Abstract: Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes determining vehicle diagnostics information associated with a first autonomous vehicle that is part of a fleet of vehicles controlled by a first entity to provide a vehicle service to a second entity. The method includes determining remote inspection information that includes an assessment of one or more categories pertaining to a third entity, based at least in part on the vehicle diagnostics information. The method includes providing the remote inspection information to the third entity to provide the vehicle service.

Abstract: A data collection system includes a server device and at least one probe vehicle. The server device includes a storage unit configured to store a master map in which a necessity of data collection for each of a plurality of unit ranges included in a plurality of segments is represented by a binary value; and a server control unit configured to extract from the master map a segment corresponding to a position of the probe vehicle, and to transmit the segment to the probe vehicle as a partial map. The probe vehicle includes a data obtaining unit configured to obtain the data; and a vehicle control unit configured to identify a unit range requiring data collection based on the partial map received from the server device, and to transmit the data obtained in the unit range to the server device.

Abstract: Disclosed is a driving assist apparatus which executes a process for collision avoidance when the possibility of collision of a vehicle with an obstacle is high. When the steering angle of the steering wheel is greater than an angle threshold, the apparatus determines that a driver is trying to avoid the collision by operating the steering wheel and does not execute the collision avoidance process. When the vehicle is making a right turn or a left turn, there arises a possibility that the collision avoidance process is not executed even in a situation where the collision avoidance process must be executed. In view of this, when the vehicle is making a right turn or a left turn, the angle threshold mentioned above is set to a larger value as compared with the case where the vehicle is not making a right turn or a left turn.

Abstract: An example method comprises receiving a number of inputs to a system employing an artificial neural network (ANN), wherein the ANN comprises a number of ANN partitions each having respective weight matrix data and bias data corresponding thereto stored in a memory. The method includes: determining an ANN partition to which the number of inputs correspond, reading, from the memory the weight matrix data and bias data corresponding to the determined ANN partition, and a first cryptographic code corresponding to the determined ANN partition; generating, using the weight matrix data and bias data read from the memory, a second cryptographic code corresponding to the determined ANN partition; determining whether the first cryptographic code and the second cryptographic code match; and responsive to determining a mismatch between the first cryptographic code and the second cryptographic code, issuing an indication of the mismatch to a controller of the system.

Abstract: A collision avoidance method for a water-based vessel, including: obtaining real time data relating to the path of two or more vessels; identifying a collision risk between the two or more vessels; determining if the collision risk is above a predetermined threshold, wherein when the collision risk is above the predetermined threshold, determining one or more collision avoidance manoeuvres on the basis of historical navigational data which corresponds to the real-time data; providing the one or more collision avoidance manoeuvres to an operator of the one or more vessels.

Abstract: An autonomous vehicle for blind people is provided. The autonomous vehicle includes a riding and alighting point search device that searches for a riding point at which a user will ride and an alighting point at which the user will alight, in response to call information received from a terminal of the user, a passenger recognition device that recognizes the user who will ride in the vehicle at the riding point, and an autonomous driving controller that controls an autonomous driving operation of the vehicle.

Abstract: An electronic apparatus provided in a first vehicle for determining a collision possibility can include an input unit configured to receive surrounding information of the first vehicle; a communication unit configured to communicate with at least one surrounding vehicle around the first vehicle; and at least one processor configured to operate in conjunction with the input unit and the communication unit, in which the at least one processor is further configured to receive a first image via the input unit, receive at least one second image from the at least one surrounding vehicle via the communication unit, and determine a collision possibility of the first vehicle based on the first image and the at least one second image.

Abstract: The system comprises a plurality of sensor systems, a counter drone, and a processor. A sensor system of the plurality of sensor systems comprises one or more sensors that are connected to a network. The counter drone is connected to the network. The processor is configured to receive an indication of a potential target from the plurality of sensor systems; generate a fused data set for the potential target, determine whether the potential target comprises the threat drone based at least in part on the fused data set; and in response to determining that the potential target comprises the threat drone, provide counter drone instructions to the counter drone.

Abstract: The present disclosure generally relates to user interfaces for managing, modifying, and/or outputting workout content.

Abstract: A server device can obtain historical location data, concerning a vehicle, captured by a global positioning system (GPS) device of the vehicle and historical engine control unit (ECU) data concerning the vehicle captured by an ECU of the vehicle. The server device can process the historical location data and the historical ECU data to train a machine learning model to determine a relationship between the historical location data and the historical ECU data. The server device can receive location data and ECU data concerning the vehicle and update the machine learning model based on the location data and the ECU data. The server device can receive real-time location data concerning the vehicle and derive an equivalent real-time ECU speed using the machine learning model. The server device can generate a message regarding the equivalent real-time ECU speed of the vehicle and send the message to a remote device for display.

