Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices for operating an autonomous vehicle are provided. For example, the disclosed technology can include receiving state data that includes information associated with states of an autonomous vehicle and an environment external to the autonomous vehicle. Responsive to the state data satisfying vehicle stoppage criteria, vehicle stoppage conditions can be determined to have occurred. A severity level of the vehicle stoppage conditions can be selected from a plurality of available severity levels respectively associated with a plurality of different sets of constraints. A motion plan can be generated based on the state data. The motion plan can include information associated with locations for the autonomous vehicle to traverse at time intervals corresponding to the locations. Further, the locations can include a current location of the autonomous vehicle and a destination location at which the autonomous vehicle stops traveling.

Abstract: A device for a hydraulic braking system of a vehicle. The device includes a processing unit, which is programmed to determine at least one brake characteristic value of the hydraulic braking system, the processing unit being programmed to determine the at least one brake characteristic value as a vehicle axle-specific brake characteristic value, which in each case corresponds to a ratio between a brake pressure in all wheel brake cylinders assigned to a shared vehicle axle of the vehicle and a vehicle axle braking torque exerted on the shared vehicle axle with the aid of the wheel brake cylinders. A method for determining at least one brake characteristic value of a hydraulic braking system of a vehicle, and a method for decelerating a vehicle with a hydraulic braking system and an electric motor usable as a generator, are also described.

Abstract: Systems, methods, and other embodiments described herein relate to determining driving behaviors for controlling a vehicle. In one embodiment, a method includes generating, using textual descriptions in combination with driving log snippets, a joint feature space that represents a coordinated mapping between the textual descriptions and the driving log snippets. The method includes training a policy network to generate identified behaviors from the driving behaviors according to a correspondence between an observed context that is mapped onto the joint feature space and the driving behaviors defined in the joint feature space resulting from at least the textual descriptions. The method includes providing a behavior cloning model including at least an encoder, the joint feature space, and the policy network to generate control behaviors from the driving behaviors defined in the joint feature space according to acquired observations of a surrounding environment of the vehicle.

Abstract: A method of calculation a vehicle load comprising calculating a first vehicle load value based at least on air pressures in air springs and height data of suspension of a vehicle axle, determining a second vehicle load value based on a change of track width of the vehicle axle, and calculating the vehicle load based on the first vehicle load value and the second vehicle load value.

Abstract: An autonomous vehicle and a system and method for operating the autonomous vehicle. The system includes a control system and a cognitive system. The control system performs a driving action at the autonomous vehicle. The cognitive system generates the driving action using an evaluation model. The evaluation model is generated by operating the cognitive system in response to a training set of data to generate a planned action for operating the autonomous vehicle by the cognitive system, evaluating the planned action to obtain a system performance grade, and updating the cognitive system based on a comparison of the system performance grade to a human-based performance grade.

Abstract: Technologies and techniques for automatically preparing and/or executing a possible lane change with an ego vehicle traveling in moving traffic from a first lane to a second lane of a multi-lane roadway by means of a driver assistance system and to a driver assistance system. Gaps are detected between two vehicles, and the relative positions and movements of the gaps relative to the ego vehicle will facilitate a potential lane change of the ego vehicle. The driver assistance system adjusts the following distance and/or following speed of the ego vehicle relative to the vehicle ahead in such a way that changing a lane and merging into a gap of an adjacent lane is possible by means of a transverse guidance of the ego vehicle.

Abstract: An unmanned ground vehicle (UGV) includes one or more motors configured to drive one or more wheels of the UGV, a memory storing instructions, and a processor coupled to the one or more motors and the memory. The processor is configured to execute the instructions to cause the UGV to determine location information of a movable target; calculate a direction and a speed for the unmanned ground vehicle based on the determined location information; and drive the one or more motors to move the unmanned ground vehicle in the calculated direction at the calculated speed to follow the movable target when the movable target moves.

Abstract: A method for synchronizing signals of a plurality of participants. A relationship between the signals is given by a physical relation. The signals are each filtered with a first filter in order to determine a shift between the signals. The determined shift is a measure of the phase shift between the signals. The shift is subsequently eliminated by filtering the signals respectively with a second filter.

Abstract: A method for operating a motor vehicle including an actuating element which is, in particular steplessly, displaceable between a first end position and a second end position. An instantaneous position of the actuating element is monitored. A deceleration torque being predefined for the motor vehicle when the instantaneous position is in a deceleration range situated between the first end position and a predefinable change position, and an acceleration torque being predefined for the motor vehicle when the instantaneous position is in an acceleration range situated between the second end position and the change position. A monitoring is carried out for the occurrence of at least one disturbance variable which influences an actual deceleration of the motor vehicle effectuated by the deceleration torque, the deceleration torque being changed as a function of a detected disturbance variable.

Abstract: A system for sensing a position of a first member relative to a second member based on a radio frequency characteristic of a bias member is disclosed. The bias member may be configured to bias the second member relative to the first member. Radio frequency circuitry may be configured to apply a radio frequency signal to the bias member and provide one or more signals indicative of a position of the first member relative to the second member based on a radio frequency characteristic of the bias member.

