Gm Global Technolgoy Operations, Inc.

Yi G Glaser

Daniel S Glaser

Joseph F Szczerba

Ron M Hecht

Omer Tsimhoni

Ke Liu

Sri Krishna Divya Pemmaraju

Paul Edward Krajewski

Mohammad Naserian

Allan K Lewis

Vivek Vijaya Kumar

Roy J Mathieu

Michael A Wuergler

Noa Garnett

Jay H Sim

Ronit Bustin

Justin K Francisco

Lisa M Talarico

Udo Schultheis

James V Roell

Robert McCulloch

Paul Gill

Maureen Elizabeth August

A system for initiating an automated slowdown procedure within a vehicle includes a system controller adapted to detect a request for initiation of an automated slowdown procedure, a human machine interface (HMI), wherein the system controller is adapted to prompt, via the HMI, the driver of the vehicle for verification to initiate the automated slowdown procedure, and a vehicle control module, wherein the system controller is adapted to initiate, via the vehicle control module, the automated slowdown procedure when either one of the driver provides, via the HMI, verification to initiate the automated slowdown procedure, or a response from the driver is not received within a pre-determined time.

Selective vehicle slowdown

A system for utilizing human machine interfaces to engage at least one passenger when a driver of a vehicle is distracted includes a system controller in communication with a plurality of passenger human machine interfaces and adapted to modify a display screen of a front seat passenger HMI, and an occupant monitoring system adapted to monitor the driver of the vehicle and the at least one passenger within the vehicle, the system controller adapted to determine, with a distracted driver algorithm within the system controller and data from the occupant monitoring system that the driver of the vehicle is distracted, and, when the driver of the vehicle is distracted, to actuate the plurality of passenger HMIs to engage the at least one passenger and encourage the at least one passenger to engage with the driver of the vehicle.

Utilizing HMI with distracted driver

A system and method for limited rate context-based eye gaze encoding includes generating, based on an outward looking camera situated in a vehicle, a first video stream of a surrounding environment to a controller. The controller generates a scene description based on the first video stream and selects a corresponding scene from a predefined list of known scenes. Further, the controller, based on the selected corresponding scene, selects a codebook of encoding and decoding parameters from a plurality of predefined codebooks. Based on an inward looking camera situated in the vehicle, a second video stream of a face of a driver to an eye tracker controller is generated, where the eye tracker controller estimates a gaze direction of the driver. Encoded data comprising the estimated gaze direction of the driver is transmitted over a bandwidth limited channel to a decoder, based on the selected codebook, the encoded data.

Limited rate context based eye gaze encoding

A full speed range adaptive cruise control system for a vehicle that stops at an intersection includes one or more controllers that execute instructions to receive localization data and situational data related to the vehicle. The one or more controllers determine, based on localization data and situational data, that the vehicle is approaching an intersection and will come to a stop at the intersection, where the vehicle is part of a queue including one or more surrounding vehicles. In response to determining the vehicle has come to a stop, the controller determines a position of the vehicle within the queue and an overall length of the queue. The controller calculates an adaptive launch time based on at least the position of the vehicle within the queue, the overall length of the queue, the situational data, and a timing delay associated with the queue.

Full speed range adaptive cruise control system for determining an adaptive launch time for a vehicle

A method of managing operator take-over of autonomous vehicle. The method includes gathering information on an external surrounding of the autonomous vehicle; analyzing the gathered information on the external surrounding of the autonomous vehicle to determine an upcoming traffic pattern; gathering information on an operator of the autonomous vehicle; analyzing the gathered information on the operator of the autonomous vehicle to determine an operator behavior; predicting an operator action based on the determined upcoming traffic pattern and the determined operator behavior; and initiating a predetermined vehicle response based on the predicted operator action. The predicting the operator action includes comparing the determined upcoming traffic pattern with a similar historic traffic pattern and retrieving a historical operator action in response to the similar historical pattern.

System and method of managing a driver take-over from an autonomous vehicle based on monitored driver behavior

A system for providing driver status to a driver of a vehicle includes a data processor, a plurality of sensors mounted within the vehicle and adapted to send vehicle information to the data processor, a driver monitoring system within the vehicle adapted to send driver information to the data processor, the data processor further adapted to collect information from external sources via a wireless data communication network, and a driver state display adapted to receive information from the data processor and to display a short-term status indicator, a long-term status indicator and contextual information.

Driver state display

An autonomous driving system of a vehicle includes: an autonomous module configured to, during autonomous driving, control at least one of: steering of the vehicle; braking of the vehicle; and acceleration and deceleration of the vehicle; and a driving control module configured to: enable and disable autonomous driving; determine a future time for beginning a period of autonomous driving; and at least one of: selectively delay the beginning of autonomous driving to after the future time; and cancel the period of autonomous driving.

Autonomous driving control systems and methods

A method of monitoring a driver in an autonomous vehicle includes monitoring, with a driver monitoring system, a driver of a vehicle, collecting, with a data processor, data from the driver monitoring system related to gaze behavior of the driver, classifying, with the data processor, the driver as one of a plurality of driver statuses based on the data from the driver monitoring system, and sending, with the data processor, instructions to at least one vehicle system based on the classification of the driver.

Predicting driver status using glance behavior

A system includes a plurality of sensors arranged in a vehicle to monitor an item in a storage area of a vehicle. The system comprises a data processing module configured to process data from the sensors, determine whether the item in the storage area of the vehicle is likely to move within the storage area or is likely to fall from the vehicle during travel, and generate a first indication that the item is likely to move within the storage area or is likely to fall from the vehicle during travel. The data processing module is configured to determine whether the item has moved within the storage area or has fallen from the vehicle during travel and generate a second indication that the item has moved within the storage area or has fallen from the vehicle during travel.

Systems and methods for monitoring and maintaining stability of vehicle cargo

Examples of techniques for overlaying on an in-vehicle display road objects associated with potential hazards are disclosed. In one example implementation, a method may include: responsive to detecting a presence of a detected vehicle in proximity to the local vehicle, determining, by a processing device, a position of the detected vehicle, a speed of the detected vehicle, and a time to the local vehicle of the detected vehicle; determining, by the processing device, whether the detected vehicle, in proximity to the local vehicle, represents a potential hazard to the local vehicle based on the position of the detected vehicle, the speed of the detected vehicle, and a time to the local vehicle of the detected vehicle; and responsive to determining that the detected vehicle, in proximity to the local vehicle, represents a potential hazard to the local vehicle, overlaying, by the processing device, a warning indicium on the in-vehicle display.

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West Bloomfield, MI, United States of America

Yi G Glaser