Gm Global Technolgoy Operations, Inc.

David E Bojanowski

Fan Bai

Donald K Grimm

Jinzhu Chen

Bo Yu

Omer Tsimhoni

Charles A Massoll

Shu Chen

Robert B Powers

Chia-Hsiang Liu

Linda Sala Angell

Richard A Young

John P Weiss

David A Craig

Michael Wagner

Quan Zhang

Bijaya Aryal

Mark J Person

Walter J Holloway

Rodney A Gooden

Vivian T Williams

Joel D Lutz

Irwin J Karwick

Patrik Lundblad

Yan Nok Cheng

Vehicles and related systems and methods are provided for controlling a vehicle in an autonomous operating mode. One method involves obtaining navigation information for a route for the vehicle from a navigation system, transforming the navigation information into data points defining an upcoming trajectory of the route, mapping the data points to a corresponding mapped set of lane segments encompassing one or more of the data points, assigning lane preference indicia to the mapped set of lane segments, and autonomously operating one or more actuators onboard the vehicle to laterally maneuver the vehicle into one or more lanes at respective longitudinal positions along the route corresponding to one or more lane segments of the mapped set of lane segments in a manner that is influenced by the lane preference indicia assigned to the lane segments.

Vehicle systems and methods for autonomous route following

Methods and apparatus are provided for controlling a vehicle. In one embodiment, a method includes: receiving, by a processor, vehicle position data from the vehicle; processing, by the processor, vehicle position data with vehicle position data from other vehicles to determine a lane topology; processing, by the processor, the vehicle position data to determine traffic conditions within a lane of the lane topology; generating, by the processor, a map for controlling the vehicle based on the lane topology and the traffic conditions.

Methods and apparatus for detetermining lane-level static and dynamic information

Presented are systems and methods for deriving speed limits of designated road segments by mining large-scale vehicle data traces. A method for controlling operation of a motor vehicle includes: determining a current location of the vehicle; determining a designated road segment corresponding to the vehicle's location; receiving host speed data indicative of the vehicle's speed while travelling on the road segment for a calibrated timeframe; receiving crowd-sourced speed data indicative of the speeds of participatory vehicles while travelling on the road segment for the calibrated timeframe; accumulating a speed distribution function for the road segment based on the host and crowd-sourced speed data; generating a finite mixture model from the speed distribution function to estimate a speed limit range; selecting a speed limit candidate from the estimated speed limit range; and transmitting command signals to a vehicle subsystem to execute a control operation based on the selected speed limit candidate.

Intelligent vehicle navigation systems, methods, and control logic for deriving road segment speed limits

Presented are systems and methods for extracting lane-level information of designated road segments by mining vehicle dynamics data traces. A method for controlling operation of a motor vehicle includes: determining the vehicle's location; identifying a road segment corresponding to the vehicle's location; receiving road-level data associated with this road segment; determining a turning angle and centerline for the road segment; receiving vehicle data indicative of vehicle locations and dynamics for multiple vehicles travelling on the road segment; determining, from this vehicle data, trajectory data indicative of start points, end points, and centerline offset distances for these vehicles; identifying total driving lanes for the road segment by processing the trajectory data with a clustering algorithm given the turning angle and centerline; extracting virtual trajectories for the driving lanes; and commanding a vehicle subsystem to execute a control operation based on an extracted virtual trajectory for at least one driving lane.

Intelligent vehicle navigation systems, methods, and control logic for multi-lane separation and trajectory extraction of roadway segments

Disclosed are vehicle communications networks for adapting user information using crowd-sensed contextual data, computer-executable instructions for provisioning such content/information, and vehicles equipped with a telematics system for adapting driver information using contextual data from vehicle participatory sensing systems. A disclosed method for provisioning information to occupants of a motor vehicle includes determining trip characteristics, including vehicle and driver data, for a current trip of the vehicle, and determining trip characteristics for previous trips that correspond to the current trip. The vehicle's communications system receives, over a distributed computer network from a vehicle participatory sensing system aggregating data from participative vehicles, operational data for the current trip as sensed by the participative vehicles. The received operational data is analyzed with the current and previous trip characteristics to determine a predicted trip duration and/or a predicted trip route. An electronic user interface of the vehicle outputs the predicted trip duration and/or route.

