A Car-Following Data Collecting Method Based on Binocular Stereo Vision

Abstract

This study proposes the design, implementation, and application of a new car-following data collecting method based on binocular stereo vision system. The car-following data consist of car-following distance, velocity, relative velocity and driving trajectory of a following vehicle. Specifically, triangulation principle is used to measure car-following distance. Robust locally weighted regression smoothing method is applied to automatically filter out the outliers caused by disturbance in real-world driving condition. Real-world experiments indicate that binocular cameras with 25mm focal length have advantages in traffic conditions with long car-following distance and high driving speed, and that binocular cameras with12mm focal length are suitable to measure on urban roads, where car-following distance is short and more driving conditions are needed to be observed. In 0-60m distance measuring range, it is verified that the mean absolute percentage error (MAPE) of binocular cameras with 25mm focal length is 3.2% and the MAPE of binocular cameras with 12mm focal length is 6.3%. The data collecting system helps to advance car following models due to its high accuracy and effective cost.

Keywords

• Binocular stereo vision
• car-following
• data collecting method
• robust locally weighted regression