Gm Global Technolgoy Operations, Inc.

University of Ottawa

Arun Adiththan

Prakash Mohan Peranandam

Ramesh Sethu

Md Mhafuzul Islam

Aravind Gangumalla

Vikramaditya Nimmagadda

Paolo Giusto

Joseph G D Ambrosio

Bakhtiar Brian Litkouhi

Yilu Zhang

SeyedAlireza Kasaiezadeh Mahabadi

Yao Hu

Azeem Sarwar

Rasoul Salehi

Shuqing Zeng

Upali Priyantha Mudalige

Shih-Ken Chen

Shige Wang

Qingrong Zhao

Wen-Chiao Lin

Roy J Mathieu

Shiming Duan

Wenyuan Qi

Praveen Palanisamy

Yubiao Zhang

Farui Peng

Ramesh S

Muralikrishnan Kailasam

Sachin Raviram

Osman Eser Atesoglu

Amirhossein Zolfagharian

Zohreh Aghababaeyan

Richard Romano

Zhiqiang J Zhou

Daniel Bouie

A context-based reminder system that determines a context-based reminder conveyed to an occupant of a vehicle includes a back-end server in wireless communication with one or more controllers that are part of the vehicle by a communication network. The back-send server receives, over the communication network, data indicative of a vehicle-oriented context and a user-oriented context from the one or more controllers of the vehicle and determines the context-based reminder based on the vehicle-oriented context and the user-oriented context. An output device of the vehicle creates a notification to the occupant indicative of the context-based reminder.

Context-based reminder system for a vehicle

A system for providing situational recommendations within a vehicle includes a system controller in communication with a plurality of onboard sensors, the plurality of onboard sensors adapted to collect real-time data related to a location of the vehicle and operating conditions of the vehicle, a database in communication with the system controller adapted to store data related to past actions and data related to a location of the vehicle and operating conditions of the vehicle when such past actions occurred, the system controller including a driver specific machine learning model adapted to predict a desired action based on the real-time data related to the location and operating conditions of the vehicle and data from the database, the system controller further adapted to initiate the predicted desired action, receive input from an occupant within the vehicle, and update the driver specific machine learning model.

Situational recommendations and control

A system for imitating target vehicle behavior in automated driving includes sensors capturing ego and target vehicle condition information, actuators selectively altering an ego vehicle state, and control modules. The control modules execute a target vehicle imitating (TVI) application. A first TVI control logic estimates a target vehicle state and trajectory. The ego and target vehicle condition information partially define the target vehicle state and trajectory. A second control logic evaluates target vehicle safety and performance constraints. A third control logic selectively initiates an imitation mode of the ego vehicle based on target and ego vehicle statuses relative to the target vehicle safety and performance constraints. A fourth control logic, models the target vehicle and optimizes a planned ego vehicle path subject to actuator constraints. A fifth control logic generates outputs to the actuators to cause the ego vehicle to follow the planned path and imitate the target vehicle.

System and method of imitating target vehicle behavior for automated driving

A system and method for locating a trailer coupler on a trailer to assist with the coupling of the trailer coupler to a vehicle hitch on a vehicle. The system includes a human-machine interface, a vehicle camera and a trailer camera, a mobile device application (App) with access to camera and mobile network a vehicle-to-infrastructure communication network, controllers, a memory, sensors, and a trailer detection and trajectory planning application. The application includes: initializing a data stream from the vehicle and trailer camera, capturing the data stream from the vehicle camera and from the trailer camera, determining key landmarks in the data stream, combining the key landmarks, determining a coupler location, computing a joint reference trajectory using the coupler location, and providing navigation assistance in real time based on the joint reference trajectory.

System and method for detecting a trailer coupler and planning a trajectory

A system for monitoring a driver in a vehicle includes a driver monitoring system adapted to monitor the driver of the vehicle, a system controller in communication with the driver monitoring system and adapted to collect data from the driver monitoring system related to gaze behavior of the driver, classify the driver as one of a plurality of driver attention statuses based on the data from the driver monitoring system, the driver attention statuses including safe, borderline and unsafe, and, when the driver status is unsafe, prompt the driver, via a human machine interface (HMI), with questions adapted to test the alertness of the driver, receive, via the HMI, from the driver, responses to the questions, analyze the responses, and initiate responsive actions based on the responses from the driver.

Driver attention detection

A resource sharing marketplace platform for vehicle parking spots includes a back-office server including a controller adapted to run a plurality of integrated systems and a wireless communication module in communication with the controller, wherein, the resource sharing marketplace platform is adapted to receive, via the wireless communication module, a request from a user, collect, via the wireless communication module, data related to available registered parking spots from a network database of registered parking spots, and provide a response to the user including a sub-group of registered parking spots.

Parking and charging marketplace and reservation system

A system for controlling an ego vehicle following a lead vehicle without vehicle-to-vehicle (V2V) communication includes sensors disposed on the ego vehicle and capturing ego and lead vehicle condition information. Control modules disposed in the ego vehicle each have a processor, memory, and input/output (I/O) ports. The I/O ports communicate with the one or more sensors. The memory stores control logic, and the processor executes the control logic, including a lead vehicle following (LVF) application. A first control logic receives a start input from a vehicle occupant via a human-machine interface (HMI) in communication with the I/O ports. A second control logic performs a feasibility analysis of ego and lead vehicle conditions according to feasibility conditions. A third control logic selectively initiates lead vehicle following. A fourth control logic continuously monitors feasibility of lead vehicle following, and fifth control logic selectively disables the LVF application upon receiving a disengagement command.

