Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with the operation of a vehicle are provided. For example a vehicle computing system can receive occupancy data that includes information associated with occupancy of a vehicle that includes seats. One or more states of the vehicle can be determined. The states of the vehicle can include a disposition of any object that is within the vehicle. Further, a configuration of the seats in the vehicle can be determined based on the occupancy data and the states of the vehicle. The configuration can include a disposition of the seats inside the vehicle. Furthermore, at least one of the seats can be adjusted based on the configuration that was determined.

Abstract: Motion steering under kino dynamic constraints is provided. A system can receive an indication to return to a route generated for autonomous navigation by the aircraft to a destination. The system can generate a vector field formed of a plurality of vectors that merge into the route. The vector field can be generated responsive to the indication to return to the route. The system can provide instructions to steer the aircraft toward the destination along the route via one or more vectors of the plurality of vectors in the vector field. The instructions can be based on a cost function applied to the vector field.

Abstract: The present invention relates to method and system for controlling speed of vehicle by using GPS location, real-time traffic light status and machine learning techniques to recommend cruising speed to vehicle without stopping at the traffic lights. The method includes determining status of traffic lights located on route of traffic junctions and associated time period for status of traffic lights based on data received from sensors. The method includes broadcasting status of traffic lights and associated time period. The method includes calculating in real-time a recommended cruising speed of the vehicle based on GPS location associated with vehicle, status of traffic lights and associated time period, and a time period required by vehicle to arrive at the traffic lights using machine learning techniques. The method includes providing in real-time the recommended cruising speed to vehicle. The method includes adaptively controlling in real-time speed of vehicle to recommended cruising speed.

Abstract: The present invention relates to method and system for controlling speed of vehicle by using GPS location, real-time traffic light status and machine learning techniques to recommend cruising speed to vehicle without stopping at the traffic lights. The method includes determining status of traffic lights located on route of traffic junctions and associated time period for status of traffic lights based on data received from sensors. The method includes broadcasting status of traffic lights and associated time period. The method includes calculating in real-time a recommended cruising speed of the vehicle based on GPS location associated with vehicle, status of traffic lights and associated time period, and a time period required by vehicle to arrive at the traffic lights using machine learning techniques. The method includes providing in real-time the recommended cruising speed to vehicle. The method includes adaptively controlling in real-time speed of vehicle to recommended cruising speed.

Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: An electrical assembly includes a primary controller, a secondary controller, and a switch assembly. The primary controller, the secondary controller, and/or the switch assembly may be electrically connected, and/or the secondary controller may be configured to control the primary controller according to a position of a switch of the switch assembly. The switch assembly may be connected to the primary controller, and/or the primary controller may be configured to control movement of a vehicle seat according to the position of the switch. The primary controller may include a first state and/or a second state; and the primary controller may be configured to instruct the secondary controller to change the primary controller from the second state to the first state. The first state of the primary controller may be a low power mode.

Abstract: A framework for modeling traffic speed in a transportation network analyzes both the spatial and temporal dependencies in probe-based traffic speeds, historical weather data, and forecasted weather data, using multiple machine learning models.

Abstract: Disclosed are systems, apparatuses, and methods to enhance control of a drone-load system, including through drone thrusters or load thrusters.

Abstract: A system for controlling a subject vehicle includes a front detection unit to detect a driving situation of a target vehicle located in front of the subject vehicle; a determination unit to detect reversing of the target vehicle or predict a collision between the target vehicle and the subject vehicle through the front detection unit; and a control unit to, when the reversing of the target vehicle is detected or the collision between target vehicle and the subject vehicle is predicted through the determination unit, generate a warning signal of the subject vehicle or control driving of the subject vehicle so that the subject vehicle avoids the collision with the target vehicle.

Abstract: Provided are methods for location based parameters for an image sensor, which can include determining the geographic location of the vehicle, adjusting the parameters of the image sensor of the vehicle from a first setting to a second setting based on the geographic location of the vehicle, receiving sensor data associated with the image sensor based on the second setting, and processing the sensor data to generate an image. Systems and computer program products are also provided.

Abstract: Provided is a multi-objective path planning method for an intelligent public transport system, includes: generating a shortest path network topology for connecting bus stops by analyzing a traffic network topology and bus drivable paths; dynamically and evenly allocate bus routes according to passenger waiting periods, road lengths, and the shortest path network topology, to thereby allocate different routes for different buses; and determining an optimal bus route configuration according to average passenger travel distances, passenger experience, and the bus routes. The method can minimize a passenger waiting period while ensuring a high passenger load rate, thereby improving the overall efficiency of the public transport system and the travel experience of passengers.

