Abstract: An apparatus of assisting lane following by considering a time delay for a front wheel steering angle, in association with parking, and a method for the same are provided. The apparatus obtains surrounding information of a vehicle, determines a target route, based on the obtained surrounding information and a target front wheel steering angle based on the target route, determines a target handle steering angle depending on the target route, based on the target front wheel steering angle, while considering a time delay of a steering system of the vehicle, and performs a lane following assist control operation to follow the target route, based on the target handle steering angle.

Abstract: An automated on-vehicle rail vehicle control system has an on-vehicle set point value detection unit, an automated train operating system, a driving and braking unit, and additional sensors for detecting environment-related information. The on-vehicle set point value detection unit is configured to determine, based on on-vehicle positioning and map data as well as sensor data from the additional sensors, operative set point values for the control mode and the current driving mission of the rail vehicle. The automated train operating system is configured to generate driving and braking commands based on the set point values of the on-vehicle set point value detection unit. The driving and braking unit is configured to carry out traction and braking operations based on the driving and braking commands so determined. There are also described a rail vehicle and a method for the automated control of a rail vehicle.

Abstract: Disclosed is method including receiving digital vehicle data for a fleet of vehicles like trucks, trains, planes, drones, etc., the digital vehicle data being one or more of GPS/location-based data, image data or radar data and combining one or more of pieces of data. The method includes inferring, based on the first combined data or based on incomplete data, a loaded/empty status of a vehicle. The method includes combining other data to yield second combined data, receiving data regarding one or more of supply, demand, and amount of available cargo to yield third combined data, generating information relating to a supply of vehicles available to load at a specified dock and/or deliver a cargo to a specified dock, in each case within a specified period of time and generating suggestions for one or more vehicles regarding future routes based on the data.

Abstract: A vehicle driving assistance method includes detecting a speed of a vehicle, obtaining a speed limit of the vehicle in a corresponding section of road based on images when the speed of the vehicle exceeds the speed threshold, and issuing a warning when the speed of the vehicle exceeds the speed limit of the vehicle in the corresponding section of road.

Abstract: Apparatus and methods for counteracting, e.g., drift of automatic swimming pool cleaners are detailed. In particular, a drifting cleaner may recover its movement by altering traction speed of the motive element(s) on one side of its body. Such alteration may occur when the cleaner is travelling along a generally horizontally-oriented pool bottom, climbing up or down a wall, or otherwise moving within a pool.

Abstract: An identification method and an unmanned aerial vehicle (UAV) detection apparatus are provided. The identification method, as a method for preventing a collision that may occur in a process of detecting and identifying a plurality of UAVs flying in the air, detects a plurality of UAVs in the air and determines a legitimacy of flight of each of the plurality of UAVs using an identification information request message.

Abstract: An electro-pneumatic service and emergency braking control system is described, comprising: a switching device arranged to allow the connection of a first group of control and feedback signals from an emergency braking control module to an electro-pneumatic emergency braking module when a monitoring device determines the correct operation of the emergency braking control module and to allow the connection of a third group of control and feedback signals from the service braking control module to the electro-pneumatic emergency braking module when the monitoring device determines the incorrect operation of the emergency braking control module.

Abstract: The application provides a method, device, electronic device for vehicle cooperative decision-making as well as a computer storage medium. The method for vehicle cooperative decision-making applied at a cloud server includes: receiving a cooperative decision request sent by a roadside device, wherein the cooperative decision request is a request sent by the roadside device after it is recognized that a road is congested based on acquired real-time road information; acquiring information of a road scene included in the cooperative decision request; determining a congestion scene type based on the information of the road scene; calculating multi-vehicle oriented decision planning schemes using a preset scene cooperative decision model based on the congestion scene type; and sending the decision planning schemes to respective vehicles, so that the vehicles perform respective driving operations according to the decision planning schemes.

Abstract: A vehicle battery fire sensing apparatus includes a battery pack mounted to a vehicle structure, an electronic control unit, and at least one communication line, wherein the battery pack includes a battery module including at least one battery cell, a battery management system configured to transmit a signal received from the battery module to the electronic control unit, and a battery pack case having a gas discharge portion configured to allow venting gas to be discharged therethrough. The battery pack case is provided with a sensor configured to measure at least one of temperature and pressure, and a vehicle battery fire sensing method.

Abstract: An aircraft control method includes: acquiring a current flight state of the aircraft, in response to the aircraft being in a night flight mode, the aircraft being provided with a visual sensor and a light supplementation lamp configured to provide a fill light function for the visual sensor; controlling the light supplementation lamp to emit light according to a light supplementation rule of the light supplementation lamp, in response to the aircraft being in a first flight state; and controlling the light supplementation lamp to emit light according to an alerting rule of the light supplementation lamp, in response to the aircraft being in a second flight state. The light supplementation rule is configured to control the light supplementation lamp to implement the fill light function in the night flight mode, and the alerting rule is configured to control the light supplementation lamp to implement an aircraft flight alerting function in the night flight mode.

