Employing Sensors and Services Fusion to Detect and Assess Driving Events

Seyed Vahid Hosseinioun, Hussein Al Osman, Abdulmotaleb El Saddik
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引用次数: 13

Abstract

With the remarkable increase in use of sensors in our daily lives, various methods have been devised to detect events in a driving environment using smart-phones as they provide two main advantages: they eliminate the need to have dedicated hardware in vehicles and they are widely accessible. Since rewarding safe driving is an important issue for insurance companies, some companies are implementing Usage-Based Insurance (UBI) as opposed to traditional History-Based plans. The collection of driving events, such as acceleration and turning, is a prerequisite requirement for the adoption of such plans. Mobile phone sensors are capable of detecting whether a car is accelerating or braking, while through service fusion we can detect other events like speeding or instances of severe weather. We propose a new and robust hybrid classification algorithm that detects acceleration-based events with an F1-score of 0.9304 and turn events with an F1-score of 0.9038. We further propose a method for measuring the driving performance index using the detected events.
利用传感器和服务融合检测和评估驾驶事件
随着传感器在我们日常生活中的使用显著增加,人们设计了各种方法来使用智能手机检测驾驶环境中的事件,因为它们有两个主要优势:它们消除了对车辆专用硬件的需求,而且它们很容易获得。由于奖励安全驾驶是保险公司的重要问题,一些公司正在实施基于使用情况的保险(UBI),而不是传统的基于历史的计划。收集驾驶事件,如加速和转弯,是采用这种计划的先决条件。手机传感器能够检测汽车是否在加速或刹车,而通过服务融合,我们可以检测超速或恶劣天气等其他事件。我们提出了一种新的鲁棒混合分类算法,该算法可以检测f1得分为0.9304的基于加速的事件和f1得分为0.9038的转弯事件。我们进一步提出了一种利用检测到的事件来测量驾驶性能指标的方法。
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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