公交车驾驶员驾驶规范行为安全报警分析数据

收集各个线路驾驶员在驾驶过程中的驾驶规范行为安全报警数据，并对这些驾驶规范行为进行了分类分级，统计每个驾驶员的驾驶规范报警指数，根据这一指数，将驾驶员标记为一般提醒、中度警告、严重警告三个层次，以实现对驾驶员的精准管理，有效提升驾驶员的驾驶规范意识，确保线路的安全运行，并提升整体运营效率。1.数据采集：通过红外摄像头实时的对驾驶员的头部、身体、动作进行采集，将视频送给主动安全设备。为了提高图像的处理速度，我们采用的是红外黑白视频。2.数据处理：主动安全设备接受到视频后，采用AI算法，对司机人脸、嘴巴、耳朵、眼睛、动作进行全方位的判断，对驾驶规范安全报警行为进行捕捉，生成数据集合，如：司机id、线路id、时间、主动安全报警类别、风险等数据。3.算法加工：使用COUNTIFS函数分类汇总出该司机的低风险累计报警次数、中风险累计报警次数、高风险累计报警次数，将处理后的数据通过加权平均法：Y=a1X1+a2X2+a3X3，权重系数a1、a2、a3分别是0.1、0.3、0.6，X1、X2、X3分别是低风险累计报警次数、中风险累计报警次数、高风险累计报警次数，计算出得分Y。通过分数，对用户进行分类分级，得分≤3，记为“一般提醒”，15≥得分＞3，记为“中度警告”，得分＞15，记为“严重警告”。通过标签，有效提升驾驶员的驾驶规范意识，确保线路的安全运行，并提升整体运营效率。

This dataset collects safety alert data for standardized driving behaviors from route drivers during their driving sessions, classifies and grades these driving behaviors against compliance standards, and calculates the standardized driving alert index for each driver. Based on this index, drivers are categorized into three levels: "General Reminder", "Moderate Warning", and "Severe Warning", to achieve precise driver management, effectively enhance drivers' standardized driving awareness, ensure safe operation of routes, and improve overall operational efficiency.

1. Data Collection: Real-time collection of the driver's head, body and movements is conducted via infrared cameras, with the captured video transmitted to active safety equipment. To accelerate image processing speed, infrared black-and-white video is adopted.

2. Data Processing: Upon receiving the video, the active safety equipment employs AI algorithms to comprehensively judge the driver's face, mouth, ears, eyes and movements, capture safety alert-triggering non-standard driving behaviors, and generate datasets including driver ID, route ID, timestamp, active safety alert category, risk level and other relevant data.

3. Algorithm Processing: The COUNTIFS function is used to summarize the cumulative number of low-risk, moderate-risk and high-risk alerts for each driver. The processed data is then calculated using the weighted average formula: Y = a1X1 + a2X2 + a3X3, where the weight coefficients a1, a2, a3 are 0.1, 0.3 and 0.6 respectively, and X1, X2, X3 represent the cumulative number of low-risk, moderate-risk and high-risk alerts respectively, to obtain the score Y. Drivers are classified and graded based on the score Y: those with a score ≤ 3 are marked as "General Reminder", those with 3 < score ≤ 15 as "Moderate Warning", and those with a score > 15 as "Severe Warning". This labeling mechanism effectively enhances drivers' standardized driving awareness, ensures safe operation of routes, and improves overall operational efficiency.

搜集汇总

数据集介绍

特点

该数据集包含公交车驾驶员驾驶规范行为安全报警数据，通过AI算法采集处理，每日更新542条数据，用于对驾驶员进行分类分级管理，提升驾驶规范意识和运营效率。