大型卡车驾驶员在变道时的间隙接受度分析——基于图像的分析
Gap Acceptance During Lane Changes by Large-Truck Drivers-An Image-Based Analysis
AI总结：
本文通过图像分析研究了大型卡车驾驶员在高速公路变道场景中的后方间隙接受特性，揭示了变道方向对车辆速度的影响及安全阈值。
摘要：
本文提出了对大型卡车驾驶员在高速公路变道场景中后方间隙接受特性进行分析的方法。通过摄像头图像推断车辆间距离，利用车道跟踪摄像头估计的车道宽度作为参考。从大规模自然驾驶数据集中获取了600次变道事件。通过加权线性最小二乘法过滤图像基于的间隙分析动力学变量，以在变道时间 extrapolate 这些变量。此外，计算了碰撞时间到和所需减速度，并提供了潜在的安全阈值值。所得的距离和距离率分布显示出方向差异，即在左变道中，大型卡车通常比目标车道的其他车辆慢，而在右变道中则通常更快。视频观察证实，变道方向不同，变道的主要动机也不同，即向左（更快）车道变道是因为前方车辆较慢或右侧合并车辆，而右变道通常是变道后返回原车道。
英文摘要：
This paper presents an analysis of rearward gap acceptance characteristics of drivers of large trucks in highway lane change scenarios. The range between the vehicles was inferred from camera images using the estimated lane width obtained from the lane tracking camera as the reference. Six-hundred lane change events were acquired from a large-scale naturalistic driving data set. The kinematic variables from the image-based gap analysis were filtered by the weighted linear least squares in order to extrapolate them at the lane change time. In addition, the time-to-collision and required deceleration were computed, and potential safety threshold values are provided. The resulting range and range rate distributions showed directional discrepancies, i.e., in left lane changes, large trucks are often slower than other vehicles in the target lane, whereas they are usually faster in right lane changes. Video observations have confirmed that major motivations for changing lanes are different depending on the direction of move, i.e., moving to the left (faster) lane occurs due to a slower vehicle ahead or a merging vehicle on the right-hand side, whereas right lane changes are frequently made to return to the original lane after passing.
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。
