Abstract: Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by a method. An example method includes transmitting a help request for help to a help center based on an emergency status of an occupant of a vehicle. The method also includes receiving availability information from the help center. The availability information indicates availability of one or more potential leader vehicles in an area. The method yet further includes placing the system in a follower mode based on a selection of a leader vehicle from the one or more potential leader vehicles by establishing a connection with the potential leader vehicle. In follower mode the vehicle is a follower vehicle. The method additionally includes wirelessly receiving a navigation instruction from the leader vehicle. The method includes executing a driving maneuver in an autonomous fashion based on the navigation instruction from the leader vehicle.

Abstract: Methods and systems may be used for obtaining a high-confidence point-cloud. The method includes obtaining three-dimensional sensor data. The three-dimensional sensor data may be raw data. The method includes projecting the raw three-dimensional sensor data to a two-dimensional image space. The method includes obtaining sparse depth data of the two-dimensional image. The method includes obtaining a predicted depth map. The predicted depth map may be based on the sparse depth data. The method includes obtaining a predicted error-map. The predicted error map may be based on the sparse depth data. The method includes outputting a high-confidence point-cloud. The high-confidence point-cloud may be based on the predicted depth map and the predicted error-map.

Abstract: Methods and systems may be used for obtaining a high-confidence point-cloud. The method includes obtaining three-dimensional sensor data. The three-dimensional sensor data may be raw data. The method includes projecting the raw three-dimensional sensor data to a two-dimensional image space. The method includes obtaining sparse depth data of the two-dimensional image. The method includes obtaining a predicted depth map. The predicted depth map may be based on the sparse depth data. The method includes obtaining a predicted error-map. The predicted error map may be based on the sparse depth data. The method includes outputting a high-confidence point-cloud. The high-confidence point-cloud may be based on the predicted depth map and the predicted error-map.

Abstract: Methods and system for compensating for vehicle system errors. A virtual camera is added to vehicle sensor configurations and a coordinate transformation process which attempts to match multiple 3D points associated with a landmark to a detected landmark. The virtual camera is associated with the detected landmark. The 3D world coordinate points may be transformed to a real 3D camera coordinate system and then to a virtual 3D camera coordinate system. The 3D points in real and virtual camera coordinate frames are projected onto the corresponding 2D image pixel coordinates, respectively. Inclusion of the virtual camera in the coordinate transformation process presents a 3D to 2D point corresponding problem which may be resolved using camera pose estimation algorithms. An offset compensation transformation matrix may be determined which accounts for errors contributed by mis-calibrated vehicle sensors or systems and applied to all data prior to use by the vehicle control systems.

Abstract: Methods and system for compensating for vehicle system errors. A virtual camera is added to vehicle sensor configurations and a coordinate transformation process which attempts to match multiple 3D points associated with a landmark to a detected landmark. The virtual camera is associated with the detected landmark. The 3D world coordinate points may be transformed to a real 3D camera coordinate system and then to a virtual 3D camera coordinate system. The 3D points in real and virtual camera coordinate frames are projected onto the corresponding 2D image pixel coordinates, respectively. Inclusion of the virtual camera in the coordinate transformation process presents a 3D to 2D point corresponding problem which may be resolved using camera pose estimation algorithms. An offset compensation transformation matrix may be determined which accounts for errors contributed by mis-calibrated vehicle sensors or systems and applied to all data prior to use by the vehicle control systems.

Abstract: Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by a method. An example method includes transmitting a help request for help to a help center based on an emergency status of an occupant of a vehicle. The method also includes receiving availability information from the help center. The availability information indicates availability of one or more potential leader vehicles in an area. The method yet further includes placing the system in a follower mode based on a selection of a leader vehicle from the one or more potential leader vehicles by establishing a connection with the potential leader vehicle. In follower mode the vehicle is a follower vehicle. The method additionally includes wirelessly receiving a navigation instruction from the leader vehicle. The method includes executing a driving maneuver in an autonomous fashion based on the navigation instruction from the leader vehicle.

