该数据描述了在联邦公路管理局（FHWA）特纳·法尔班公路研究中心（TFHRC）的移动实验室（LL）进行的59次数据采集过程中，高速公路跟车行为（如速度、加速度和相对位置）的实例。数据通过位于弗吉尼亚北部高速公路的仪器化研究车辆（IRV）采集，旨在更好地理解施工区驾驶员行为。美国交通部沃尔普国家交通运输系统中心（沃尔普中心）从原始数据集中识别、分离并分类了单独的跟车实例（分类参数包括道路类型、交通拥堵程度和限速），随后对数据集进行了处理、精炼和清洗。本表包含沃尔普中心工作人员记录的跟车实例。另请参见运行记录表（https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5）和雷达数据表（https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj）。

The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset. This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).