Abstract: A vehicle may determine that erratic vehicle behavior has been sensed, based on comparison of a sensed vehicle behavioral characteristic at a given location compared to a predefined expected value of the characteristic. The vehicle may further determine whether an environmental anomaly has been detected in association with the given location and classify the sensed erratic behavior based on whether the environmental anomaly was detected. Responsive to classifying the behavior as erratic based on determining no environmental anomaly was detected, the vehicle may report the erratic behavior to a remote server, along with the given location. The remote server may receive a plurality of such reports for a given location and update a classification of the behavior based on data indicated in the plurality of reports.

Abstract: Predictive maintenance and diagnostics for an electronic module of an autonomous vehicle using modular condition monitoring is described herein. A computing system receives a signal from a data logger which monitors a condition of the electronic module of the autonomous vehicle, wherein the signal is indicative of damage accumulation information thereof. The computing system identifies a type of the electronic module and a damage accumulation threshold for the type of the electronic module to generate a predicted maintenance schedule for the electronic module of the autonomous vehicle. The damage accumulation information can be stored in a data store to define the damage accumulation threshold for the type of the electronic module.

Abstract: The controller of the electric vehicle is configured to control the torque of the electric motor using the MT vehicle model based on the operation amount of the accelerator pedal, the operation amount of the pseudo-clutch pedal, and the shift position of the pseudo-shifter. Further, the controller is configured to execute the stall production process for changing the engine output torque used for calculation of the driving wheel torque to zero when the calculated virtual engine speed using the MT vehicle model becomes lower than the prescribed stall engine speed.

Abstract: The present disclosure relates to system that includes a database including data associated with one or more building features of a building. The system includes a processor of a computing device. The processor is configured to determine an absolute position of the computing device within the building. The processor is configured to identify at least one of the building features located within a threshold distance of the absolute position of the computing device based on a query of the database. Additionally, the processor is configured to generate an alert configured to cause the computing device to display information associated with the at least one of the building features or output an audible signal associated with the at least one of the building features.

Abstract: A camera-based localization system is provided. The camera-based localization system may assist an unmanned vehicle to continue its operation in a GPS-denied environment with minimal increase in vehicular cost and payload. In one aspect, a method, a computer-readable medium, and an apparatus for localization via visual inertial odometry are provided. The apparatus may construct an optical flow based on feature points across a first video frame and a second video frame captured by a camera of the apparatus. The apparatus may refine the angular velocity and the linear velocity corresponding to the second video frame via solving a quadratic optimization problem constructed based on the optical flow, the initial values of the angular velocity and the linear velocity corresponding to the second video frame. The apparatus may estimate the pose of the apparatus based on the refined angular velocity and the refined linear velocity.

Abstract: The present disclosure provides a method and apparatus of determining a guide path, and a method and apparatus of controlling driving of a vehicle. The method of determining the guide path may be performed by a monitoring platform and includes: displaying a map for a predetermined range of a vehicle in response to receiving a guide request transmitted by the vehicle, wherein the map includes a plurality of first track points for the vehicle; changing a position of at least one of the plurality of first track points in the map in response to a target operation on the at least one first track point, so as to obtain a plurality of second track points; determining the guide path for the vehicle according to the plurality of second track points; and transmitting path information indicative of the guide path to the vehicle.

Abstract: A commercial vehicle with a cargo space includes a detection unit for detecting movement of a wheel suspension and/or an inertial measuring unit for detecting movements of a sprung mass of the vehicle in order to evaluate a loading state of cargo in the cargo space. To provide improved cargo capacity, improved user-friendliness, and improved driving behavior, the commercial vehicle has an optical signaling unit arranged in the cargo space which is electrically activatable using an evaluation electronics unit, wherein the evaluation electronics unit is configured to activate the signaling unit on the basis of signals of the detection unit and/or the inertial measuring unit which are generated upon placement of the cargo on a cargo surface of the cargo space in such a way that an optimum position of the cargo surface is displayable by means of the signaling unit.

Abstract: A takeoff and landing device, includes: a fixing devices or a communication unit configured to be able to switch between a first state that is a state of preventing the unmanned aerial vehicle from taking off from the takeoff and landing device and a second state that is a state of not preventing taking off; a weight acquisition unit configured to acquire weight of the article that the unmanned aerial vehicle delivers; and a takeoff controller or a takeoff controller configured to switch a state of the fixing devices or the communication unit to the first state or the second state on the basis of the weight of the article acquired by the weight acquisition unit and of a reference value for determining whether it is an overload.

Abstract: The disclosure relates to assessing operation of two or more cameras. These cameras may be a group of cameras of a perception system of a vehicle having an autonomous driving mode. A first image captured by a first camera and a second image captured by a second camera may be received. A first feature vector for the first image and a second feature vector for the second image may be generated. A similarity score may be determined using the first feature vector and the second feature vector. This similarity score may be used to assess the operation of the two cameras and an appropriate action may be taken.

Abstract: An automated driving assistance apparatus includes an occupant's emotion learning section and a control parameter setting section. The occupant's emotion learning section creates an occupant's emotion model based on vehicle driving state information and occupant's emotion information. The occupant's emotion model is used to estimate an emotion of the occupant from a vehicle driving state. The control parameter setting section calculates an ideal driving state based on the occupant's emotion model, and set a control parameter for automated driving of the vehicle based on the ideal driving state. The control parameter setting section output input values relevant to the vehicle driving state to the occupant's emotion model, and select, from the input values received by the occupant's emotion model, an input value that causes a current occupant's emotion to become closer to a target emotion as the ideal driving state of the vehicle.