PDB：并非所有驾驶员都相同——一个用于理解驾驶行为的个性化数据集
PDB: Not All Drivers Are the Same -- A Personalized Dataset for Understanding Driving Behavior
AI总结：
本文提出个性化驾驶行为数据集PDB，通过多模态传感器采集12名驾驶员在一致路线和车辆条件下的自然驾驶数据，支持驾驶员识别、人因分析和个性化出行应用。
摘要：
驾驶行为本质上是个人化的，受到个人习惯、决策风格和生理状态的影响。然而，现有的大多数数据集将所有驾驶员视为同质的，忽视了驾驶员特定的差异性。为了弥补这一不足，我们引入了个性化驾驶行为（PDB）数据集，这是一个多模态数据集，旨在自然驾驶条件下捕捉驾驶行为的个性化特征。与常规数据集不同，PDB 通过在各个会话中保持一致的路线、车辆和光照条件，最大限度地减少了外部影响。该数据集包含来自128线激光雷达、前视摄像头视频、GNSS、9轴IMU、CAN总线数据（油门、制动、转向角）以及驾驶员特定信号（如面部视频和心率）的数据源。该数据集包含12名参与者、约270,000帧激光雷达数据、160万张图像和6.6 TB的原始传感器数据。处理后的轨迹数据集由1,669个片段组成，每个片段持续10秒，间隔为0.2秒。通过明确捕捉驾驶员的行为，PDB 作为人因分析、驾驶员识别和个性化出行应用的独特资源，有助于推动以人为中心的智能交通系统的发展。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
