IP Library › Granted Patent US 10,214,136
Granted Patent B2
US 10,214,136 · App. 15/706,857 · Granted Feb 26, 2019

Adaptive vehicle illumination utilizing visual pattern learning and cognitive enhancing

Inventors: Yu Tao Ba (Beijing, CN); Bo Zhang (Beijing, CN); Lin Tang (Beijing, CN); Changrui Ren (Beijing, CN)
Assignee: International Business Machines Corporation
B60Q1/085G06K9/00604G06K9/00845G06N5/047B60Q1/12B60Q2300/112B60Q2300/114B60Q2300/23
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Quick Facts
Patent No.
US 10,214,136
App. No.
15/706,857
Granted
Feb 26, 2019
Kind
B2
Abstract

Embodiments describing an approach to receiving visual feedback. Generating a recommended visual pattern based on the visual feedback. Tracking a driver's real-time visual pattern. Extracting the driver's real-time visual patterns from the eye-tracking data. Determining the differences between the recommended visual pattern and the driver's real-time visual pattern. Generating enhanced headlamp control configurations based on the determined differences between the recommended visual pattern and the driver's real-time visual pattern; and adjusting the headlamp calibration controls based on the enhanced headlamp control configuration.

Claims (11)

1. A method for adjusting headlight calibration controls based on eye-tracking data for improving driver safety, the method comprising:

receiving, by one or more processors, visual feedback, wherein the visual feedback is based on radar data;

generating, by the one or more processors, a recommended visual pattern based on the visual feedback;

tracking, by the one or more processors, a driver's real-time visual pattern, wherein tracking a driver's real-time visual pattern further comprises driving characteristics, wherein driving characteristics comprise the vehicles speed, velocity, how fast the driver accelerates, the amount of pressure the driver applies to the breaks, how often the breaks are being applied, the speed at which the gears are shifted, and average revolutions per minute (RPM);

extracting, by the one or more processors, the driver's real-time visual patterns from eye-tracking data, wherein extracting the driver's real-time visual patterns from the eye-tracking data further comprises extracting fixation indexes from the eye-tracking data, wherein eye-tracking data comprises: where the driver is looking, where the driver is focusing, the area of the road the driver is not focusing on, the driver's peripheral vision, visual blind spots, when the driver blinks, the rate at which the driver blinks, how strained the drivers eyes become while trying to focus on the road, road visibility, level of visual stimuli on the road, or how the drivers pupil react to different stimuli;

determining, by the one or more processors, differences between the recommended visual pattern and the driver's real-time visual pattern;

generating, by the one or more processors, enhanced headlamp control configurations based on the determined differences between the recommended visual pattern and the driver's real-time visual pattern;

adjusting, by the one or more processors, headlamp calibration controls based on the enhanced headlamp control configuration;

creating, by the one or more processors, a driver profile;

storing, by the one or more processors, driver data to a database; and

updating, by the one or more processors, driver profile data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 18, 2017
From: BA, YU TAO; ZHANG, BO; TANG, LIN; REN, CHANGRUI
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 043611/0284 →
Continuity (2)
Continuation 15661008 · Jul 27, 2017
Related Publication 20190031085A1 · Jan 31, 2019