Abstract: 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.

Abstract: 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.

Abstract: A method for allocating computing resources for a vehicle includes determining an optimal task configuration for a computing task based at least in part on a task constraint of the computing task. The method further may include determining a criticality level of the computing task based at least in part on the optimal task configuration and the task constraint of the computing task. The method further may include routing the computing task to one of a plurality of remote server systems based at least in part on the criticality level of the computing task.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system for monitoring misbehavior of neighboring vehicles and initiating interventions within a vehicle includes a plurality of onboard vehicle sensors in communication with a system controller, the system controller adapted to identify at least one neighboring vehicle, tag the at least one neighboring vehicle with a unique identifier, monitor, with the plurality of onboard sensors, driving patterns of the at least one neighboring vehicle, classify the at least one neighboring vehicle, and initiate intervention action.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system for determining a representative vehicle software configuration for a subset vehicles that are part of a group of vehicles. The system includes one or more processors and a memory coupled to the one or more processors, where the memory stores data comprising a database and program code that, when executed by the one or more processors, causes the system to select a module configuration that is part of a set of combined module configurations as the representative vehicle software configuration based on at least one predefined criteria.

Abstract: 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.

Abstract: 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.

Abstract: A resource sharing marketplace platform includes a back-office server in wireless communication with a controller adapted to run a plurality of integrated systems, and is adapted to authenticate identification of the user and facilitate user log-in, receive a request from a user, establish dynamic parameters related to the request, break down the request from the user into a plurality of serviceable micro-queries by decomposing at least one request for multivariate data into a plurality of requests for multivariate and univariate data, and develop a contract including key clauses and reward constraints, identify, from a group of registered service providers, a sub-group of registered service providers that are capable of providing data related to at least one micro-query, and send a request for data to the sub-group, collect data from a plurality of acceptable service providers, and repack the individual data to provide a response to the user.

Abstract: An autonomous driving system for an autonomous vehicle includes a plurality of on-board autonomous sensors that sense data related to operation of the autonomous vehicle and a surrounding environment and an automated driving controller in electronic communication with the plurality of on-board autonomous sensors. The automated driving controller is instructed to receive an indication one or more of the plurality of on-board autonomous sensors are non-functional and a secondary autonomous sensor system including one or more replacement sensors are installed. The automated driving controller is instructed to verify the secondary autonomous sensor system based on a security check and perform a redundancy check between the one or more replacement sensors and the plurality of on-board autonomous sensors. In response to determining the one or more replacement sensors are valid based on the redundancy check, the automated driving controller operates the autonomous vehicle in a limp home mode.