Abstract: A method for the performance-enhancing driver assistance of a road vehicle driven on a track. The method comprises the steps of defining a dynamic model of the road vehicle, determining the actual position and orientation of the road vehicle, detecting a plurality of space data concerning the structure of the track, detecting a plurality of dynamic data of the vehicle, determining a passing through point of the road vehicle arranged in front of the road vehicle, solving an optimum control problem aimed at optimizing a cost function, taking into account, as boundary conditions, the plurality of environmental data, the actual position and the passing through point, so as to compute a mission optimizing the cost function, and driving the vehicle in an autonomous manner so as to show to the driver the mission optimizing the cost function.

Abstract: Apparatuses, systems, kits, methods and storage medium associated with using different electrical energy source types with an electric vehicle are disclosed herein.

Abstract: A drive system for an electric vehicle and a method for controlling the same. The drive system includes: a front wheel electric motor and a rear wheel electric motor of the same specification; a front wheel reducer whose output shaft is operatively coupled to a front wheel drive axle of the electric vehicle via the front wheel electric motor; and a rear wheel reducer whose output shaft is operatively coupled to a rear wheel drive axle of the electric vehicle via the rear wheel electric motor, wherein the front wheel reducer has a transmission ratio different than that of the rear wheel electric motor.

Abstract: A method of lane detection for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, cause the computing device to perform the following steps comprising: generating a ground truth associated with lane markings expressed in god's view; receiving features from at least one of a hit-map image and a fitted lane marking, wherein the hit-map image includes a classification of pixels that hit a lane marking, and the fitted lane marking includes pixels optimized based on the hit-map image; and training a confidence module based on the features and the ground truth, the confidence module configured to determine on-line whether a fitted lane marking is reasonable, using parameters that express a lane marking in an arc.

Abstract: There is provided a drone system in which a drone and a movable body operate in coordination with each other, the movable body being capable of moving with the drone aboard and allowing the drone to make a takeoff and a landing, the movable body including: a takeoff-landing area on which the drone can be placed and that serves as a takeoff-landing point from and on which the drone takes off and lands; a movement control section capable of moving the movable body together with the drone aboard; and a movable body transmission section that sends information on the movable body, the drone including: a flight control section that causes the drone to fly; and a drone reception section that receives information on the movable body, wherein the drone sends, to the movable body, a position of a takeoff-landing point at a time when the drone takes off.

Abstract: In a drone system in which a drone and a movable body operate in coordination with each other, the drone performing a predetermined operation in an agricultural field, the movable body being capable of moving with the drone aboard and allowing the drone to make a takeoff and a landing, the plan determining section determines a flight plan for the drone and a movement plan for the movable body in accordance with the flight plan, and the instructing section instructs the drone to execute an operation in accordance with the flight plan and instructs the movable body to move or to be on standby in accordance with the movement plan.

Abstract: Techniques for optimizing a scan pattern of a LIDAR system including a bistatic transceiver include receiving first SNR values based on values of a range of the target, where the first SNR values are for a respective scan rate. Techniques further include receiving second SNR values based on values of the range of the target, where the second SNR values are for a respective integration time. Techniques further include receiving a maximum design range of the target at each angle in the angle range. Techniques further include determining, for each angle in the angle range, a maximum scan rate and a minimum integration time. Techniques further include defining a scan pattern of the LIDAR system based on the maximum scan rate and the minimum integration time at each angle and operating the LIDAR system according to the scan pattern.

Abstract: Embodiments described herein provide for enabling a mobile device comprising a GNSS receiver to implement a modified PPP technique that utilizes orbit and clock information of a satellite that is broadcast from the satellite. In particular, embodiments may utilize a positioning engine to perform PPP error mitigation with respect to various error sources (e.g., troposphere, ionosphere, phase windup, etc.). With regard to errors stemming from satellite orbit and satellite clock, embodiments may utilize orbit and clock information from broadcast ephemeris data rather than obtaining precise orbit and clock information (e.g., from a third party provider). Further, embodiments may account for errors in this broadcast information by adjusting the ambiguity dynamic and/or ambiguity estimate term used by the positioning engine. This can enable the positioning engine to determine a solution more accurate than traditional GNSS without resetting.

Abstract: A system and a method are provided for feasibility evaluation of UAV Digital Twin based on Vicon motion capture system is disclosed, which establishes a mission feasibility evaluation model according to flight history data of a target UAV acquired by the UAV Digital Twin system. The mission feasibility evaluation model includes a UAV trajectory prediction module and a mission feasibility determination module. The UAV trajectory prediction module acquires real-time position and attitude information of the target UAV according to the Vicon motion capture system, and predicts target flight trajectory of the target UAV according to the real-time position and attitude information. The mission feasibility determination module compares the position difference between an end point of the target flight trajectory and preset designated mission point to evaluate feasibility of target mission of the target UAV.

Abstract: A production factory unmanned transfer system includes: a vehicle, which connects Vehicle to Everything (V2X) communication with an infrastructure facility in a vehicle production factory and transfers a worker to a set destination in an unmanned manner through autonomous driving; and a road side unit, which is fixed around a road in the production factory to relay the V2X communication and which generates positioning error correction information based on high-precision Real Time Kinematic-Global Navigation Satellite System (RTK-GNSS) based on a fixed absolute coordinate and transmits the generated positioning error correction information to the vehicle. The vehicle includes a vehicle terminal, which controls autonomous driving according to a lane of a precise map based on high-precise positioning information obtained by correcting an error of satellite-based vehicle location information with the positioning error correction information.

