Abstract: A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: execute an autonomous vehicle algorithm simulating vehicle operations within a simulated environment. The simulated environment represents a plurality of driving situations. The memory also includes instructions such that the processor is programmed to: determine a challenge rating for the driving situation, determine an autonomous vehicle performance assessment score corresponding to the simulated environment, compare the autonomous vehicle performance assessment score with a human driving score corresponding to the simulated environment, and generate a performance profile based on the comparison. In some implementations, a vehicle computer can determine a challenge rating and generate at least one of a driver takeover recommendation or an alert indicating a presence of a fault based on a comparison of vehicle performance with the challenge rating.

Abstract: A system for selecting an optimized parking location for a vehicle includes a data processor, a plurality of sensors within the vehicle, and a user model based on historical data of parking events for the vehicle, the data processor is adapted to collect parking preferences for a driver of the vehicle, identify a destination of the vehicle, identify a current location of the vehicle, collect data from a plurality of sensors within the vehicle, collect data from external sources and create a list of potential parking spaces, access the user model, rank the potential parking spaces based on the parking preferences of the driver, the data from external sources and the user model, and provide an output based on parking preferences for the driver of the vehicle and the user model.

Abstract: System and method of controlling operation of a device in real-time. The system includes an optical sensor having a steerable optical field of view for obtaining image data and a radar unit having a steerable radar field of view for obtaining radar data. A controller may be configured to steer a first one of the optical sensor and the radar unit to a first region of interest and a second one of the optical sensor and the radar unit to the second region of interest. The controller may be configured to steer both the optical sensor and the radar unit to the first region of interest. The radar data and the image data are fused to obtain a target location and a target velocity. The controller is configured to control operation of the device based in part on at least one of the target location and the target velocity.

Abstract: A system and method for obtaining an overall image that is constructed from multiple sub-images. The method includes: capturing a first sub-image having a first sub-image field of view using an image sensor of an electronically-steerable optical sensor; after capturing the first sub-image, steering light received at the electronically-steerable optical sensor using an electronically-controllable light-steering mechanism of the electronically-steerable optical sensor so as to obtain a second sub-image field of view; capturing a second sub-image having the second sub-image field of view using the image sensor of the electronically-steerable optical sensor; and combining the first sub-image and the second sub-image so as to obtain the overall image.

Abstract: System and method of controlling operation of a device in real-time. The system includes an optical sensor having a steerable optical field of view for obtaining image data and a radar unit having a steerable radar field of view for obtaining radar data. A controller may be configured to steer a first one of the optical sensor and the radar unit to a first region of interest and a second one of the optical sensor and the radar unit to the second region of interest. The controller may be configured to steer both the optical sensor and the radar unit to the first region of interest. The radar data and the image data are fused to obtain a target location and a target velocity. The controller is configured to control operation of the device based in part on at least one of the target location and the target velocity.

Abstract: Methods and systems for automatically controlling a vehicle are disclosed. In one embodiment, a system includes an actuator configured to control one or more vehicle driving characteristics, at least one vehicle sensor configured to measure a vehicle characteristic, a remote assistant in communication with the vehicle, and a controller in communication with the actuator, the at least one vehicle sensor, and the remote assistant, the controller being programmed with an automated driving system control algorithm and configured to determine whether a failsafe condition has occurred based on sensor data from the at least one vehicle sensor, receive a control signal from the remote assistant, and automatically control the actuator based on the control signal.

Abstract: Methods are provided for intelligently overriding a driving automation system for a vehicle. The method first identifies a road feature ahead of the vehicle that requires overriding the engaged driving automation system. A deceleration zone is calculated for the vehicle prior to reaching the road feature and a transition zone is identified for the vehicle to pass through while under driver control. The driver is signaled to disengage the driving automation system as the vehicle approaches the deceleration zone and take control of the vehicle. If the driver fails to take control, the vehicle stops and shuts off the driving automation system. If the driver takes control, the vehicle passes through the transition zone and the driving automation system re-engages once the vehicle exits the transition zone.

Abstract: Methods and systems for controlling a driving feature for an automated driving system are provided. In one embodiment, a method includes: receiving a first sensor signal from a first sensor; receiving a second sensor signal from a second sensor; selectively determining a driver intent based on at least one of the first sensor signal and the second sensor signal; and controlling the driving feature based on the driver intent.

Abstract: A method for localizing a vehicle in a digital map. GPS raw measurement data is retrieved from satellites. A digital map of a region traveled by the vehicle based on the raw measurement data is retrieved from a database. The digital map includes a geographic mapping of a traveled road and registered roadside objects. The registered roadside objects are positionally identified in the digital map by earth-fixed coordinates. Roadside objects are sensed in the region traveled by the vehicle using distance data and bearing angle data. The sensed roadside objects are matched on the digital map. A vehicle position is determined on the traveled road by fusing raw measurement data and sensor measurements of the identified roadside objects. The position of the vehicle is represented as a function of linearizing raw measurement data and the sensor measurement data as derived by a Jacobian matrix and normalized measurements, respectively.

