Abstract: A calibration pipeline for 6DoF alignment parameters for an autonomous vehicle includes an automated driving controller instructed to receive inertial measurement unit (IMU) poses and final radar poses and determine smoothened IMU poses from the IMU poses and smoothened final radar poses from the final radar poses. The automated driving controller aligns the smoothened IMU poses and the smoothened final radar poses with one another to create a plurality of radar-IMU A, B relative pose pairs. The automated riving controller determines a solution yielding a threshold number of inliers of further filtered radar-IMU A, B relative pose pairs, randomly samples the further filtered radar-IMU A, B relative pose pairs with replacements several times to determine a stream of filtered radar-IMU A, B relative pose pairs, and solves for a solution X for the stream of filtered radar-IMU A, B relative pose pairs.

Abstract: The present disclosure relates to methods of enhancing a navigation solution about a device and a platform, wherein the mobility of the device may be constrained or unconstrained within the platform, and wherein the navigation solution is provided even in the absence of normal navigational information updates (such as, for example, GNSS). More specifically, the present method comprises utilizing measurements from sensors (e.g. accelerometers, gyroscopes, magnetometers etc.) within the device to calculate and resolve the attitude of the device and the platform, and the attitude misalignment between the device and the platform.

Abstract: A method is presented for determining a reliability of a low-definition map to make the activation of at least one driving assistance system of an autonomous vehicle reliable when the autonomous vehicle is traveling on a road and wherein the vehicle comprises a navigation system and a perception system, the navigation system comprising the mapping and providing mapped data, the perception system providing measured data of the vehicle and/or the external environment of the vehicle, the method comprising the steps of: receiving mapped data; receiving measured data; determining a path of the road; calculating a road correlation value; calculating a sign correlation value; determining a reliability indicator, reliable or unreliable.

Abstract: A driving assistance control section of a vehicle control apparatus has an operation state of a driver's vehicle transition from a stop state to a start-stand-by state keeping a second assistance state, if an accelerating operation larger than a predetermined first threshold acceleration is performed and there is an ahead-located vehicle, and has the driving assistance state transition from the second assistance state to a first assistance state and has the operation state transition from the stop state to the start-stand-by state if an accelerating operation larger than a predetermined second threshold acceleration is performed over a longer time than a predetermined threshold duration and there is an ahead-located vehicle, if follow-up running control is being performed in the second assistance state in which it is not necessary for a driver to hold a steering wheel to continue to have a driving assistance function performed.

Abstract: In a target track generation apparatus, a subject vehicle reference preceding vehicle position calculator calculates a point group of subject vehicle reference preceding vehicle positions representing a history of a relative position of a preceding vehicle in a coordinate system using a current position of a subject vehicle as a reference. A target track generator generates a target track of the subject vehicle, based on the point group of the subject vehicle reference preceding vehicle positions. A correction target track generator generates a correction target track obtained by correcting the target track, based on the point group of the subject vehicle reference preceding vehicle positions or the target track, when it is determined that correction of the target track is necessary.

Abstract: Embodiments of the present disclosure set forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, generating, based on the sensor data, a set of lane change data values associated with positions of at least two vehicles relative to a first lane position in the environment, determining, based on the set of lane change data values, a collision risk value associated with the at least two vehicles attempting to occupy the first lane position, and generating, based on the collision risk value, an output signal to a first vehicle included in the at least two vehicles.

Abstract: Hybrid electric propulsion systems includes a combustion engine and an electric motor. The hybrid electric propulsion systems may include or utilize a non-transitory computer-readable medium comprising computer-executable instructions, which when executed by a processor associated with the hybrid electric propulsion system, cause the processor to perform a method that includes determining an occurrence of a thrust asymmetry in the hybrid electric propulsion system, and controlling the electric motor to decrease an efficiency of the electric motor for a transient time period sufficient to reduce a torque output of the combustion engine to match an electrical load on the combustion engine.

Abstract: Techniques for utilizing microphone or audio data to detect and responding to low velocity impacts to a system such as an autonomous vehicle. In some cases, the system may be equipped with a plurality of microphones that may be used to detect impacts that fail to register on the data captured by the vehicle's inertial measurement units and may go undetected by the vehicle's perception system and sensors. In one specific example, the perception system of the autonomous vehicle may identify a period of time in which a potential low velocity impact may occur. The autonomous vehicle may then utilize the microphone or audio data associated with the period of time to determine if an impact occurred.

Abstract: Systems, methods, and apparatus related to dynamically adjusting sensing and/or processing resources of a vehicle. In one approach, sensor data is collected by sensing devices of the vehicle. A controller of the vehicle uses the sensor data to control one or more functions of the vehicle. The controller evaluates the sensor data to determine a context of operation (e.g., weather, lighting, and/or traffic) for the vehicle. Based on the context of operation, the controller adjusts the operation of one or more of the sensing or processing devices in real-time during operation of the vehicle. In one example, the adjustment reduces power consumption by the vehicle.

Abstract: A vehicular control system determines a planned path of travel for a vehicle along a traffic lane in which the vehicle is traveling on a road. The system determines a respective target speed for waypoints along the planned path that represents a speed the vehicle should travel when passing through the respective waypoint. The system determines a speed profile for the vehicle to travel at as the vehicle travels along the planned path, with at least two different speeds being based on a difference in target speeds of at least two consecutive respective waypoints of the plurality of waypoints. The system determines an acceleration profile for the vehicle to follow as it changes from one speed to another speed of the speed profile. The system controls the vehicle to maneuver the vehicle along the planned path in accordance with the determined speed and acceleration profiles.