Abstract: Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by monitoring characteristics of an occupant of a vehicle and determining an emergency status for the occupant based on characteristics of the occupant, transmitting a request for help based on the emergency status indicating the occupant of the vehicle is experiencing an emergency, receiving a “follow me” request from a potential leader vehicle, enabling follower mode such that vehicle is a follower vehicle and the potential leader vehicle is a leader vehicle, establishing a connection with the leader vehicle and receiving navigation instructions from the leader vehicle based on the vehicle being in follower mode, generating driving action commands based on navigation instructions, and executing respective driving action commands in an autonomous fashion based on the vehicle being in follower mode.

Abstract: A method and system for controlling sensor data acquisition using a vehicular communication network is provided. An example method includes establishing an operable connection between a first vehicle and remote vehicles. The first vehicle and the remote vehicles operate based upon a common time base according to a global time signal. The method includes receiving capability data that includes a sensor actuation time slot of each of the remote vehicles indicting a time slot at which the sensors of each of the remote vehicles are actuating. The sensor actuation time slot of each of the remote vehicle is different. The method also includes dividing a clock cycle into a plurality of time slots based on the remote vehicles and controlling, according to the plurality of time slots and the sensor actuation time slot, sensor actuation of a sensor of the first vehicle and the sensors of the remote vehicles.

Abstract: A method and system for controlling sensor data acquisition using a vehicular communication network is provided. An example method includes establishing an operable connection between a first vehicle and remote vehicles. The first vehicle and the remote vehicles operate based upon a common time base according to a global time signal. The method includes receiving capability data that includes a sensor actuation time slot of each of the remote vehicles indicting a time slot at which the sensors of each of the remote vehicles are actuating. The sensor actuation time slot of each of the remote vehicle is different. The method also includes dividing a clock cycle into a plurality of time slots based on the remote vehicles and controlling, according to the plurality of time slots and the sensor actuation time slot, sensor actuation of a sensor of the first vehicle and the sensors of the remote vehicles.

Abstract: A DSRC controller used for controlling a dedicated short-range communication (DSRC) device is provided. The DSRC controller includes a processor communicatively coupled to a memory device. The processor is programmed to store a communication profile of the DSRC device. The communication profile includes rules for transmitting and receiving communications by the DSRC device. The processor is also programmed to receive DSRC zone information describing a DSRC zone, determine a current location of the DSRC device, compare the current location to the DSRC zone information, determine whether the DSRC device is located within a DSRC zone based on the comparison, and if the determination is that the DSRC device is located within the DSRC zone, update the communication profile based on the DSRC zone information.

Abstract: A DSRC controller used for controlling a dedicated short-range communication (DSRC) device is provided. The DSRC controller includes a processor communicatively coupled to a memory device. The processor is programmed to store a communication profile of the DSRC device. The communication profile includes rules for transmitting and receiving communications by the DSRC device. The processor is also programmed to receive DSRC zone information describing a DSRC zone, determine a current location of the DSRC device, compare the current location to the DSRC zone information, determine whether the DSRC device is located within a DSRC zone based on the comparison, and if the determination is that the DSRC device is located within the DSRC zone, update the communication profile based on the DSRC zone information.

Abstract: Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by monitoring characteristics of an occupant of a vehicle and determining an emergency status for the occupant based on characteristics of the occupant, transmitting a request for help based on the emergency status indicating the occupant of the vehicle is experiencing an emergency, receiving a “follow me” request from a potential leader vehicle, enabling follower mode such that vehicle is a follower vehicle and the potential leader vehicle is a leader vehicle, establishing a connection with the leader vehicle and receiving navigation instructions from the leader vehicle based on the vehicle being in follower mode, generating driving action commands based on navigation instructions, and executing respective driving action commands in an autonomous fashion based on the vehicle being in follower mode.

Abstract: Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by monitoring characteristics of an occupant of a vehicle and determining an emergency status for the occupant based on characteristics of the occupant, transmitting a request for help based on the emergency status indicating the occupant of the vehicle is experiencing an emergency, receiving a “follow me” request from a potential leader vehicle, enabling follower mode such that vehicle is a follower vehicle and the potential leader vehicle is a leader vehicle, establishing a connection with the leader vehicle and receiving navigation instructions from the leader vehicle based on the vehicle being in follower mode, generating driving action commands based on navigation instructions, and executing respective driving action commands in an autonomous fashion based on the vehicle being in follower mode.