Driver Behavior Image Dataset

High-resolution images in the dataset were collected across different lighting conditions and vehicle types, representing diverse driving situations. The images, presented in raw, unannotated form, allow for flexible pre-processing by machine learning practitioners. The dataset is organized into five behavioral classes:

Safe Driving: Images show drivers fully attentive to the road, either with both hands on the steering wheel or one hand on the wheel and the other on the gear stick, exemplifying distraction-free driving.

Turning: Photos capture drivers as they turn, moving their heads or bodies to indicate a change in direction. This behavior reflects the driver’s engagement in typical actions like steering.

Texting on Phone: Images of drivers using mobile phones to type messages or interact with screens. This class addresses one of the primary causes of distracted driving.

Talking on Phone: Drivers are depicted holding their phones to their ears or speaking on the phone while driving. This class helps to identify the distractions associated with phone conversations.

Others: Includes images of behaviors that compromise safe driving, such as drinking water, conversing with passengers in the back seat, or showing signs of drowsiness.

With its wide-ranging real-life conditions, this dataset offers a rich resource for developing systems to detect and classify risky driving behaviors, supporting efforts to improve road safety.

该数据集中收录了在不同光照条件和车辆类型下采集的高分辨率图像，全面反映了多样化的驾驶场景。图像以原始、未标注的形式呈现，便于机器学习从业者进行灵活的预处理。数据集按照五种行为类别进行组织：

安全驾驶：图像展示了驾驶员对道路高度专注的情形，无论是双手握方向盘还是一手握方向盘一手握档杆，均体现了无分心的驾驶方式。

转向：照片捕捉了驾驶员转向时的瞬间，他们通过头部或身体的移动来指示方向的变化，这一行为反映了驾驶员在转向等典型动作中的参与。

手机短信：展示了驾驶员使用手机发送短信或与屏幕交互的图像。此类别旨在解决分心驾驶的主要原因之一。

手机通话：描绘了驾驶员在驾驶时将手机贴耳或通话的情形。此类别有助于识别与电话交谈相关的分心因素。

其他：包括那些危害安全驾驶的行为的图像，如喝水、与后排乘客交谈或表现出困倦迹象等。

凭借其广泛的现实生活条件，该数据集为开发检测和分类风险驾驶行为系统提供了丰富的资源，支持提升道路安全的工作。