Abstract: A first network device includes a transceiver, a memory and a control module. The transceiver receives an integrated model from a second network device that is separate from the first network device. The memory stores the integrated model and diagnostic trouble code data, most probable cause data, and least probable cause data, which have corresponding cause of issue indications for an issue of a vehicle. The control module while executing the integrated model: compares the cause of issue indications to determine whether the cause of issue indications are consistent such that a same cause of issue is indicated; in response to the cause of issue indications being consistent, displays the same cause of issue, and in response to the cause of issue indications being inconsistent and based on a set of conditions, displays a portion of health related information while refraining from displaying another portion of the health related information.

Abstract: A vehicle driving system that controls switching between automatic driving by a vehicle and manual driving by a driver of the vehicle includes a temperature sensor configured to monitor a temperature of an automatic driving ECU which controls the automatic driving; and a microcontroller configured to: (i) set a threshold temperature based on an estimated gradient of increase in the temperature of the automatic driving ECU, the estimated gradient of increase being estimated based on a drive state of an equipment installed on the vehicle, and (ii) in a case where the temperature of the automatic driving ECU that is sensed by the temperature sensor becomes equal to or greater than the threshold temperature, perform an operation for prompting the driver to switch to the manual driving during the automatic driving.

Abstract: A method for controlling emergency stop of an autonomous vehicle is provided. The method includes: controlling emergency stop of an autonomous vehicle capable of recognizing a stop request from an emergency vehicle, determining whether a current situation is an emergency situation or a general situation, and performing a procedure corresponding to each situation to stop the autonomous vehicle based on each situation.

Abstract: The present disclosure relates to methods of enhancing a navigation solution about a device and a platform, wherein the mobility of the device may be constrained or unconstrained within the platform, and wherein the navigation solution is provided even in the absence of normal navigational information updates (such as, for example, GNSS). More specifically, the present method comprises utilizing measurements from sensors (e.g. accelerometers, gyroscopes, magnetometers etc.) within the device to calculate and resolve the attitude of the device and the platform, and the attitude misalignment between the device and the platform.

Abstract: The present disclosure aims to implement UAV (unmanned aerial vehicle) logistics operation and air traffic control in flyable airspace technically through a UAV task planning system, which depends on blockchain technology to carry out UAV air traffic surveillance on flight segments in a predetermined barrier-free airway and optimize air traffic according to a safe separation distance for fewest UAV operators, air traffic controllers, communications links and airborne loads.

Abstract: Systems and methods for distracted driving detection are described. A method includes receiving proximate vehicle data about a proximate vehicle proximate to the host vehicle. The method also includes estimating one or more baselines for a predetermined future time for the proximate vehicle from the proximate vehicle data. The method further includes comparing current kinematic data of the proximate vehicle data for the predetermined future time to the one or more baselines. The method includes generating distraction flags associated with the proximate vehicle based on the comparison. The method also includes controlling one or more vehicle systems of the host vehicle based on the generated distraction flags.

Abstract: A control system (100) for an emergency braking system (200) using at least one transmitter/receiver sensor (210) comprising: means for causing automatic transition, from a first state (310) in which the emergency braking system (200) is inactive to a second state (320) in which the emergency braking system (200) is active, in dependence upon satisfaction of a first condition (412); and means for causing automatic transition from the second state (320) to the first state (310) in dependence upon satisfaction of a second condition (421) different to the first condition (412) wherein transition from the second state (320) to the first state (310) does not occur in dependence upon the first condition (412) no longer being satisfied, and/or transition from the first state (320) to the second state (310) does not occur in dependence upon the second condition (421) no longer being satisfied.

Abstract: A method and a traffic control entity (100) for controlling a group of vehicles (104) capable of autonomous driving without requiring a driver, to allow an emergency vehicle (102) to pass the group of vehicles (104) which are travelling concurrently in multiple lanes on a road. When detecting that the emergency vehicle (102) is approaching the group of vehicles (104) e.g. from behind, the vehicles in the group (104) are identified based on information (108) about current position and movement of the vehicles (104). The traffic control entity (100) then issues a command (106) instructing the identified vehicles to adjust their lateral positions relative the lanes to create a passage along the group of vehicles (104). Thereby, the emergency vehicle (102) is able to move through the passage without having to slow down significantly.

Abstract: Embodiments are provided that include maintaining a map of a plurality of markers in an environment. The map includes a last detection time of each marker of the plurality of markers. The embodiments also include receiving a set of detected markers from a robotic device that is configured to localize in the environment using the plurality of markers. The embodiments further include updating, in the map, the last detection time of each marker which has a mapped position that corresponds to a detected position of a detected marker in the set of detected markers. The embodiments additionally include identifying, from the plurality of markers in the map, a marker having a last detection time older than a threshold amount of time. The embodiments still further include initiating an action related to the identified marker.

Abstract: A vehicular hazard mitigation system includes one or more processors and a memory communicably coupled to the processors. The memory may store a vehicular hazard mitigation module including computer-readable instructions that when executed by the processors cause the processors to determine a base vehicle currently driving in an enhanced response driving mode. After determining the base vehicle, at least one alert zone of the base vehicle is determined. A determination is then made as to whether at least one other vehicle is currently in the at least one alert zone of the base vehicle. If at least one other vehicle is currently in the at least one alert zone of the base vehicle, the vehicular hazard mitigation module may autonomously control operation of the base vehicle to shift the driving mode of the base vehicle from the enhanced response driving mode to a non-enhanced response driving mode.