Abstract: A driving assist method reduces a possibility of missing an opportunity to correct a host vehicle position set on map data. In the driving assist method using a controller that sets a target inter-vehicular distance from a host vehicle to a preceding vehicle, whether there is a request to execute a correction of a host vehicle position set on electronic map data is determined based on a result of comparing position information on a road sign described on the electronic map data with position information on the road sign acquired by using a camera installed in the host vehicle. If an execution request has not been made, the target inter-vehicular distance is set to a preset first target inter-vehicular distance. If an execution request has been made, the target inter-vehicular distance is set to a second target inter-vehicular distance, which is longer than the first target inter-vehicular distance.

Abstract: Time slot specifying unit reads out facility information of a facility to be inspected (specifically, a base station ID of a base station whose previous inspection day is included in a past predetermined period) from facility information storage unit. Daytime information acquiring unit acquires daytime information at positions at which base stations to be inspected are installed. Time slot specifying unit specifies non-backlight time slots based on the read-out facility information and the acquired daytime information. Operation plan generating unit generates an operation plan of drone in which facilities are shot in the specified non-backlight time slots. Operation plan outputting unit outputs the generated operation plan.

Abstract: In a map data generation apparatus, probe map data is generated for each of data management units corresponding to (i) road sections, (ii) road links, or (iii) meshes into which a map is divided, based on a plurality of probe data collected from a plurality of vehicles. Difference data are obtained by comparing basic map data with the probe map data; the basic map data is updated based on a plurality of difference data, for each of the data management units. A transient data is discriminated from data corresponding to the probe data or the difference data; the transient data is excluded from the data.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive a first time series of positions of a vehicle sensor mounted on a vehicle from at least one calibration sensor spaced from the vehicle, measured while vibrations are applied to the vehicle; receive a second time series of motion of the vehicle sensor based on data from the vehicle sensor measured while the vibrations are applied to the vehicle; fuse the first and second time series; and determine at least one calibration value for an adjustment model based on the fusion of the first and second time series. The adjustment model is a model of motion of the vehicle sensor relative to the vehicle resulting from motion of the vehicle.

Abstract: A method for an unmanned aerial vehicle (UAV) includes: generating a control signal that controls multiple motors of the UAV each configured to drive a corresponding one of multiple propellers. The multiple propellers are configured to be mounted at the multiple motors, respectively. The control signal includes at least one of an idling control signal or a takeoff control signal. The method also includes: controlling the multiple motors to operate based on the control signal; obtaining status information of the UAV when the multiple motors are operating in response to the control signal; and determining whether at least one of the multiple propellers is abnormally mounted according to the status information.

Abstract: An unmanned vehicle (UV) navigation system is provided. The UV navigation system comprises a processor, a communication interface for communicating with a remote station, and a non-transitory memory device storing machine-readable instructions that, when executed by the processor, causes the processor to navigate the UV. The processor is configured to receive data from sensors, camera or data line for UV processor analysis, determine that a link-free trigger event has occurred, and autonomously navigate the UV in response to the trigger event.

Abstract: The present disclosure is directed to method for controlling an autonomous or human-driven vehicle that can include receiving, via a processor a vehicle communication indicative of a traffic flow parameter, and determining, based on the vehicle communication, a driver behavior characteristic, determining, via the processor and based on a historic driver behavior record, a driver performance characteristic, generating, via the processor, a first speed assignment and a lane assignment and associated with the vehicle and causing to transmit a first speed and lane assignment message to the vehicle. The system uses enhanced sensing technology within a connected environment to observe vehicle speeds and other vehicle patterns to ingest real-time, road network patterns of vehicle behavior, manages traffic through simulation, and sends messages to dynamic lane management controls such as signage, V2V communication, etc.

Abstract: Methods and systems are provided for limiting requested wheel torque during startup of a vehicle having an electrified powertrain. In one example, a method may include, responsive to a discharge power currently available being less than or equal to a threshold discharge power, operating the vehicle while requesting the wheel torque at a feedforward torque limit, the feedforward torque limit being based on the discharge power and a threshold vehicle speed. In this way, large shifts in wheel torque may be avoided upon startup of the vehicle, thereby reducing noise, vibration, and harshness at the electrified powertrain.

Abstract: A smart cruise control system includes a controller communicatively connected to a first sensor obtaining front image data and a second sensor obtaining front radar data, wherein the controller is configured to recognize a front vehicle based on the front image data and the front radar data, and in response to the front vehicle being not recognized in the front radar data and the front vehicle being recognized in the front image data, control the vehicle so that the vehicle is not accelerated even if the distance between the vehicle and the front vehicle recognized in the front image data is greater than the preset distance.

Abstract: A method for the dynamic fixation of an occupant wearing a seatbelt on a vehicle seat involves determining a lateral acceleration of the vehicle and a road course ahead of the vehicle. The seatbelt is tightened with a predetermined belt force for a predetermined period of time before entering a bend having a certain curvature.