Abstract: A vehicle including: a communication section configured to receive operation information to operate a travel device from an external operation device; a memory; and a processor coupled to the memory, the processor being configured to: acquire peripheral information peripheral to a vehicle body from a peripheral information detection section, generate a travel plan based on the peripheral information, and control the travel device so as to perform autonomous driving in which travel is based on the generated travel plan, and perform remote driving in which travel is based on the operation information received by the communication section; and the vehicle further comprising a presentation device configured to present, at a vehicle exterior, identifying information received by the communication section, the identifying information relating to a user making use of transportation by the autonomous driving or the remote driving.

Abstract: An agriculture support system includes a data obtaining device to obtain at least one type of data among a plurality of types of data relating to planting of crops, a mesh setting device to allocate, as divided data, the data obtained by the data obtaining device to each of areas of an agricultural field in which the crops are planted, a first map display to relate, to a location of the agricultural field, the divided data allocated to each of the areas by the mesh setting device and to display the divided data as a first field map, a spreading setting device to set a spreading amount of spread substance in each of the areas based on the divided data of each of the areas, and a second map display to relate, to the location of the agricultural field, the spreading amount and to display the spreading amount.

Abstract: An aerial vehicle includes a hull containing the main processor, energy storage, support components such as sensors, wireless communication, and landing gear. Attached to the hull are at least three thrust or propulsion units each with two degrees of freedom from the hull allowing them to orient independently in any direction and apply thrust independently from the hull or any other thrust or propulsion unit. In some embodiments, a mount for auxiliary attachments is included or the auxiliary system is built into the hull. Components like the energy storage, auxiliary attachments, and/or propulsion units may also be replaceable as required.

Abstract: A computer-implemented method of dynamically generating a charger map for electric vehicle (EV) charger locations. The method includes providing one or more parameters for a plurality of target areas to a machine learning (ML) model. The ML model is iteratively trained to identify relationships between the parameters using historical data corresponding to the plurality of target areas. One or more target parameters for a user-specific target area are received along with one or more user-specific weights representing one or more prioritized charging features associated with the user-specific target area. A charger map is generated via the trained ML model for the user-specific target area including one or more locations for EV chargers within the user-specific target area. The charger map is optimized relative to the one or more prioritized charging features.

Abstract: Provided are a lane separation line detection correcting device/method and an automatic driving system for stabilizing the behavior of a vehicle by correcting overestimated curvature information resulting from an erroneous detection of a curvature of a lane separation line. A travel speed detecting circuit detects, for example, a target travel speed as vehicle sensor information. A maximum curvature estimating circuit estimates, based on the target travel speed, a maximum curvature of a road along which an own vehicle is traveling. A curvature correcting circuit corrects a curvature of a lane separation line input thereto based on the maximum curvature. A control unit controls steering of the own vehicle based on the lane separation line having a corrected curvature. As a result, vehicle steering can be automatically controlled so as to prevent the own vehicle while traveling from departing from a driving lane.

Abstract: Methods and system for vehicle control. The methods and systems determining actuator commands data based on a vehicle stability and motion control function. The vehicle stability and motion control function having planned trajectory data, current vehicle position data and current vehicle heading data as inputs, having the actuator commands data as an output and utilizing a model predicting vehicle motion including predicting vehicle heading data and predicting vehicle position data. The actuator commands data includes steering and propulsion commands. The actuator commands data includes differential braking commands for each brake of the vehicle to correct for any differential between the planned vehicle heading and the current vehicle heading data or the predicted vehicle heading data. The methods and systems output the actuator commands data to the actuator system.

Abstract: A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, classifying and tracking objects and/or terrain characteristics from on-board sensors that capture images in front and around the autonomous machinery as it performs agricultural or other activities. The framework generates commands for navigational control of the autonomous machinery in response to perceived objects and terrain impacting safe operation. The framework processes image data and range data in multiple fields of view around the autonomous equipment to discern objects and terrain, and applies artificial intelligence techniques in one or more neural networks to accurately interpret this data for enabling such safe operation.

Abstract: Route information data records are received from a navigation system indicating road elements and maneuvers between a starting point and a destination point. An estimated time of arrival is established using the route information data records. A personalized correction value based on the road elements, maneuvers, and a driver profile is determined. A personalized time of arrival is calculated based on the estimated time of arrival value and the personalized correction value.

Abstract: A method for risk based processing, the method may include detecting, based on first sensed information sensed at a first period, a suspected risk within an environment of a vehicle; selecting, from reference information, a situation related subset of the reference information, wherein the situation related subset of the reference information is related to the situation; selecting, from reference information, a suspected risk related subset reference information, wherein the potential risk related subset of the reference information is related to the potential risk; and determining whether the suspected risk is an actual risk, based at least on part on the suspected risk related subset reference information.

Abstract: Systems, methods, and apparatuses described herein are directed to performing segmentation on voxels representing three-dimensional data to identify static and dynamic objects. LIDAR data may be captured by a perception system for an autonomous vehicle and represented in a voxel space. Operations may include determining a drivable surface by parsing individual voxels to determine an orientation of a surface normal of a planar approximation of the voxelized data relative to a reference direction. Clustering techniques can be used to grow a ground plane including a plurality of locally flat voxels. Ground plane data can be set aside from the voxel space, and the remaining voxels can be clustered to determine objects. Voxel data can be analyzed over time to determine dynamic objects. Segmentation information associated with ground voxels, static object, and dynamic objects can be provided to a tracker and/or planner in conjunction with operating the autonomous vehicle.

