振動と操舵イベントを用いた走行データの自動同期
Automated Synchronization of Driving Data Using Vibration and Steering Events
加速度・テレメトリ・音声・複数カメラのオプティカルフローの相互相関により、車両センサのデータストリームを平均13ミリ秒の誤差で自動同期する手法を提案した。
著者: Lex Fridman, Daniel E Brown, William Angell, Irman Abdić, Bryan Reimer, Hae Young Noh
分類: cs.RO, cs.DC
原文アブストラクト
We propose a method for automated synchronization of vehicle sensors useful for the study of multi-modal driver behavior and for the design of advanced driver assistance systems. Multi-sensor decision fusion relies on synchronized data streams in (1) the offline supervised learning context and (2) the online prediction context. In practice, such data streams are often out of sync due to the absence of a real-time clock, use of multiple recording devices, or improper thread scheduling and data buffer management. Cross-correlation of accelerometer, telemetry, audio, and dense optical flow from three video sensors is used to achieve an average synchronization error of 13 milliseconds. The insight underlying the effectiveness of the proposed approach is that the described sensors capture overlapping aspects of vehicle vibrations and vehicle steering allowing the cross-correlation function to serve as a way to compute the delay shift in each sensor. Furthermore, we show the decrease in synchronization error as a function of the duration of the data stream.
