the authorities should immediately be notified to prevent further car congestion as well as allow the passengers to be escorted to the hospital in a timely fashion. The system involves the use of fuzzy logic as a decision support built into the smartphone application that analyzes the incoming data from the sensors and makes a decision based on a set of rules. The simulated results show a 98.67% accuracy of the system with failures resulting from the “gray regions” of the variable values.
事故检测的自动化系统
在高速公路、高速公路和地方道路上发生的重大事故会造成巨大的社会和经济影响。小事故可以由乘客自己解决,不需要护送到医院,而安全气囊部署的重大事故需要当局立即关注。自动智能事故检测(ASAD)是一种自动检测单元系统,当系统检测到车辆尾部的加速度、旋转和冲击力的瞬间变化时,它会立即通过短信通知紧急联系人,并详细说明事故的位置和时间。这个想法是,一旦系统检测到事故,就应该立即通知当局,以防止进一步的车辆拥堵,并允许乘客及时被护送到医院。该系统使用模糊逻辑作为内置在智能手机应用程序中的决策支持,该应用程序分析来自传感器的传入数据,并根据一组规则做出决策。仿真结果表明,由于变量值的“灰色区域”导致的故障,系统的准确率为98.67%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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