Abstract: A autonomous robotic golf caddy which is capable of following a portable receiver at a pre-determined distance, and which is capable of sensing a potential impending collision with an object in its path and stop prior to said potential impending collision.

Abstract: A method for authorizing the flight of an aircraft provided with a hybrid power plant having at least one heat engine and at least one electric motor electrically connected to an electrical energy source comprising several electrical accumulators. The method comprises extracting (STP1), while on the ground, an electrical energy or an electrical power to be extracted from the electrical energy source during a predetermined time period and determining (STP2) for the electrical accumulators, respective initial values of an operating parameter, calculating (STP3) an average value from the initial values, determining (STP4) a minimum value from the measured initial values, issuing an authorization when a difference between the average value and the minimum value is less than a threshold and a prohibition when said difference between the average value and the minimum value is greater than or equal to the threshold.

Abstract: The on-vehicle security device 10 includes log collection means 11 for collecting communication logs, log analysis means 12 for analyzing the collected communication logs, and control means 13 for having alerting means issue an alert when it is determined that an error occurrence frequency exceeds a predetermined threshold value, based on an analysis result of the communication logs by the log analysis means 12, and blocks a communication path where an error has occurred when a state where the error occurrence frequency exceeds the predetermined threshold value continues after having the alerting means issue the alert.

Abstract: A device and method for preventing blind spot collision based on vehicle-to-vehicle communication. The method includes detecting a forward vehicle, requesting vehicle-to-vehicle communication with the forward vehicle, receiving image data and ultrasound data of the forward vehicle, analyzing information about a moving object in a blind spot formed by the forward vehicle, based on the image data and the ultrasound data, calculating a possibility of collision with the moving object based on the information about the moving object, and performing one or both of warning notification and collision avoidance control based on the possibility of collision.

Abstract: Systems, methods, and other embodiments described herein relate to identifying a user of a vehicle. In one embodiment, a method includes determining an activity of the user using one or more mobile devices. The method includes detecting an event in the vehicle using one or more vehicle sensors. The method includes identifying the user based on a relationship between the activity and the event.

Abstract: A drone loaded with a package takes off from a takeoff device and uses a GPS system to fly to a user house that is a delivery destination of the package as the destination. Further, when the drone approaches the user house that is the destination, the flight of the drones is switched from autonomous navigation using the GPS system to remote control performed by a landing device and an in-house control device installed in the user house. The drone lands on the landing device by remote control from the landing device and the in-house control device, separates the package, and then returns to the warehouse using the GPS system and lands on the takeoff device.

Abstract: The present invention belongs to the technical field of electric automobiles and particularly relates to a fault tolerance decision-making method and system for sensor failure of a vehicular wheel hub driving system. The method comprises a current sensor failure diagnostic process, a position/velocity sensor failure diagnostic process and a selection process for a wheel hub motor fault tolerance control method. The system comprises a current sensor failure diagnostic module, a position/velocity sensor failure diagnostic module and a selection module for a wheel hub motor fault tolerance control method. The position/velocity sensor failure diagnostic module further comprises a fault tolerance control switching module.

Abstract: An Unmanned Aerial System configured to receive a request from a user and fulfill that request using an Unmanned Aerial Vehicle. The Unmanned Aerial System selects a distribution center that is within range of the user, and deploys a suitable Unmanned Aerial Vehicle to fulfill the request from that distribution center. The Unmanned Aerial System is configured to provide real-time information about the flight route to the Unmanned Aerial Vehicle during its flight, and the Unmanned Aerial Vehicle is configured to dynamically update its mission based on information received from the Unmanned Aerial System.

Abstract: A first vehicle in traffic can use machine learning and artificial intelligence to detect an imminent collision with a second vehicle or other object. A well-trained AI algorithm can select a sequence of actions (braking, swerving, or accelerating—depending on the specific kinetics) to avoid the collision if possible, and to reduce or minimize the harm if unavoidable. With proper training, the AI model may also infer the intent and future actions of the second vehicle, as well as potential interference of other traffic agents. A good algorithm can also infer the intent of the driver of the first vehicle, for example based on prior driving habits. The AI algorithm may be implemented in a processor on the subject vehicle, potentially in communication with another processor at a fixed site such as a local access point or a central supercomputer.