Context-aware vehicle communications system and control logic with adaptive crowd-sensing capabilities

A system configured to receive baseline map data from a remote map-data source, and determine whether the baseline map data is sufficient for present mobile navigation-unit function, yielding a map-sufficiency determination. If the map-sufficiency determination is affirmative, using the baseline map data for the present mobile navigation-unit function. If the map-sufficiency determination is negative, the system predicts navigation-unit movement, obtains based on the navigation-unit movement predicted, supplemental map data, and uses the baseline map data and the supplemental map data for the present mobile navigation-unit function.

Progressive map maintenance at a mobile navigation unit

Systems and method are provided for implementing selective crowd sourcing. In one embodiment, a processor-implemented method for obtaining data from vehicles includes calculating a greedy parameter value for each of a plurality of vehicles in a geographical area; selecting no more than a predetermined number of the plurality of vehicles having a greedy parameter value in a greedy parameter threshold range; instructing the selected vehicles to transmit data while in the geographical area; and receiving the data from the selected vehicles. In another embodiment, a vehicle including a crowd sourcing selection module is provided. The crowd sourcing selection module is configured to retrieve consensus information from a central repository; calculate greedy parameter information regarding the vehicle using the consensus information; and determine whether to transmit an event observation to the central repository based on the greedy parameter information.

Method and apparatus of selective sensing mechanism in vehicular crowd-sensing system

A system having a resource-availability module configured to cause the processing unit to determine whether a resource scarcity condition exists in connection with providing map data to a mobile navigation unit. The system also includes a tuning-parameter module configured to cause the processing unit to, in response to determining that the resource scarcity condition exists, determine a tuning parameter to use in preparing map data to provide to the mobile navigation unit. The system further includes an encoding module configured to cause the processing unit to encode map data based on the tuning parameter, and a map-data-delivery module configured to cause the processing unit to provide or make available the encoded map data to the mobile navigation unit.

Systems and methods for progressive map maintenance and communication channel selection

A system and method for providing navigation routing options to a vehicle driver, including estimated fuel consumption and fuel cost. A server collects data from a large number of road vehicles driving different routes, where the data includes road grade, average speed, stop/start and acceleration/deceleration info and vehicle specifications, and the data is collected via a telematics or other wireless system. The server also receives map data, point of interest data and real-time traffic data from their respective providers. When a driver of a road vehicle requests navigation routing from a start point to a destination, the server provides multiple routing options including not only distance and time for each routing option, but also fuel consumption and cost. The estimated fuel consumption is computed using models based on the crowd-sensed data from the other vehicles driving the routes, where the models include a physics-based model and a machine learning model.

Method and apparatus for fuel consumption prediction and cost estimation via crowd sensing in vehicle navigation system

An assisted learning (AL) system for a vehicle including vehicle systems with input devices is provided. The AL system includes: memory that stores usage instructions for the input devices; an AL input device; an audio output device; and a control module that retrieves a respective one of the usage instructions associated with a selected one of the input devices when the selected one of the input devices is actuated after the AL input device is actuated and that outputs the usage instructions to the audio output device.

Assisted learning device

A vehicular navigation system includes a display, a memory configured to store data related to a plurality of preset map view, and a user input configured to permit the selection of a map view from the plurality of preset map views. A controller is coupled to the user input, the display, and the memory. The controller is configured to generate the selected map view on the display.

Vehicular navigation system for recalling preset map views

An apparatus and method are disclosed for real-time assessment of driver workload by a vehicle device. To determine driver workload, the system monitors the driver interaction with the vehicle device. The driver interaction is then used to determine an estimated driver workload based on the driver interaction. In one embodiment, the vehicle device has one or more buttons configured to be pressed by the driver and each of the one or more buttons has an assigned driver workload value. The system sums the workload value of the buttons pressed by the driver over a moving time window to determine the estimated driver workload.

Method for real-time assessment of driver workload by a navigation or telematics device

Methods and apparatus are provided for adaptively locking out a display on a vehicle device based on user interaction. A method begins by counting a number of user initiated display changes with an event counter, and timing the user initiated display changes with an event timer. The method continues by comparing the number of user initiated display changes in the event counter to an allowable number of user initiated display changes corresponding to the time in the event timer, and disabling the display for a display lockout time period if the number of user initiated display changes exceeds the allowable number of user initiated display changes.

Growing community of inventors

Clarkston, MI, United States of America

David E Bojanowski