Huawei Technologies Co., Limited

Future Wei Technologies, Inc.

Hai Yu

Wei Huang

Fatih Porikli

Yuzhu Wu

Lei Yang

Chengcheng Jia

Luis Bill

A computer-implemented method of detecting distracted driving comprises: determining, by one or more processors, a primary preview region (PPR) in a representation of an environment; determining, by the one or more processors, a gaze point for a driver based on a sequence of images of the driver; determining, by the one or more processors, that the gaze point is outside of the PPR; based on the determined gaze point being outside of the PPR, decreasing, by the one or more processors, an attention level for the PPR; based on the attention level for the PPR, generating, by the one or more processors, an alert.

Primary preview region and gaze based driver distraction detection

The disclosure relates to technology for determining vehicle environment interaction metrics and/or passenger behavioral metrics for autonomous vehicles in a driving environment. A group of one or more autonomous vehicles independently determine a VEI score for a target vehicle within a predefined vicinity of the group of one or more vehicles. A target vehicle may determine a VPB score based on passengers within the target vehicle. VEI scores and/or VPB scores determined for a target vehicle may be used by the target vehicle to reinforce and/or correct driving actions of the target vehicle.

System and method for improving interaction of a plurality of autonomous vehicles with a driving environment including said vehicles

The disclosure relates to technology for a navigation system that enhances the safety of drivers using fatigue detection mapping. The navigation system accesses data sources storing map data a route for drivers of one or more first vehicles. Based on the map data, a personalized fatigue map for a driver of a second vehicle is generated based on the map data. The personalized fatigue map displays predicted driver fatigue of the driver of the second vehicle on the route. Drivers in the first and second vehicles are monitored to detect driver fatigue and a level of the driver fatigue is measured according to a calculated fatigue score. When driver fatigue is detected, a recommendation is output to the driver of the second vehicle that is based on the level of the driver fatigue. The personalized fatigue map is updated to reflect the recommendation.

Personalized routing based on driver fatigue map

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San Jose, CA, United States of America

Hai Yu