Lexfridman.com Website Review

developing de*p learning approaches for perception, planning, and human-robot interaction in the context of real-world shared autonomy A course on the practice of de*p learning explored through the theme of building a self-driving car. Course page is We propose a set of shared autonomy principles for designing and building autonomous vehicle systems in a human-centered way. Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical Decisions life-critical decisions. We propose an arguing machines framework that improves the accuracy of the overall system given human driving data collection and large-scale de*p learning based parsing of that data, how human-AI interaction in driving can be safe and from the tragic Uber crash in Arizona. Open source code and arXiv paper will be out soon. I hope it can help, in however small a way, make the roads safer for people inside and outside both manually-controlled and autonomous vehicles. synchronized video streams in a Tesla while transfering control to Autopilot and taking control back. and audio streams captured during the driver's interaction with an in-vehicle voice-based navigation system. data that uses vibration and steering events to sync driving data within 13ms precision. Authors: Fridman, Brown, Glazer, Angell, Dodd, Jenik, et al. Journal: IEEE Access Reinforcement Learning 2018 Under Review PDF available on request 2018 Under Review PDF available on request Authors: Kindelsberger, Fridman, Glazer, Seppelt, Reimer 2018 Under Review PDF available on request Authors: Brown, Fridman, Kindelsberger, Glazer, Reimer 2018 Under Review PDF available on request Authors: Fridman, Reimer, Mehler, Freeman Pedestrians Toward Safer Automated Vehicles 2017 PDF available on request Authors: Toyoda, Fridman, Jenik, Mehler, Reimer Conference: FAST-Zero Authors: Fridman, Lee, Reimer, Victor Journal: IET Computer Vision Authors: Fridman, Brown, Angell, Abdic, Reimer, Noh Journal: Pattern Recognition Letters