A vehicle equipped with inertial sensing and auxiliary sensors travels on the road. By analyzing the components of physical quantities in X and Y vehicle’s coordinate system, driving events such as direction (e.g. turning right softly or sharply, turning left) and mechanical control actions (accelerating and slowing down). By providing this information to the intelligent agent controlling the vehicle, it is possible to determine whether the decisions made regarding vehicle movements are being carried out correctly and, if necessary, make command adjustments. In conjunction with the perception module it is possible, for example, that traveling in a lane of high irregularity in which its qualitative concept is low, the agent decides to reduce the speed, a decision that can be proven through the proprioception module.
Vehicular Box-Black System
- Driving behavior.
Thiago Rateke is a Computer Vision Researcher with experience mainly focusing on visual perception for autonomous navigation. Finished his PhD degree at Federal University of Santa Catarina (UFSC) in 2020 with focuses on visual perception for Autonomous Navigation. Using approaches like: Stereo Vision, Optical Flow and Convolutional Neural Networks.