Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.

The disclosed solution generally relates to a hyperloop vehicle detecting objects in a hyperloop system. Hyperloop vehicles operate at incredible velocities and require robust systems to detect objects that increase the risk to a hyperloop vehicle. Transponders typically provide long-range data about the activity of downstream hyperloop vehicles. However, nearby objects require detection at line-of-sight distances in order to ensure that objects and vehicles within a given transponder interval distance are detected. The disclosed system provides an elegant solution that combines the advantages of both transponder-based object detection and sensor-based object detection.

A predicted course estimating apparatus for estimating a predicted course of the own vehicle, includes: a data acquiring means for acquiring turning data that indicates a turning direction of the own vehicle; a filtering means for removing a high-frequency component that is included in the turning data; a course predicting means for calculating an estimated value for course prediction of the own vehicle, based on the turning data that has been filtered and a speed of the own vehicle; a determining means for determining whether the own vehicle is traveling a part of a road where the shape changes; and a characteristics changing means for changing the extent of removing of the high-frequency component by the filtering means when it is determined that the own vehicle is traveling a part of the road where the shape changes.

A path providing device for providing a route to a vehicle includes a first communication module configured to receive a high-definition (HD) map information from an external server, a second communication module configured to receive external information generated by an external device located within a predetermined range from the vehicle, and a processor configured to generate forward path information for guiding the vehicle based on the HD map and provide the forward path information to at least one of electric components provided in the vehicle. The processor is configured to generate dynamic information related to an object to be sensed by the at least one of the electric components based on the external information and to match the dynamic information to the forward path information.

A vehicle identification system includes a communication device receiving other vehicle information related to other vehicle around a host vehicle, a detection device detecting other vehicle around the host vehicle, and a vehicle identification device identifying a vehicle transmitting the other vehicle information on the basis of the other vehicle information received by the communication device and the detection device, wherein the vehicle identification device is switching between a capturing mode capturing the transmitting vehicle on the basis of the other vehicle information received by the communication device and the detection device, and a tracking mode identifying the transmitting vehicle on the basis of a positional relation between the host vehicle and the transmitting vehicle at the time of the capturing mode, and motion information related to the transmitting vehicle based on the other vehicle information received by the communication device, after the capturing mode.

The present invention relates to a system and a method for correcting position information of a surrounding vehicle, which provide accurate position information of a surrounding vehicle by correcting the position information of the surrounding vehicle received through vehicle-to-vehicle communication, and identifies a license-plate number of a front vehicle through a sensor mounted in a vehicle, calculates a position of the front vehicle, and compare position information, which is included in information including the identified number of the front vehicle in information received from the surrounding vehicle, with the calculated position of the front vehicle to correct the position information of the surrounding vehicle.

Systems, methods, controllers and algorithms for controlling a vehicle to closely follow another vehicle safely using automatic or partially automatic control are described. The described control schemes are well suited for use in vehicle platooning and/or vehicle convoying applications, including truck platooning and convoying controllers. In one aspect, methods of initiating a platoon between a host vehicle and a platoon partner are described. In another aspect, a number of specific checks are described for determining whether a platoon controller is ready to initiate platoon control of the host vehicle. In another aspect, a platoon controller that includes a state machine that determines the state of the platoon controller is described. In another aspect, methods for generating braking alerts to a driver of a vehicle while the vehicle is being at least semi-automatically controlled by a platoon controller are described.

A radar device for detecting a distance between vehicles by the transmission and reception of survey waves is mounted in a vehicle as an object detection means for detecting an object. A cruise control apparatus includes a trajectory calculation means for calculating a moving locus of a preceding vehicle traveling in front of an own vehicle on the basis of the detection result of the radar device, a route prediction means for calculating a predicted route of the vehicle on the basis of the moving locus of the preceding vehicle calculated by the trajectory calculation means, an axial deviation detection means for detecting the axial deviation of the radar device, and an invalidation processing means for invalidating the predicted route calculated by the route prediction means when it is detected that the axial deviation detection means has detected axial deviation of the radar device.

A vehicle control system includes at least one control inceptor to provide pilot control of an associated vehicle and a communications interface to process external entity SA data associated with an external entity that is received at a communications system associated with the associated vehicle. An SA video screen displays video data to a pilot of the associated vehicle. The video data includes pilot-perspective visual data corresponding to a real-time dynamic virtual representation of surroundings of the associated vehicle that simulates a real-world visual perspective of the pilot to the surroundings of the associated vehicle and is responsive to the pilot control. A visual indicator of the external entity is superimposed onto the pilot-perspective visual data at an approximate location corresponding to an actual location of the external entity relative to the associated vehicle and beyond a visual range of the pilot based on the external entity SA data.

Methods of detecting stationary objects are provided. Methods include: receiving sensor signal data including stationary and non-stationary detections from a surrounding environment of the ego-vehicle; determining at least one group of stationary detections which meet one or more lateral position selection criteria based on the lateral position of each stationary detection from a direction faced by the ego-vehicle; determining, at least one group of stationary detections which meet one or more group regularity selection criteria based on the regularity of the differences in position between pairs of sequentially positioned stationary detections in the group in the direction faced by the ego vehicle; determining stationary detections which meet the lateral selection criteria and the group regularity selection criteria for being a group of stationary detections corresponding to at least one stationary object; and removing the stationary detections in corresponding to at least one stationary object from the sensor signal data output.