Hayden Ai Technologies, Inc.

Hayden Al Technologies, Inc.

Vaibhav Ghadiok

Bo Shen

Christopher Carson

Randal B Chinnock

Patrick L McGuire

Morgan Kohler

Shaocheng Wang

Marcin Grzesiak

Maciej Budys

Wiktor Muron

Joseph Virzi

Michael Gleeson-May

Ahmad Lemar

Andrei Liaukovich

Disclosed herein are systems, methods, and devices for detecting traffic lane violations. In one embodiment, a method for detecting a potential traffic violation is disclosed comprising bounding a vehicle detected from one or more video frames of a video in a vehicle bounding box. The vehicle can be detected and bounded using a first convolutional neural network. The method can also comprise bounding, using the one or more processors of the edge device, a plurality of lanes of a roadway detected from the one or more video frames in a plurality of polygons. The plurality of lanes can be detected and bounded using multiple heads of a multi-headed second convolutional neural network. The method can further comprise detecting a potential traffic violation based in part on an overlap of at least part of the vehicle bounding box and at least part of one of the polygons.

Lane violation detection using convolutional neural networks

Disclosed herein are systems and methods for alleviating traffic congestion within an enforcement zone. In some embodiments, a system for alleviating traffic congestion within an enforcement zone comprises a server and a plurality of edge devices coupled to carrier vehicles deployed within the enforcement zone. The edge devices can be configured to capture videos of vehicles that may be subject to the traffic congestion pricing policy and to determine their locations, license plate numbers, and certain vehicle attributes using certain sensors on the edge devices and deep learning models running on the edge devices. The edge devices can also be configured to transmit evidence packages to the server concerning such vehicles. The server can be configured to evaluate the evidence packages received from the edge devices and prepare final evidence packages concerning the vehicles for further review and processing.

Systems and methods for enforcing traffic congestion pricing

Disclosed herein are systems and apparatus for detecting a traffic violation. In one embodiment, a system for detecting a traffic violation comprises a context camera assembly and a license plate recognition (LPR) camera assembly. The context camera assembly can comprise a context camera housing containing a context camera, a context camera mount configured to mount the context camera housing to an interior of a carrier vehicle, and a context camera skirt coupled to and protruding outwardly from the context camera housing. The license LPR camera assembly can comprise an LPR camera housing containing one or more LPR cameras, an LPR camera mount configured to mount the LPR camera housing to the interior of the carrier vehicle, and one or more LPR camera skirts coupled to and protruding outwardly from the LPR camera housing.

Behind the windshield camera-based perception system for autonomous traffic violation detection

Disclosed herein are systems and methods for managing traffic rules. In one embodiment, a method of managing traffic rules can comprise generating or updating a semantic map layer based in part on positioning data obtained from one or more edge devices and videos captured by the one or more edge devices. The method can also comprise generating or updating a traffic enforcement layer on top of the semantic map layer. A plurality of traffic rules can be saved as part of the traffic enforcement layer. The method can further comprise generating or updating a traffic insight layer based in part on traffic violations or traffic conditions determined by the one or more edge devices or the server. The traffic insight layer can adjust or provide a suggestion to adjust at least one of the traffic rules based on an impact analysis conducted by the traffic insight layer concerning the traffic rule.

Systems and methods for managing traffic rules using multiple mapping layers with traffic management semantics

Disclosed herein are methods and systems for automatically validating evidence of traffic violations. One instance of a method comprises receiving an evidence package comprising video frames showing a vehicle involved in a potential traffic violation. The video frames can be input into one or more deep learning models to obtain a plurality of classification results. The method can further comprise generating a score based in part on the classification results and evaluating the score against one or more thresholds to determine whether the evidence package is automatically approved, is automatically rejected, or requires further review.

System and methods for automatically validating evidence of traffic violations using automatically detected context features

Disclosed are systems and methods for detecting traffic violations using one or more mobile detection devices. Videos captured by one or more mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a determination as to whether a traffic violation has occurred by comparing the data and information received from the mobile detection devices.

Systems and methods for detecting traffic violations using mobile detection devices

Disclosed herein are methods and systems that allow users to report traffic violations and obtain information concerning reported violations using mobile devices. In one embodiment, a method comprises receiving, at a server, one or more images or videos captured by a mobile device of an offending vehicle committing a potential traffic violation and an extended metadata tag; storing the one or more images or videos and the extended metadata tag as unstructured content in a content lake; generating database tables on top of the content lake; receiving a request from another mobile device to view traffic violation content; querying the database tables and retrieving at least one of the one or more images or videos of the offending vehicle committing the potential traffic violation from the content lake; and generating a GUI to be displayed via the other mobile device showing the traffic violation content.

Systems and methods for user reporting of traffic violations using a mobile application

Disclosed are systems and methods for detecting traffic violations using mobile detection devices. Videos captured by the mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a final determination as to whether a traffic violation has occurred by comparing the data and information received from at least two mobile detection devices. The server can also construct semantic annotated maps using data and information received from the mobile detection devices. Updated versions of the semantic annotated maps can be transmitted back to the mobile detection devices to aid in traffic violation detection.

Growing community of inventors

Mountain View, CA, United States of America

Vaibhav Ghadiok