在DriveSafe项目现场测试中用于确定车头时距的激光雷达数据分析

Ilker Altay, B. A. Güvenç, L. Guvenç
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引用次数: 18

摘要

DriveSafe项目由土耳其的大学研究中心和汽车原始设备制造商组成的联盟开展,旨在减少驾驶员行为造成的事故。研究人员从108名驾驶装有仪表的DriveSafe车辆的司机身上收集了大量的驾驶数据,这些司机在伊斯坦布尔的城市和高速公路上行驶了25公里。DriveSafe车辆中使用的传感器之一是前视激光雷达。来自激光雷达的数据用于确定和记录不同驾驶员的车头时特征。本文主要对来自DriveSafe车辆的激光雷达数据进行分析。首先使用了一种简单的算法,该算法只关注沿直线前进的方向。基于这种简单的方法,给出了一个示例驱动程序的车头时距。本文随后提出了一种基于文献的更精确的检测和跟踪算法。首先提出了基于网格和基于点距离的方法。然后,提出了一种基于卡尔曼滤波的检测与跟踪算法。用实验数据对结果进行了验证。
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Lidar Data Analysis for Time to Headway Determination in the DriveSafe Project Field Tests
The DriveSafe project was carried out by a consortium of university research centers and automotive OEMs in Turkey to reduce accidents caused by driver behavior. A huge amount of driving data was collected from 108 drivers who drove the instrumented DriveSafe vehicle in the same route of 25 km of urban and highway traffic in Istanbul. One of the sensors used in the DriveSafe vehicle was a forward-looking LIDAR. The data from the LIDAR is used here to determine and record the headway time characteristics of different drivers. This paper concentrates on the analysis of LIDAR data from the DriveSafe vehicle. A simple algorithm that only looks at the forward direction along a straight line is used first. Headway times based on this simple approach are presented for an example driver. A more accurate detection and tracking algorithm taken from the literature are presented later in the paper. Grid-based and point distance-based methods are presented first. Then, a detection and tracking algorithm based on the Kalman filter is presented. The results are demonstrated using experimental data.
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