Abstract: A computer is programmed to instruct a vehicle to navigate to a pickup location based on a current user location received from a first device and data about a user event received from a second device.

Abstract: A work machine includes a plurality of actuators that drive a work device; a posture sensor that senses postural data about the work device; and a controller having a degree-of-proximity calculating section that computes a degree of proximity that is an index value indicating proximity between an intrusion prohibition region and the work device on the basis of positional data about the intrusion prohibition region and the postural data. A command section executes, when the proximity specified by the degree of proximity is closer than proximity specified by a degree-of-proximity threshold, operating area limiting control to decelerate at least one of the plurality of actuators such that an intrusion of the work device into the intrusion prohibition region is prevented. History of the data about the degree of proximity calculated at the degree-of-proximity calculating section is stored and the degree-of-proximity threshold is altered on the basis of the history data.

Abstract: A method for monitoring a vehicle, the method may include determining, by a computer, whether a pairing between a vehicle and a mobile device associated with the vehicle succeeded; applying, by the computer, a first monitoring process when the pairing succeeded; and applying, by the computer, a second monitoring process that differs from the first monitoring process when the pairing failed.

Abstract: An autonomous vehicle may access portions of a map to maneuver a roadway. The map may be split into one or more levels that represent different regions in space. For example, an overpass may be represented by one level while the road below the overpass may be on a separate level. A vehicle traveling on a particular level may use map data that is associated with that level. Furthermore, if the vehicle travels through a warp zone, it may transition from the current level to a destination level and thus begin to use map data associated with the destination level.

Abstract: Computer-implemented methods and computer systems are disclosed herein as implemented by one or more local or remote processors, transceivers, servers, and/or sensors. The methods and systems include the one or more processors (i) determining an electric vehicle has a state of charge (SOC) below a predetermined threshold; (ii) if the SOC is determined to be below the predetermined threshold, determining homes capable of charging electric vehicles within a vicinity of, or a predetermined distance of, the low SOC vehicle's GPS location; (iii) from among the homes within the predetermined distance of the low SOC vehicle, ranking the homes based upon various factors; and/or (iv) scheduling a rendezvous or appointment for the low SOC vehicle with the highest ranked home for recharging the low SOC vehicle, the highest ranked home being equipped to recharge the low SOC vehicle and is available to charge the low SOC vehicle.

Abstract: Systems and methods are disclosed for the development and management of curated navigational routes are disclosed. The curated navigational route can be a particular path of travel that is specifically designed for one or more users. The curated navigational routes are carefully constructed paths of travel that are custom defined by a route manager.

Abstract: A method, a device, a storage medium and a vehicle for vehicle rollover prevention warning, wherein the method for vehicle rollover prevention warning includes: collecting vehicle body rollover state parameters; calculating a lateral-load transfer rate of the vehicle according to the collected vehicle body rollover state parameters and a preset load transfer rate threshold model comprising the centrifugal force rollover moment of the sprung mass; and determining whether the vehicle has the risk of rollover or not according to the calculated lateral-load transfer rate and the preset rollover threshold. According to the technical solution provided by the invention, the load transfer rate threshold model based on the centrifugal force rollover moment of the sprung mass can simulate the actual rollover state of a vehicle more truly, with a more accurate state indication effect and a high warning accuracy.

Abstract: An actuator system includes an actuator, a first actuator controller that is operable to control operation of the actuator and is operable to determine a first value for a parameter that relates to operation of the actuator, a second actuator controller that is operable to control operation of the actuator and is operable to determine a second value for the parameter, and at least one additional component that is operable to determine a third value for the parameter. A fault is identified in response to determining that the first value does not agree with at least one of the second value or the third value. In response to identification of the fault, the first actuator controller changes from an activated state to a deactivated state and the second actuator controller changes from a deactivated state an activated state.

Abstract: A lift device includes a chassis, tractive elements, a platform, a lift assembly, a first set of proximity sensors, and a controller. The tractive elements are rotatably coupled to the chassis and support the chassis. The platform is disposed above the chassis and includes a deck for supporting an operator. The lift assembly couples the platform to the chassis and can selectably move the platform between a lowered position and a raised position. The first set of proximity sensors are coupled to the platform and detect a distance of an obstacle relative to the platform. The controller is operably coupled with an alert system and receives obstacle detection data from the first set of proximity sensors. The controller selects a subset of the first set of proximity sensors to analyze based on an active function of the lift device and determines whether the obstacle is within the minimum allowable distance.

Abstract: An apparatus and method for an aircraft flight management system configured to analyze a takeoff sequence for an aircraft, the aircraft slight management system comprising a memory storing runway information associated with the runway from which the aircraft will depart, one or more inputs configured to receive variables comprising real-time aircraft variables and real-time condition variables that influence an actual velocity of the aircraft, sensors for sensing the actual velocity of the aircraft; and a processor configured to compare a real-time takeoff value to a takeoff requirement value.