Abstract: An automated valet parking system, an automated valet parking method, an automated valet parking infrastructure, and a vehicle having an automated valet parking feature each enable an unmanned vehicle to autonomously move to and park in a designated parking spot by communicating with the infrastructure. An unmanned vehicle can autonomously move to a pickup area from a parking spot by communicating with the infrastructure.

Abstract: Systems and methods for identifying physical intelligent moving objects (IMOs); creating, for a first subset of the physical IMOs, digital representations in edge clouds of a distributed cloud computing environment, each digital representation representative of a physical IMO of the first subset of the physical IMOs; generating a cooperative network computing (CNC) platform that includes the digital representations of the first subset of the physical IMOs, each digital representation functioning as a CNC entity in the CNC platform for the corresponding physical IMO; identifying a CNC task of a first physical IMO of the plurality of physical IMOs; and performing, by a first digital representation of the representations that corresponds to the first physical IMO, the CNC task in the CNC platform, including accessing data associated with a second digital representation of the digital representations in the CNC platform to perform the CNC task at the first digital representation.

Abstract: A method for setting a tuning parameter for an Automated Driving System (ADS) of a vehicle is disclosed. A corresponding non-transitory computer-readable storage medium, vehicle control device and a vehicle comprising such a control device are also disclosed. The method comprises receiving environmental data from a perception system of the vehicle, said environmental data comprising a plurality of environmental parameters, determining, by means of a self-learning model, an environmental scenario based on the received environmental data; setting the tuning parameter for the ADS based on the self-learning model and the determined environmental scenario, the tuning parameter defining a dynamic parameter of the ADS, receiving at least one signal representative of a vehicle user feedback on the set tuning parameter, and updating the self-learning model for the set tuning parameter for the identified environmental scenario based on the received vehicle user feedback.

Abstract: A multi-disk brake system comprises an electrical generator disposed therein. The electrical generator is configured to convert mechanical energy to electrical energy. The mechanical energy may be generated during a braking event of the multi-disk brake system. The electric generator may power various electrical components on the aircraft or store the electrical energy in a capacitor bank. The electric generator may also act as a motor and/or power a landing gear in a motor configuration.

Abstract: A control system of a vehicle includes: a target speed module configured to, using a parametric driver model and based on first driver parameters, second driver parameters, and vehicle parameters, determine a target vehicle speed trajectory for a future predetermined period; a driver parameters module configured to determine the first driver parameters based on conditions within a predetermined distance in front of the vehicle; and a control module configured to adjust at least one actuator of the vehicle based on the target vehicle speed trajectory and a present vehicle speed.

Abstract: A device is provided for operating a vehicle which can be driven in an at least partly automated manner, having a steering wheel which can be operated by a driver and which is also designed to carry out a substantially manual driving mode for controlling at least the lateral control of the vehicle. The device has at least one first operating mode which differs from a substantially manual operating mode in that one or more operations initiated by the driver in a first time interval at the steering wheel are not carried out in the first time interval, but instead are carried out in a second time interval in accordance with a predetermined condition.

Abstract: An example operation includes one or more of initially determining, via one or more sensors on a transport, that the transport is approaching a one-way road in a wrong direction based on a slowing down of the transport and a movement of the transport toward the one-way road, notifying, via the one or more sensors, one or more occupants of the transport about the approaching, and in response to the transport continuing to approach in the wrong direction, slowing the transport, by a computer associated with the transport, to not permit entry into the one-way road.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to detect a moving object in video stream data based on determining an eccentricity map. The instructions can further include instructions to determine a magnitude and direction of motion of the moving object, transform the magnitude and direction to global coordinates and operate a vehicle based on the transformed magnitude and direction.

Abstract: An advanced driver assistance system configured to implement one or more automotive V2V applications designed to assist a driver in driving a Host Motor-Vehicle. The advanced driver assistance system is configured to be connectable to an automotive on-board communication network to communicate with automotive on-board systems to implement one or different automotive functionalities aimed at assisting the driver in driving the Host Motor-Vehicle, controlling the Host Motor-Vehicle, and informing the driver of the Host Motor-Vehicle of the presence of Relevant Motor-Vehicles deemed to be relevant to the driving safety of the Host Motor-Vehicle.

Abstract: A computer for a roadside infrastructure element includes a processor and a memory. The memory stores instructions executable by the processor to receive communications from a plurality of vehicles; receive sensor data about an area that includes the roadside infrastructure element; based on the sensor data, determine whether the plurality of vehicles includes a priority vehicle or a spoofing vehicle; and specify to the plurality of vehicles a first action upon determining that the plurality of vehicles includes the priority vehicle, and a second action upon determining that the plurality of vehicles includes a spoofing vehicle.

