Motion state acquisition and error analysis for intelligent vehicle power management strategies

Intelligent Vehicles acquire driving environment information and it self´s attitude using several kinds of sensors. Then through data fusion, it implements driving assistant system and even automatic/autonomous driving. This article focuses on vehicle motion state acquisition and error analysis for driving patterns recognition, which is needed by intelligent power management strategies. With low cost MEMS sensors and low accuracy data processing model, vehicles´ velocity, acceleration and gyroscope data can be acquired and analyzed, which can be used in driving patterns recognition. Because of the high interference of dynamic driving environment and low accuracy of MEMS sensors, common errors appear in sensor data acquisition and methods to eliminate the deviations are also discussed, with experiments and data analysis presented.