Abstract: A system includes a plurality of ride vehicle modules, where each of the plurality of ride vehicle modules includes an interlock system configured to perform linking operations to join to other ride vehicle modules to form a cluster and delinking operations to separate from the other ride vehicle modules throughout a ride, control circuitry configured to control the interlock system and movement of the respective ride vehicle module independently or as a part of the cluster, and communication circuitry configured to wirelessly communicate with the other ride vehicle modules internal and/or external to the cluster. The cluster may change sizes throughout the ride by performing linking and delinking operations as desired. A method for changing the size of clusters of ride vehicle modules throughout a ride is also disclosed.

Abstract: A method of controlling driving of a vehicle using an in-wheel system includes: calculating a time to collision (TTC) by dividing a distance between the vehicle and an obstacle located in front of the vehicle by relative velocity; determining whether the vehicle enters a braking avoidance section, based on the calculated TTC; and generating, by a motor mounted in each wheel, braking force of a brake by an amount of shortage of braking force of the brake compared with a demanded braking force if the vehicle enters the braking avoidance section.

Abstract: Boundary information for a three-dimensional (3D) flying space is obtained. An input associated with steering a vehicle is received from an input device and location information associated with the vehicle is received from a location sensor. A control signal for the vehicle is generated based at least in part on the boundary information, the input, and the location information. In the event the input would cause the vehicle to cross the boundary of the 3D flying space if obeyed, the control signal for the vehicle is generated so that the vehicle is prevented from crossing the boundary of the 3D flying space. In response to receiving an indication associated with the vehicle landing, the boundary information is modified so that the 3D flying space includes a landing pathway.

Abstract: A system and a method for updating and sharing crossroad dynamic map data are disclosed.

Abstract: Disclosed herein are a method and apparatus for automated following behind a lead vehicle. The lead vehicle navigates a path from a starting point to a destination. The lead vehicle and the following vehicle are connected via V2V communication, allowing one or more following vehicles to detect the path taken by the lead vehicle. A computerized control system on the following vehicle (a Follow-the-Leader, or FTL, system) allows the following vehicle to mimic the behavior of the lead vehicle, with the FTL system controlling steering to guide the following vehicle along the path previously navigated by the lead vehicle. In some embodiments, the lead vehicle and following vehicle may both use Global Navigation Satellite System (GNSS) position coordinates. In some embodiments, the following vehicle may also have a system of sensors to maintain a gap between the following and lead vehicles.

Abstract: In one embodiment, an autonomous driving system of an ADV perceives a driving environment surrounding the ADV based on sensor data obtained from various sensors, including detecting one or more lanes and at least a moving obstacle or moving object. For each of the lanes identified, an NN lane feature encoder is applied to the lane information of the lane to extract a set of lane features. For a given moving obstacle, an NN obstacle feature encoder is applied to the obstacle information of the obstacle to extract a set of obstacle features. Thereafter, a lane selection predictive model is applied to the lane features of each lane and the obstacle features of the moving obstacle to predict which of the lanes the moving obstacle intends to select.

Abstract: The invention discloses a preferable short arc initial orbit determining method based on Gauss solution cluster, and belongs to the astrodynamics field, including: grouping the observation data, using Gauss method to obtain the target state vector at the corresponding time point for each group of data, forming a solution set of preliminary estimation; dividing the solution set of preliminary estimation into a position component vector solution set and a velocity component vector solution set for clustering to obtain a position component vector solution cluster and a velocity component vector solution cluster; based on the position component vector solution cluster and the velocity component vector solution cluster, generating a two-dimensional trajectory solution set; evaluating each of the two-dimensional trajectories by using a trajectory optimal method, calculating the number of root of orbits corresponding to the optimal two-dimensional trajectory, thereby completing determination of initial orbit.

Abstract: A method for adjusting brake pressures at pneumatically actuated wheel brakes of a vehicle includes receiving an external braking demand. The method further includes, in response to the received external braking demand, performing, during each of a plurality of computation cycles: (i) ascertaining control signals for pressure control valves of the pneumatically actuated wheel brakes of the vehicle, (ii) continuously ascertaining a differential slip value, wherein the differential slip value is a difference between a slip of two axles of the vehicle and is determined by measuring signals supplied by speed sensors of wheels of the vehicle, (iii) evaluating the differential slip value with respect to a predefined or adjustable setpoint differential slip value, (iv) based on the evaluation of the differential slip value, adapting the ascertained control signals, and (v) releasing the adapted control signals to the pressure control valves.

Abstract: A map matching method for autonomous driving includes extracting a first statistical map from 3D points contained in 3D map data; extracting a second statistical map from 3D points of surroundings which are obtained by a detection sensor simultaneously or after the previous extracting of the statistical map; dividing the second statistical map into a vertical-object part and a horizontal-object part; and performing map matching using the horizontal-object part and/or the vertical-object part and the first statistical map.

Abstract: A method is disclosed for detecting a hazardous situation in road traffic, wherein visible surroundings of a motor vehicle are scanned by way of at least one surroundings monitoring sensor for the presence of a trigger. Upon detection of the trigger, data regarding the surroundings of the motor vehicle is collected by the at least one surroundings monitoring sensor in a trigger-specific radius around the trigger. Pieces of information based on the collected data are transmitted via a communication device to at least one receiver that is independent of the motor vehicle.