Abstract: This disclosure provides a method, apparatus, and storage medium for processing a driving simulation scenario. The method includes: acquiring a plurality of route points in a road network model for driving simulation; determining one or more departure points and one or more destination points from the plurality of route points; generating a background vehicle at the one or more departure points; and controlling the background vehicle to travel in the road network model from the one or more departure points to a corresponding destination point of the one or more destination points, where the background vehicle is removed.

Abstract: The invention relates to a method and a system for determining process data of a work process carried out by an implement based on the determination of a moved mass by a weighing system of the implement and the detection of a parameter concerning a state of the implement and/or a work step, wherein with reference to these and further data a prediction value concerning the remaining part of the current work process is determined and on the basis of which information on the assistance is indicated to the operator of the implement, and to an implement comprising such a system.

Abstract: In order to control at least partially automated vehicles in a road danger zone, in particular road junctions in road traffic, in such a way that the vehicles can pass through the road danger zone in flowing traffic without stop/start interruptions, such as those caused e.g. by signalling equipment, traffic lights, the following proposes the following steps: a) each vehicle of the vehicles, on approaching the road danger zone, surrender the power to control the dynamic driving tasks of the vehicle in order to pass through said zone, b) when the vehicles have surrendered vehicle control power, a central control entity generates a digital road danger zone twin, and, as a result of the vehicles having surrendered vehicle control power, vehicle movements of the vehicle are automatically and dynamically controlled in a vehicle-coordinated and collision-free manner in order to pass through the road danger zone.

Abstract: The present disclosure provides a neural network-based method for calibration and localization of an indoor inspection robot. The method includes the following steps: presetting positions for N label signal sources capable of transmitting radio frequency (RF) signals; computing an actual path of the robot according to numbers of signal labels received at different moments; computing positional information moved by the robot at a tth moment, and computing a predicted path at the tth moment according to the positional information; establishing an odometry error model with the neural network and training the odometry error model; and inputting the predicted path at the tth moment to a well-trained odometry error model to obtain an optimized predicted path. The present disclosure maximizes the localization accuracy for the indoor robot by minimizing the error of the odometer with the odometry calibration method.

Abstract: Implementations process, using machine learning (ML) layer(s) of ML model(s), actor(s) from a past episode of locomotion of a vehicle and stream(s) in an environment of the vehicle during the past episode to forecast associated trajectories, for the vehicle and for each of the actor(s), with respect to a respective associated stream of the stream(s). Further, implementations process, using a stream connection function, the associated trajectories to forecast a plurality of associated trajectories, for the vehicle and each of the actor(s), with respect to each of the stream(s). Moreover, implementations iterate between using the ML layer(s) and the stream connection function to update the associated trajectories for the vehicle and each of the actor(s). Implementations subsequently use the ML layer(s) in controlling an AV.

Abstract: Methods and systems are provided for an automated door system for a vehicle. In one example, the method for a vehicle may include operating an automated door system to enable hands-free actuation of a set of door vehicles while the height of the vehicle is not changing and when the vehicle height is changing, suspending operation of the automated door system until the floor has stopped changing height.

Abstract: A tire wear prediction system (100) is provided with a wear prediction unit (110) for predicting a wear state of a tire mounted at a predetermined wheel position of a vehicle based on the traveling state of the vehicle, a change history acquisition unit (120) for acquiring a change history including the rotation of the wheel position on which the tire is mounted or a content of replacement with another tire, and a wear state correction unit (140) for correcting a reference of the wear state of the tire predicted by the wear prediction unit (110) based on the change history. The wear prediction unit (110) predicts the wear state of the tire based on the reference of the wear state corrected by the wear state correction unit (140).

Abstract: Connected vehicles and methods described herein provide for message sender identification. Connected vehicles and methods disclosed herein can include generating a message based hyper-graph based on the positions of connected elements of a road traffic network as communicated to the connected vehicle by the connected elements. Connected vehicles and methods disclosed herein can include generating, a perception based hyper-graph based on the perceived positions of at least a subset of the elements of the road traffic network as determined by a sensor of the vehicle. Connected vehicles and methods disclosed herein can include matching a node of the message-based hyper-graph to a corresponding node of the perception-based hyper-graph to determine the sender of a received message.

Abstract: Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.

Abstract: A vehicle control apparatus selects, as a first group, objects in a predetermined area from objects included in object information, selects, as a second group, an upper limit number of the objects from the first group in descending order of a priority value when the number of the objects of the first group is greater than the upper limit number, and executes a collision avoidance control when an index value satisfies a predetermined condition. The priority value represents a probability that the own vehicle collides with the object. The apparatus reduces the priority value of a particular object of the first group when the moving speed of the own vehicle is equal to or lower than a moving speed threshold. The particular object is an object which is deemed to have a moving speed lower than a moving speed of a four-wheel vehicle.