Method for following a lead vehicle without vehicle-to-vehicle communication

A system for context-oriented auto park assist includes sensor, communication, and vehicle control sub-systems. Each sub-systems has control modules having processors, memories, and input/output (I/O) ports. The I/O ports of the sensor and communication sub-systems are in communication with the vehicle control system. The control modules execute program code portions stored in the memory including a program code portions that generates occupant, environmental, time and location, and vehicle contexts, and a combined context by combining the occupant, environmental, location and time, and vehicle contexts. The system scans a parking area for candidate parking spots by applying the combined context vector as the vehicle is driven through the parking area. The system informs vehicle occupants of the presence of candidate parking spots, and upon receiving an input from the vehicle occupants, performs one or more automated driver assistance system (ADAS) actions through the vehicle control system to park the vehicle.

System and method for context oriented auto park assist

A motor vehicle motion control health monitoring system includes sensors and actuators disposed on the motor vehicle. The sensors measure real-time static and dynamic telemetry data about the motor vehicle, and the actuators alter static and dynamic behavior of the motor vehicle. A control module has a processor, a memory, and input/output (I/O) ports. The processor executes program code portions stored in the memory, the program code portions include: an offline portion that collects telemetry data from the motor vehicle, performs failure analysis on the telemetry data and allocates tasks based on the failure analysis; and an online portion that analyzes the telemetry data for failures within specific sensors, actuators, or functions that utilize systems of sensors and/or actuators. The online portion mitigates deviations in the telemetry data by sending a correction to the one or more sensors, actuators, and/or functions of a motor vehicle motion control system.

Architecture and methodology for vehicle motion control health monitoring and mitigation

A method is provided for operating a vehicle having an interior control setting system with a computer. One or more occupant input devices generate an occupant input signal associated with sensor data, which indicates a total number of occupants, a classification, and a current emotion for each occupant disposed in the vehicle. One or more processors uses multiple occupant profiles, with each occupant profile mapped to a unique occupant identification and a plurality of actuated interior control settings, to determine an n-occupant emotion vector based on the total number of the occupants and the classification for each occupant. The processor maps the n-occupant emotion vector to interior control settings and determines a predicted interior control setting for the occupant. The processor generates an actuation signal associated with the predicted interior control setting, such that one or more actuators actuate a vehicle component based on the predicted interior control setting.

Vehicle system and method for adjusting interior control settings based on driver emotion and environmental context

A method in an On-Demand Autonomy system includes: monitoring for a trip change request from a plurality of platoon vehicles including a first leader vehicle (Lv) and a follower vehicle (Fv). When a trip termination request is received from a platoon vehicle, the method includes broadcasting information regarding the request to the other platoon vehicles, and monitoring for an acknowledgement of the request. When the trip termination request originated from the first Lv, the method includes electing a new Lv, computing a rendezvous point for the new Lv and the Fv, and signaling the Fv and new Lv regarding the rendezvous point. When a trip modification request is received from the Fv, the method includes broadcasting information regarding the request to the first Lv, electing a new Lv, computing a rendezvous point for the new Lv and the Fv, and signaling the Fv and new Lv regarding the rendezvous point.

System amd method for providing a ride assistant for on-demand autonomy

A resource sharing marketplace platform includes a back-office server including a controller adapted to run a plurality of integrated systems and a wireless communication module in communication with the controller, wherein, the resource sharing marketplace platform is adapted to receive a request from a user, collect data from a plurality of acceptable service providers, and provide a response to the user.

Electronics and data resource sharing marketplace platform

An infotainment system for a vehicle selects and plays recordings based on a current emotion of a user in response to receiving a user-generated query. The user-generated query includes one or more words indicating a current state of mind of the user. The infotainment system includes one or more controllers in electronic communication with one or more recording databases that store a plurality of content clusters that each describe a specific recording. The one or more controllers execute instructions to select a recording described by a selected content cluster, where the recording reflects the current emotion of a user.

Vehicle infotainment system for selecting recordings based on user emotion

A computing system including a cooperative system architecture for cataloging, informing, sharing, and managing engineering assets within an organization includes a user management subsystem for creating a registered user profile associated with a specific user of the computing system. The registered user profile includes user metadata that provides identifying characteristics of the specific user. The computing system includes an asset management subsystem including an asset repository for recording one or more engineering assets. The asset management subsystem modifies the user metadata of the registered user profile in response to the specific user recording an engineering asset in the asset repository. The computing system includes a test management subsystem including a test repository for recording one or more test bill of materials.

Cooperative system architecture for engineering asset management and sharing

A vehicle system for recommending driving automation based on occupant behavior and emotion includes one or more input devices. The input devices generate an input signal associated with sensor data indicative of a current emotion and a current driving pattern of an occupant. The vehicle system further includes a computer having a processor and a non-transitory computer readable storage medium (CRM). The CRM stores multiple occupant behavior profiles, with each occupant behavior profile including a unique occupant identification and multiple historical driving patterns. Each driving pattern has an associated historical emotion for the unique occupant identification. The processor is programmed to determine a deviation of the current driving pattern from the historical driving patterns, compare the deviation to a threshold, and generate a notification signal. The notification device provides the notification to recommend that the occupant actuate the vehicle system.

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Warren, MI, United States of America

Arun Adiththan