Abstract:
Provided are a method and device for determining a non-line of sight (NLOS) state around a GPS receiver. The method may include collecting, from at least one satellite, satellite information including a direction angle, a signal to noise (SNR), and an altitude, selecting a satellite of which the NLOS state is to be determined based on an altitude value of the collected satellite information, and determining whether the selected satellite is in the NLOS state with respect to a direction to the satellite based on the SNR and direction angle included in the satellite information of the selected satellite. According to the present invention, by reducing a location calculation error that occurs due to a distance measurement error when a location is measured, a more precise result of location measurement can be obtained.
Abstract:
Disclosed herein are a method and apparatus for processing a driving cooperation message. The method for processing a driving cooperation message includes receiving multiple first driving cooperation messages from neighboring autonomous vehicles, adjusting cooperation classes of the multiple first driving cooperation messages, creating driving strategies corresponding to the adjusted cooperation classes in descending order of priorities of the adjusted cooperation classes, generating second driving cooperation messages including the adjusted cooperation classes and the driving strategies corresponding to the adjusted cooperation classes, and sending the second driving cooperation messages to the neighboring autonomous vehicles requiring cooperative driving.
Abstract:
Disclosed herein are a cooperative driving method based on driving negotiation and an apparatus for the same. The cooperative driving method is performed by a cooperative driving apparatus for cooperative driving based on driving negotiation, and includes determining whether cooperative driving is possible in consideration of a driving mission of a requesting vehicle that requests cooperative driving with neighboring vehicles, when it is determined that cooperative driving is possible, setting a responding vehicle from which cooperative driving is to be requested among the neighboring vehicles, performing driving negotiation between the requesting vehicle and the responding vehicle based on a driving negotiation protocol, and when the driving negotiation is completed, performing cooperative driving by providing driving guidance information for vehicle control to at least one of the requesting vehicle and the responding vehicle.
Abstract:
Disclosed herein are an apparatus and a method for autonomous vehicle negotiation based on Vehicle-to-Vehicle (V2V) communication, the method including requesting, by vehicles that enter a driving negotiation section, a driving negotiation token, acquiring, by a vehicle that enters the driving negotiation section first, among the entering vehicles, the driving negotiation token, performing driving negotiation based on whether the driving negotiation token is acquired, and returning, by a vehicle having acquired the driving negotiation token, the driving negotiation token when the vehicle arrives at a destination.
Abstract:
Disclosed herein are an apparatus and method for providing a seamless network service based on multiple heterogeneous networks. The method for providing a seamless network service based on multiple heterogeneous networks includes providing, by a multi-network management apparatus, a service transmitted from a server to a terminal over a primary network, synchronizing, by the multi-network management apparatus, service data transmitted over the primary network with a secondary network maintained in a standby state, changing, by the multi-network management apparatus, the secondary network to the primary network as a communication failure between the primary network and the terminal occurs, and providing, by the multi-network management apparatus, the service transmitted from the server to the terminal over the changed primary network.
Abstract:
In a vehicle communication environment, a handover apparatus that is located at a random vehicle determines whether to perform handover based on a received signal intensity value of a signal that is received from base stations that are installed at the roadside and information that is acquired from peripheral vehicles. In this case, it is determined whether to perform handover using a signal intensity value and a link base station value representing a base station to which each vehicle is connected among information that is acquired from peripheral vehicles.
Abstract:
The present disclosure relates to a defensive driving vehicles interaction system (D2VIS), and to an autonomous driving predictive defensive driving system through an interaction based on forward vehicle driving and situation judgement information and a method thereof. An autonomous driving predictive defensive driving system through an interaction based on forward vehicle driving and situation judgement information according to the present disclosure includes an inter-vehicle distance recognition unit configured to recognize a distance between a surrounding vehicle and an ego vehicle, a situation recognition unit configured to recognize situation information including surrounding information of the surrounding vehicle, and a driving situation response determination unit configured to share data for determining a defensive driving action by using the situation information.
Abstract:
Disclosed is a system performing a method for detecting intersection traffic light information including a traffic light detection module including an image sensor for generating first signal data based on traffic light image data in which a traffic light is included, a communication module that receives second signal data for communication with a surrounding object and an external device, an object information collection module that collects dynamic data of the surrounding object, and a signal information inference module that infers third signal data based on the dynamic data. The dynamic data of the surrounding object includes at least one information of whether the surrounding object moves, a moving direction of the surrounding object, and whether the surrounding object accelerates or decelerates. Each of the signal data includes pieces of information about a type of the traffic light and a signal direction of the traffic light.
Abstract:
Disclosed herein is a method of controlling an autonomous vehicle driving in a lane of a main line. The method may include determining whether the autonomous vehicle is driving in a target lane to accommodate merging traffic, determining whether a merge request message is received from a merging vehicle when the autonomous vehicle is determined to drive in the target lane, determining whether a collision with the merging vehicle will occur based on the merge request message when the merge request message is received, and sending a merge approval message to the merging vehicle when the collision with the merging vehicle is expected.
Abstract:
Disclosed herein are an object recognition apparatus of an automated driving system using error removal based on object classification and a method using the same. The object recognition method is configured to train a multi-object classification model based on deep learning using training data including a data set corresponding to a noise class, into which a false-positive object is classified, among classes classified by the types of objects, to acquire a point cloud and image data respectively using a LiDAR sensor and a camera provided in an autonomous vehicle, to extract a crop image, corresponding to at least one object recognized based on the point cloud, from the image data and input the same to the multi-object classification model, and to remove a false-positive object classified into the noise class, among the at least one object, by the multi-object classification model.