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US Patent 10235882 Early warning and collision avoidance

Patent 10235882 was granted and assigned to Derq on March, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Derq
Derq
Current Assignee
Derq
Derq
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10235882
Date of Patent
March 19, 2019
Patent Application Number
15994826
Date Filed
May 31, 2018
Patent Citations
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US Patent 10163350 Vehicular driver warnings
Patent Citations Received
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US Patent 12128929 Methods and system for predicting trajectories of actors with respect to a drivable area
0
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US Patent 11475774 Systems and methods for machine learning based collision avoidance
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US Patent 11472444 Method and system for dynamically updating an environmental representation of an autonomous agent
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US Patent 11472436 Method and system for operating an autonomous agent with incomplete environmental information
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US Patent 11513189 Systems and methods for intelligently calibrating infrastructure devices using onboard sensors of an autonomous agent
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US Patent 12077183 Method and system for remote assistance of an autonomous agent
0
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US Patent 12118879 C-V2X mobile edge computing interface for mobile services
0
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US Patent 11464275 Intelligent electronic footwear and control logic for automated infrastructure-based pedestrian tracking
...
Patent Primary Examiner
‌
Brent Swarthout
Patent abstract

Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data received from the sensor about ground transportation entities at or near the intersection is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. The wireless communication device sends the warning about the dangerous situation to the device of one of the ground transportation entities.

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