uiux
Regular
https://www.theregister.com/2017/11/01/toyota_picks_renesas_soc_to_power_its_first_selfdriving_cars/
Toyota picks Renesas SoC to power its first self-driving cars
"Toyota has selected the embedded systems maker Renesas to supply the ARM-powered systems-on-a-chip to power autonomous vehicles scheduled for commercial launch in the year 2020."
https://global.toyota/en/detail/10171645
Toyota Will Establish New Artificial IntelligenceResearch and Development Company
"Directed by Dr. Gill Pratt, Toyota's Executive Technical Advisor and the Chief Executive Officer of the new enterprise, TRI will hire leading researchers and engineers to support its wide range of activities."
Reference Dr. Gill Pratt's career Born in the U.S.A. in 1961. Obtained a Doctorate degree from the Electrical Engineering and Computer Science department at MIT, and taught at MIT and Olin College as Associate Professor and Professor, respectively. Established three startups between 1983 and 2005, and helped found Olin College. As a DARPA Program Manager, led projects in Neuromorphic Systems and Robotics, including the DARPA Robotics Challenge, from 2010 to 2015. Significantly influenced robotics research by leading the DARPA Robotics Challenge, where humans and robots collaborated for disaster response.
https://www.technologyreview.com/20...-self-driving-cars-with-an-invisible-copilot/
Toyota Joins the Race for Self-Driving Cars with an Invisible Copilot
"Pratt also suggested that Toyota will take a different computational approach. During his speech, he noted that existing self-driving cars use computers that consume thousands of watts. To achieve greater power efficiency, Pratt said Toyota could use neuromorphic chips, an architecture that computes data in parallel rather than sequentially, as conventional computers do."
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Lots of Toyota Research Institute Inc patents specifically mentioning neuromorphic processors:
Systems and methods for automatic test generation
https://patents.google.com/patent/US20200125472A1/
System and method of using a vehicle as a backup roadside unit (rsu)
https://patents.google.com/patent/US20200388161A1/
Simulation-based technique to synthesize controllers that satisfy signal temporal logic specifications
https://patents.google.com/patent/US20200379893A1
Personalized notification system for mobility as a service
https://patents.google.com/patent/US20200363229A1
Adjusting an operating mode of a vehicle based on an expected resource level
https://patents.google.com/patent/US20200353944A1/
Adaptive localized notifications
https://patents.google.com/patent/US10822000B1
Controlling driving condition components of an autonomous vehicle based on a current driving mode and current conditions
https://patents.google.com/patent/US10822000B1
Attention-based recurrent convolutional network for vehicle taillight recognition
https://patents.google.com/patent/US20200234066A1
Actively adapting to driving environments based on human interactions
https://patents.google.com/patent/US20200262444A1
Vehicles as traffic control devices
https://patents.google.com/patent/US20200250989A1
Autonomous vehicle route planning
https://patents.google.com/patent/JP2020106525A
Infrastructure-free nlos obstacle detection for autonomous cars
https://patents.google.com/patent/US20200143179A1
Selective arrival notification system
https://patents.google.com/patent/US20200294175A1
Debugging an autonomous driving machine learning model
Sampling training data for in-cabin human detection from raw video
https://patents.google.com/patent/US10776642B2
Toyota picks Renesas SoC to power its first self-driving cars
"Toyota has selected the embedded systems maker Renesas to supply the ARM-powered systems-on-a-chip to power autonomous vehicles scheduled for commercial launch in the year 2020."
https://global.toyota/en/detail/10171645
Toyota Will Establish New Artificial IntelligenceResearch and Development Company
"Directed by Dr. Gill Pratt, Toyota's Executive Technical Advisor and the Chief Executive Officer of the new enterprise, TRI will hire leading researchers and engineers to support its wide range of activities."
Reference Dr. Gill Pratt's career Born in the U.S.A. in 1961. Obtained a Doctorate degree from the Electrical Engineering and Computer Science department at MIT, and taught at MIT and Olin College as Associate Professor and Professor, respectively. Established three startups between 1983 and 2005, and helped found Olin College. As a DARPA Program Manager, led projects in Neuromorphic Systems and Robotics, including the DARPA Robotics Challenge, from 2010 to 2015. Significantly influenced robotics research by leading the DARPA Robotics Challenge, where humans and robots collaborated for disaster response.
https://www.technologyreview.com/20...-self-driving-cars-with-an-invisible-copilot/
Toyota Joins the Race for Self-Driving Cars with an Invisible Copilot
"Pratt also suggested that Toyota will take a different computational approach. During his speech, he noted that existing self-driving cars use computers that consume thousands of watts. To achieve greater power efficiency, Pratt said Toyota could use neuromorphic chips, an architecture that computes data in parallel rather than sequentially, as conventional computers do."
---
Lots of Toyota Research Institute Inc patents specifically mentioning neuromorphic processors:
Systems and methods for automatic test generation
https://patents.google.com/patent/US20200125472A1/
System and method of using a vehicle as a backup roadside unit (rsu)
https://patents.google.com/patent/US20200388161A1/
Simulation-based technique to synthesize controllers that satisfy signal temporal logic specifications
https://patents.google.com/patent/US20200379893A1
Personalized notification system for mobility as a service
https://patents.google.com/patent/US20200363229A1
Adjusting an operating mode of a vehicle based on an expected resource level
https://patents.google.com/patent/US20200353944A1/
Adaptive localized notifications
https://patents.google.com/patent/US10822000B1
Controlling driving condition components of an autonomous vehicle based on a current driving mode and current conditions
https://patents.google.com/patent/US10822000B1
Attention-based recurrent convolutional network for vehicle taillight recognition
https://patents.google.com/patent/US20200234066A1
Actively adapting to driving environments based on human interactions
https://patents.google.com/patent/US20200262444A1
Vehicles as traffic control devices
https://patents.google.com/patent/US20200250989A1
Autonomous vehicle route planning
https://patents.google.com/patent/JP2020106525A
Infrastructure-free nlos obstacle detection for autonomous cars
https://patents.google.com/patent/US20200143179A1
Selective arrival notification system
https://patents.google.com/patent/US20200294175A1
Debugging an autonomous driving machine learning model
US20200348670A1 - Debugging an autonomous driving machine learning model - Google Patents
A method for improving an autonomous driving system for an autonomous vehicle is disclosed. The method includes sub-sampling a frame generated by an output of a sensor and transmitting, to a remote device, the sub-sampled frame and classification data corresponding to the sub-sampled frame. The...
patents.google.com
Sampling training data for in-cabin human detection from raw video
https://patents.google.com/patent/US10776642B2
