Mobileye Vision Technologies Ltd.

John Weast

Ignacio Javier Alvarez

Maria Soledad Elli

Tal Serphos

Matt Yurdana

A system is described to derive local driving behaviors from naturalistic data, which are then incorporated as guidance into the behavioral layer of an Automated Vehicle (AV) for adaptation to local traffic. Moreover, the local driving behaviors are implemented in the AV performance validation process. The techniques facilitate scaling of this process via automatic crowdsourced behavioral data aggregation from human-driven vehicles, as well as ADAS vehicles and autonomous vehicles, and map information. The described techniques also enable the creation of a spatial-behavioral relational database that provides interfaces for efficiently querying geo-bounded local driving information, enabling customization of automated vehicle driving policies to local norms, and enabling traffic behavior analysis.

Safe and scalable model for culturally sensitive driving by automated vehicles

Methods and apparatus to provide accident avoidance information to passengers of autonomous vehicles are disclosed. An example apparatus includes a safety analyzer to determine an autonomously controlled vehicle is in a safe situation at a first point in time and in a dangerous situation at a second point in time. The example apparatus also includes a user interface generator to: generate user interface data to define content for a user interface to be displayed via a screen, the user interface to include a graphical representation of the vehicle, the user interface to graphically indicate the vehicle is in the safe situation at the first point in time; and modify the user interface data so that the user interface graphically indicates the vehicle is in the dangerous situation at the second point in time.

Growing community of inventors

Portland, OR, United States of America

John Weast