• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.6
• /
• pp.517-523
• /
• 2010

In this paper, we proposed an algorithm to detect aggressive driving status by analysing six kinds of driving patterns, which was achieved by comparing for the feature vectors using mahalanobis distance. The first step is to construct feature matrix of $6{\times}2$ size using frequency response of the time-series accelerometer data. Singular value decomposition makes it possible to find the dominant eigenvalue and its corresponding eigenvector. We use the eigenvector as the feature vector of the driving pattern. We conducted real experiments using three drivers to see the effects of recognition. Although there exists differences from individual drivers, we showed that driving patterns can be recognized with about 80% accuracy. Further research topics will include the development of aggressive driving warning system by improving the proposed technique and combining with post-processing of accelerometer signals.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.1
• /
• pp.106-123
• /
• 2024

This article takes the talk show "Beast Town" as an example to introduce the overall technical solution, technical difficulties and countermeasures for the combination of cartoon virtual characters and virtual studio technology, providing reference and experience for the multi-scenario application of digital humans. Compared with the live broadcast that combines reality and reality, we have further upgraded our virtual production technology and digital human-driven technology, adopted industry-leading real-time virtual production technology and monocular camera driving technology, and launched a virtual cartoon character talk show - "Beast Town" to achieve real Perfectly combined with virtuality, it further enhances program immersion and audio-visual experience, and expands infinite boundaries for virtual manufacturing. In the talk show, motion capture shooting technology is used for final picture synthesis. The virtual scene needs to present dynamic effects, and at the same time realize the driving of the digital human and the movement with the push, pull and pan of the overall picture. This puts forward very high requirements for multi-party data synchronization, real-time driving of digital people, and synthetic picture rendering. We focus on issues such as virtual and real data docking and monocular camera motion capture effects. We combine camera outward tracking, multi-scene picture perspective, multi-machine rendering and other solutions to effectively solve picture linkage and rendering quality problems in a deeply immersive space environment. , presenting users with visual effects of linkage between digital people and live guests.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.10 no.1
• /
• pp.195-202
• /
• 2002

By using modeling and simulation. today's design engineers are simultaneously reducing time to market and decreasing the cost of development, while increasing the quality and reliability of their products. A driving simulator is the best example of this method and allows virtual designs of control systems, electronic systems, mechanical systems and hydraulic system of a vehicle to be evaluated before costly prototyping. The objective of this Paper is to develop the virtual Proving: ground using a driving simulator and to show its capabilities of an automotive system development tool. For this purpose, including a real-time vehicle dynamics analysis system, the PC-based driving simulator and the virtual proving ground are developed by using VR(Virtual Reality) techniques. Also ABS HIL(Hardware-In-the-Loop ) simulation is performed successfully.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.1503-1506
• /
• 2008

A novel white-LED (light emitting diode) backlight system for 46"LCD TVs which involves the current controlled X-Y channel driving method is proposed in this paper. There are two problems related to the LED current in the conventional X-Y channel driving driven by a constant voltage source. To solve these problems, a real time current sensing system is applied to the conventional one and the time-division current sensing method is employed.

• International Journal of Automotive Technology
• /
• v.7 no.3
• /
• pp.377-383
• /
• 2006

This paper presents evaluation and comparisons of manual driving and driving with intelligent cruise control(ICC) systems. An intelligent vehicle cruise control strategy has been designed to achieve natural vehicle behavior of the controlled vehicle that would make human driver feel comfortable and therefore would increase driver acceptance. The evaluation and comparisons of the ICC and manual driving have been conducted using real-world vehicle driving data and an ICC vehicle simulator.

• Journal of Korean Society of Transportation
• /
• v.33 no.5
• /
• pp.449-460
• /
• 2015

The reliability of air quality evaluation results for green transportation could be improved by applying correct emission factors. Unlike previous studies, which estimated emission factors that focused on vehicles in laboratory experiments, this study investigates emission factors according to road types and time using real driving data. The real driving data was collected using a Portable Activity Monitoring System (PAMS) according to road types and time, which it compared and analyzed fuel consumption from collected data. The result of the study shows that fuel consumption on national highway is 17.33% higher than the fuel consumption on expressway. In addition, the average fuel consumption of peak time is 4.7% higher than that of non-peak time for 22.5km/h. The difference in fuel consumption for road types and time is verified using ANOCOVA and MANOVA. As a result, the hypothesis of this study - that fuel consumption differs according to road types and time, even if the travel speed is the same - has proved valid. It also suggests correction factor of emission factors by using the difference in fuel consumption. It is highly expected that this study can improve the reliability of emissions from mobile pollution sources.

• The Journal of Korea Robotics Society
• /
• v.14 no.2
• /
• pp.122-130
• /
• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.3
• /
• pp.555-560
• /
• 2018

In this paper, we focus on the study of educational contents using real vehicle based electric vehicle diagnosis system. To understand the electric vehicle, we describe the driving modes and operating principles of the core components and electric vehicles that make up the electric vehicles. In addition, we implemented a diagnostic system for analyzing the characteristics of the electric vehicle test bed and analyzed the characteristics of the vehicle based on the driving mode.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.25 no.2
• /
• pp.219-226
• /
• 2017

This paper addresses the effective and quantitative image DB construction for the development of front looking camera systems. The automotive industry has expanded the capability of front camera solutions that will help ADAS(Advanced Driver Assistance System) applications targeting Euro NCAP function requirements. These safety functions include AEB(Autonomous Emergency Braking), TSR(Traffic Signal Recognition), LDW(Lane Departure Warning) and FCW(Forward Collision Warning). In order to guarantee real road safety performance, the driving image DB logged under various real road conditions should be used to train core object classifiers and verify the function performance of the camera system. However, the driving image DB would entail an invalid and time consuming task without proper guidelines. The standard working procedures and design factors required for each step to build an effective image DB for reliable automotive front looking camera systems are proposed.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.15 no.1
• /
• pp.71-77
• /
• 2007

Dangerous driving is a major cause of traffic accidents in Korea. It becomes more serious for commercial vehicles due to higher fatality rates. The Safe Driving Management System (SDMS), developed in this research, is a comprehensive solution that monitors and stores driving conditions of vehicles, detects dangerous driving situations, and analyzes the results in real time. The Safe Driving Management System consists of a vehicle movement information controller, a dangerous driving detection algorithm and a vehicle movement data report and analysis program. The dangerous driving detection algorithm detects and classifies dangerous driving conditions into representative cases such as sudden acceleration, sudden braking, sudden lane change, and sudden turning. Both computer simulation and vehicle test have been conducted to develop and verify the algorithm. The Safe Driving Management System has been implemented on commercial buses to verify its reliability and objectivity. It is expected that the system can contribute to prevention of traffic accidents, systemization of safe driving management and reduction of commercial vehicle operation costs.