DriverSonar: Fine-Grained Dangerous Driving Detection Using Active Sonar
DriverSonar: Fine-Grained Dangerous Driving Detection Using Active Sonar
复制标题
DriverSonar：使用主动声纳进行细粒度危险驾驶检测
DOI：
--
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Minjie Cai
中科院分区：
文献类型：
--
作者：
Hongbo Jiang;Jingyang Hu;Daibo Liu;Jie Xiong;Minjie Cai
由于困倦和分心而导致的危险驾驶是造成交通事故的主要原因，造成人员伤亡和经济损失。目前迫切需要通过准确检测危险驾驶行为并产生实时警报来解决这一问题。由于观察到危险的驾驶行为会产生独特的声学特征，这些声学特征会响应声源的信号，我们在本文中提出了DriverSonar系统。该系统可以检测危险驾驶行为，并使用现成的智能手机产生实时警报。与最先进的技术相比，DriverSonar系统不需要专用传感器，只需使用智能手机内置的扬声器和麦克风。具体来说，DriverSonar能够识别头部/手部动作，如点头、打哈欠和突然调整方向盘。我们通过大量的实验来设计、实施和评估DriverSonar。我们对30名志愿者进行了为期12个月的模拟器和真实驾驶实验（irb批准）。实验结果表明，该系统检测困倦和分心相关危险驾驶行为的准确率高达93.2%，误检率仅为3.6%。
Dangerous driving due to drowsiness and distraction is the main cause of traffic accidents, resulting in casualties and economic loss. There is an urgent need to address this problem by accurately detecting dangerous driving behaviors and generating real-time alerts. Inspired by the observation that dangerous driving actions induce unique acoustic features that respond to the signal of an acoustic source, we present the DriverSonar system in this paper. The proposed system detects dangerous driving actions and generates real-time alarms using off-the-shelf smartphones. Compared with the state-of-the-arts, the DriverSonar system does not require dedicated sensors but just uses the built-in speaker and microphone in a smartphone. Specifically, DriverSonar is able to recognize head/hand motions such as nodding, yawning, and abrupt adjustment of the steering wheel. We design, implement and evaluate DriverSonar with extensive experiments. We conduct both simulator-based and and real driving-based experiments (IRB-approved) with 30 volunteers for a period over 12 months. Experiment results show that the proposed system can detect drowsy and distraction related dangerous driving actions at an precision up to 93.2% and a low false acceptance rate of 3.6%...