Vehicle speed estimation using video data and acceleration information of a drive recorder

Kazuki Osamura, A. Yumoto, Osafumi Nakayama
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引用次数: 12

Abstract

A drive recorder (DR) is installed in many vehicles to record information about car accidents. Recently, images and vehicle behavior data captured with DR is being used with increasing frequency to analyze dangerous driving behaviors and visualize the conditions in which this behavior occurs. Essential to this risk analysis is identifying the dangerous situation and obtaining information on the circumstances at the time, which must include precise vehicle speed information for analyzing detailed dangerous car motions such as rapid deceleration. Today, instead of high-precision speed pulse generator DR, many simple DR that record vehicle speeds captured by GPS are used, because they are easy to use without being connected to the car electronics. While these GPS-type DR are accurate enough for recording purposes, they are insufficient for analysis purposes, which hamper using DR for analysis in many cases. This study proposes a method that estimates precise vehicle speeds using images and acceleration data captured by simple DR. Most vehicle speed estimation methods calculate the velocity by estimating the vehicle motion that is represented by the motion flow of feature points in images. Maintaining the estimation accuracy requires obtaining these flow data from entire images. However, images captured by DR include few feature points of road surfaces that occupy the lower half of images and provide skewed feature-point flow position distributions, leading to a decrease in the accuracy of the speed estimation. The proposed method uses acceleration information, which is unique to DR, to calculate the area in which the vehicle can possibly move around, and restrict the image flow analysis to within this area. This can overcome skewed flow distributions to estimate the vehicle speed accurately. It was verified in actual running experiments that the proposed method significantly improves the accuracy of vehicle speed estimation compared with previous methods.
利用行车记录仪的视频数据和加速度信息进行车速估计
许多车辆都安装了行车记录仪(DR)来记录交通事故的信息。最近,DR捕获的图像和车辆行为数据被越来越多地用于分析危险驾驶行为,并将这种行为发生的条件可视化。这种风险分析的关键是识别危险情况并获取当时情况的信息,其中必须包括精确的车速信息,以便分析详细的危险汽车运动,如快速减速。如今,人们不再使用高精度的速度脉冲发生器DR,而是使用许多由GPS捕获的记录车速的简单DR,因为它们无需连接到汽车电子设备即可轻松使用。虽然这些gps类型的DR对于记录目的来说足够准确,但对于分析目的来说是不够的,这阻碍了在许多情况下使用DR进行分析。本研究提出了一种利用简单dr捕获的图像和加速度数据来精确估计车速的方法。大多数车速估计方法是通过估计图像中特征点的运动流来表示的车辆运动来计算速度。保持估计的准确性需要从整个图像中获取这些流量数据。然而,DR捕获的图像中包含的路面特征点很少,占据图像的下半部分,并且特征点流位置分布倾斜,导致速度估计的准确性降低。该方法利用DR特有的加速度信息来计算车辆可能移动的区域,并将图像流分析限制在该区域内。这可以克服扭曲的流动分布,以准确地估计车辆的速度。实际运行实验证明,与以往的方法相比,该方法显著提高了车速估计的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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