Abstract: Methods and systems for automatically controlling a vehicle are disclosed. In one embodiment, a system includes an actuator configured to control one or more vehicle driving characteristics, at least one vehicle sensor configured to measure a vehicle characteristic, a remote assistant in communication with the vehicle, and a controller in communication with the actuator, the at least one vehicle sensor, and the remote assistant, the controller being programmed with an automated driving system control algorithm and configured to determine whether a failsafe condition has occurred based on sensor data from the at least one vehicle sensor, receive a control signal from the remote assistant, and automatically control the actuator based on the control signal.

Abstract: An automated vehicle includes a control system configured to selectively transfer the automated vehicle from an automated control mode to a manual control mode based on a transfer-of-control criterion. The transfer-of-control criterion is based on a current context of the automated vehicle and a dataset of previous transfer-of-control events and previous contexts associated with the operation of a plurality of additional automated vehicles.

Abstract: Methods and systems are provided for controlling a vehicle. In one embodiment, a method includes: determining, by a processor, unresponsiveness of at least one of a driver and a vehicle system; in response to the determining, communicating, by a processor, a request for remote control to a remote server; in response to the communicating, receiving, by a processor, information from the remote server; and controlling the vehicle by one or more semi-autonomous or autonomous vehicle controls systems based on the received information.

Abstract: Methods and systems for monitoring a driver of a vehicle are provided. In accordance with one embodiment, a system includes a sensing unit and a processor. The sensing unit is configured to at least facilitate detecting whether a driver of a vehicle is looking or has recently looked in a direction with respect to the vehicle. The processor is coupled to the sensing unit, and is configured to at least facilitate providing an action based at least in part on whether the driver is looking or has recently looked in the direction.

Abstract: A vehicle lateral control system includes a lane marker module configured to determine a heading and displacement of a vehicle in response to images received from a secondary sensing device, a lane information fusion module configured to generate vehicle and lane information in response to data received from heterogeneous vehicle sensors and a lane controller configured to generate a collision free vehicle path in response to the vehicle and lane information from the lane information fusion module and an object map.

Abstract: A method for localizing a vehicle in a digital map. GPS raw measurement data is retrieved from satellites. A digital map of a region traveled by the vehicle based on the raw measurement data is retrieved from a database. The digital map includes a geographic mapping of a traveled road and registered roadside objects. The registered roadside objects are positionally identified in the digital map by earth-fixed coordinates. Roadside objects are sensed in the region traveled by the vehicle using distance data and bearing angle data. The sensed roadside objects are matched on the digital map. A vehicle position is determined on the traveled road by fusing raw measurement data and sensor measurements of the identified roadside objects. The position of the vehicle is represented as a function of linearizing raw measurement data and the sensor measurement data as derived by a Jacobian matrix and normalized measurements, respectively.

Abstract: A method and system for localizing a vehicle in a digital map includes generating GPS coordinates of the vehicle on the traveled road and retrieving from a database a digital map of a region traveled by the vehicle based on the location of the GPS coordinates. The digital map includes a geographic mapping of a traveled road and registered roadside objects. The registered roadside objects are positionally identified in the digital map by longitudinal and lateral coordinates. Roadside objects in the region traveled are sensed by the vehicle. The sensed roadside objects are identified on the digital map. A vehicle position on the traveled road is determined utilizing coordinates of the sensed roadside objects identified in the digital map. The position of the vehicle is localized in the road as a function of the GPS coordinates and the determined vehicle position utilizing the coordinates of the sensed roadside objects.

Abstract: A method of detecting and tracking objects using multiple radar sensors. Objects relative to a host vehicle are detected from radar data generated by a sensing device. The radar data includes Doppler measurement data. Clusters are formed, by a processor, as a function of the radar data. Each cluster represents a respective object. Each respective object is classified, by the processor, as stationary or non-stationary based on the Doppler measurement data of each object and a vehicle speed of the host vehicle. Target tracking is applied, by the processor, on an object using Doppler measurement data over time in response to the object classified as a non-stationary object; otherwise, updating an occupancy grid in response to classifying the object as a stationary object.

Abstract: An automated vehicle includes a control system configured to selectively transfer the automated vehicle from an automated control mode to a manual control mode based on a transfer-of-control criterion. The transfer-of-control criterion is based on a current context of the automated vehicle and a dataset of previous transfer-of-control events and previous contexts associated with the operation of a plurality of additional automated vehicles.

Abstract: Methods and control systems are provided for automatically controlling operation of a vehicle. In one embodiment, the control system includes an exterior sensor for sensing the environment outside the vehicle. A processor is in communication with the exterior sensor and configured to calculate a driving plan of the vehicle based at least partially on the sensed environment outside the vehicle. The processor is also configured to calculate a confidence level of the driving plan of the vehicle based at least partially on the sensed environment around the vehicle. The control system also includes a display in communication with the processor and configured to receive data from the processor and display a representation of at least one of the driving plan and the confidence level.

Abstract: A method and system may manage the driver's attention while driving. The driver may be driving using an autonomous driving system or limited-ability autonomous driving system. A method may detect, by a sensor, characteristics of a driver; determine, based on the detected characteristics of the driver, whether the driver exercises sufficient supervisory control of the vehicle; and provide a series of one or more prompts, wherein each prompt's intrusiveness is related to the determination of whether the driver exercises sufficient supervisory control of the vehicle.