Abstract: The present invention provides a large-scale high-speed rotary equipment measuring and intelligent learning assembly method and device based on vector minimization geometry center, mass center, the center of gravity and the center of inertia, belonging to the technical field of mechanical assembly. The method includes the steps of establishing a four-parameter circular profile measuring model for a single stage of rotor, simplifying the established four-parameter circular profile measuring model for the single stage of rotor, and establishing a four-target optimization model of the geometry center, mass center, the center of gravity and the center of inertia of multiple stages of rotors based on the angular orientation mounting position of each stage of rotor.

Abstract: A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Abstract: A positioning method comprises acquiring positioning information of a 5G base station from a satellite, obtaining calibration information based on the positioning information, and broadcasting outwards the calibration information; acquiring initial positioning information of a user terminal from the satellite; accessing a nearest 5G base station in real time, monitoring and acquiring calibration information broadcasted by the nearest 5G base station; and calibrating the initial positioning information acquired in the initial positioning step according to the calibration information acquired in the monitoring step to obtain positioning result information. As described above, the positioning of centimeter level precision can be realized by utilizing the 5G base station, and there is no need to additionally establish a CORS base station and a data center, thereby the cost of precise positioning can be reduced.

Abstract: A bank angle of a vehicle can be accurately calculated using yaw axis data and roll axis data, and based on the calculated bank angle, vehicle illumination optics can be controlled to maintain a pattern of distributed light from the illumination optics to be generally horizontal. The calculated bank angle may be zeroed when the yaw axis data equals zero. The improved pattern of distributed light from the illumination optics illuminates a more natural field of view for the vehicle driver during a bank.

Abstract: A spatial monitoring system for a vehicle includes a LiDAR sensor, sensors arranged to monitor ambient environmental states, sensors arranged to monitor vehicle operating conditions, and a controller. The controller includes an instruction set that is executable to monitor the ambient environmental states and the vehicle operating conditions. The LiDAR sensor captures a point cloud, and the instruction set is executable to determine point cloud metrics. Desired control parameters for the LiDAR sensor are determined based upon the ambient environmental conditions, the vehicle operating conditions, and the point cloud metrics, and the LiDAR sensor is controlled based upon the desired control parameters. The LiDAR sensor is controlled to capture an image of a field-of-view proximal to the vehicle based upon the desired control parameters.

Abstract: The present application discloses an abnormal data collecting method for automatic parking, an apparatus, a storage medium and a product, and relates to automatic driving technology and automatic parking technology in computer technology. A specific implementation i: in response to monitoring that a target vehicle generates a fault code during an automatic parking process, matching the fault code with at least one pre-configured fault code to be collected; in response to determining that the fault code matches the fault code to be collected, determining a data collecting strategy corresponding to the fault code to be collected; and performing a data collecting operation on abnormal data corresponding to the fault code according to the data collecting strategy.

Abstract: A system and a method for automatically configuring a road sensor unit. Embodiments of the invention include detecting, by the road sensor unit, an identification unit of a road socket unit upon insertion of the road sensor unit into the road socket unit, reading, by the road sensor unit, a unique designation of the identification unit of the road socket unit, transmitting, by the road sensor unit, the unique designation and a unique sensor identification of the road sensor unit to a remote server, receiving, by the road sensor unit from the remote server, unique parameters, wherein the unique parameters are based on the unique designation of the identification unit, configuring, by the road sensor unit, the road sensor unit to operate based on the unique parameter and operating said road sensor unit with the configuration.

Abstract: A method, comprising: receiving position data from a mobile device; incrementing a counter variable, said counter variable associated with a predefined geographic area that includes a position of the position data, and initializing a time variable, said time variable set to a predefined value and decremented continuously; and decrementing said counter variable in response to expiration of said time variable.

Abstract: A vehicular device includes: an eye opening degree determiner that determines a driver eye opening degree; a line-of-sight movement determiner that determines frequency of a driver line-of-sight movement; an operation determiner that determines a driver operation state for a driving operation instrument; a deviation determiner that determines a possibility that a driving state of a subject vehicle driver deviates from a safe driving state; a vehicle inside notification controller that performs a notification operation for a vehicle inside; and a vehicle outside notification controller that performs a notification operation for a vehicle outside.

Abstract: A method for determining driving strategy of a vehicle includes obtaining localization information of the vehicle, a driving route of the vehicle, and a current driving velocity of the vehicle. The method further includes detecting and interpreting a current status of a traffic light. The method further includes recognizing a duration of the current status of the traffic light. The method further includes detecting a relevant stop line. The method further includes obtaining a distance between the stop line and the vehicle. The method further includes determining whether to change the current driving velocity according to the current status of the traffic light, the duration of the current status of the traffic light, the distance between the traffic stop line and the vehicle, and the current driving velocity. A data processing device for determining driving strategy of a vehicle is also provided.