Abstract:
Disclosed herein is an apparatus for continuous profiling for a multicore embedded system, the apparatus including a profiling data reception unit for receiving one or more pieces of profiling source data, in which events for each core in a multicore embedded system are written, from the multicore embedded system; a profiling data analysis unit for analyzing the profiling source data, determining a time at which each of events included in the profiling source data occurred and a core corresponding to the event, and determining whether each of the events is a past event depending on the time at which the event occurred; and a profiling file management unit for distinguishing each of the events depending on the determination of whether the event is a past event and storing the events in profiling files.
Abstract:
Methods for Joint Photographic Experts Group (JPEG) 2000 encoding and decoding based on a graphic processing unit (GPU) are provided. The method for JPEG2000 encoding based on a GPU includes receiving input image data from a central processing unit (CPU), encoding the image data, and transferring the encoded image data to the CPU.
Abstract:
A method of automatically detecting a dynamic object recognition error in an autonomous vehicle is provided. The method includes parsing sensor data obtained by frame units from a sensor device equipped in an autonomous vehicle to generate raw data by using a parser, analyzing the raw data to output a dynamic object detection result by using a dynamic object recognition model, determining that detection of a dynamic object recognition error succeeds by using an error detector when the dynamic object detection result satisfies an error detection condition, and storing the raw data and the dynamic object detection result by using a non-volatile memory when the detection of the dynamic object recognition error succeeds.
Abstract:
Disclosed herein are a dynamic scheduling method for guaranteeing Quality of Service QoS depending on network transmission traffic and a system using the same. The dynamic scheduling method includes assigning communication channels to respective nodes based on Identifications (IDs) of parent nodes corresponding to the respective nodes, setting priorities for assignment of time slots to the respective nodes in each quarter based on data traffic volumes corresponding to the respective nodes, and assigning time slots to the respective nodes in each quarter depending on the set priorities for assignment of the time slots.
Abstract:
There is provided a network join method including transmitting a long beacon message including transmission timing information of a first short beacon message to a child node network device, transmitting a first short beacon message including information regarding an interval in which it is possible to transmit a message, to the child node network device according to a transmission timing of the first short beacon message, receiving a slot allocation request message from the child node network device according to the interval in which it is possible to transmit a message, and checking whether the child node network device joins a network, and transmitting a slot allocation confirmation message to the child node network device.
Abstract:
A method for changing a route when an error occurs in an autonomous driving AI includes collecting error information of the AI when an error of the AI has occurred, extracting, from a storage, past error information about a same kind of AI as that of the AI based on the error information of the AI, generating an error analysis result based on the past error information, generating an error analysis result message based on the error analysis result, and determining whether the driving of the autonomous driving vehicle needs to be stopped based on the error analysis result message.
Abstract:
Disclosed herein are an apparatus and method for adaptive autonomous driving control. The apparatus includes memory in which at least one program is recorded and a processor for executing the program. The program may perform control of a target vehicle by converting a theoretical control value based on a vehicle control algorithm into a hardware-dependent control value, which is dependent on the platform or hardware of the target vehicle, and may modify at least one parameter or a conversion equation for conversion of the hardware-dependent control value such that an error is minimized based on the difference between a response value according to the control of the target vehicle and a control value.
Abstract:
A method and an apparatus for visualizing a scheduling result in a multicore system. A method for visualizing a scheduling result of a plurality of tasks with respect to a plurality of cores in a multicore system includes extracting scheduling data in a time section to be visualized, determining whether the number of the extracted scheduling data exceeds a preset first threshold value, if the number of the extracted scheduling data exceeds the preset first threshold value, performing reduction of the extracted scheduling data, and visualizing and outputting the reduced scheduling data.
Abstract:
The present invention relates to an apparatus and method for monitoring abnormal state of a vehicle. In the method, CAN data collected from an ECU mounted on the vehicle is transformed into coordinates. The coordinates are applied to a distribution map in a specific space, a number of clusters is calculated based on results of the application, and an initial center point corresponding to the number of clusters is selected. Clustering is performed based on the initial center point, and then clusters are generated. At least one piece of data is extracted from each of the clusters, and a state feature of a corresponding cluster is decided on using a difference between maximum and minimum values of attributes constituting the at least one piece of data. A current state of the vehicle is monitored based on current CAN data of the vehicle and state features of the clusters.