构建个性化驾驶行为数据集，揭示每位司机的独特驾驶习惯。
PDB: Not All Drivers Are the Same -- A Personalized Dataset for Understanding Driving Behavior
- 采集12名司机在固定路线、车辆和光照下的多模态数据
- 包含约27万帧激光雷达、160万张图像和6.6TB原始数据
- 适合研究驾驶员识别、人因分析与个性化智能交通系统
驾驶行为具有明显的个体差异，受个人习惯、决策风格和生理状态影响。然而，现有数据集普遍将所有司机视为同质，忽视了个体差异。为此，我们提出个人化驾驶行为（PDB）数据集，一个在自然驾驶条件下捕捉个体特征的多模态数据集。与传统数据集不同，PDB通过保持路线、车辆和光照条件一致，最小化外部干扰。数据包含128线激光雷达、前向摄像头视频、GNSS、9轴惯性测量单元、CAN总线数据（油门、刹车、转向角），以及面部视频和心率等司机特有信号。数据集涵盖12名参与者，约27万帧激光雷达数据、160万张图像和6.6TB原始传感器数据。处理后的轨迹数据包含1,669个片段，每个片段时长10秒，采样间隔0.2秒。该数据集为驾驶员行为分析、身份识别及个性化出行应用提供了独特资源，助力以人为本的智能交通系统发展。
原文摘要 · Abstract (English)
Driving behavior is inherently personal, influenced by individual habits, decision-making styles, and physiological states. However, most existing datasets treat all drivers as homogeneous, overlooking driver-specific variability. To address this gap, we introduce the Personalized Driving Behavior (PDB) dataset, a multi-modal dataset designed to capture personalization in driving behavior under naturalistic driving conditions. Unlike conventional datasets, PDB minimizes external influences by maintaining consistent routes, vehicles, and lighting conditions across sessions. It includes sources from 128-line LiDAR, front-facing camera video, GNSS, 9-axis IMU, CAN bus data (throttle, brake, steering angle), and driver-specific signals such as facial video and heart rate. The dataset features 12 participants, approximately 270,000 LiDAR frames, 1.6 million images, and 6.6 TB of raw sensor data. The processed trajectory dataset consists of 1,669 segments, each spanning 10 seconds with a 0.2-second interval. By explicitly capturing drivers' behavior, PDB serves as a unique resource for human factor analysis, driver identification, and personalized mobility applications, contributing to the development of human-centric intelligent transportation systems.
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