• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.549-557
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• 2021

In this research, we will use the existing OID sensor environment for smart robots, which are a type of educational robot, but we would like to propose that the problem of running be handled by a program. Maybe you have driving information We are building a driving test environment focusing on environment, position recognition, route planning, obstacle avoidance and path reset, and it is not the average final error rate, but the time when the error increases The experiment was conducted by a household that catches the moment of recalibration. Through the process, stable running results were obtained compared to the previous experiment. In this research, I think that it will be a development method that can improve the running performance of educational robots equipped with low-cost sensors currently on the market.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.7-18
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• 2015

This research examined the effects of user experience in driving simulation game between using general monitor and 3D virtual reality device, Oculus Rift DK2. We compared the difference of user experience such as presence, flow and arousal by gaming environment. We also tested the effects of virtual reality on driving attitude, emotional pleasure and satisfaction. 100 beginner drivers with a driver's license participated in the experiment of two modes of gaming environment. As a result, all the three user experiences were proved to be significantly higher in VR game play than general monitor game. Also driving attitude, emotional pleasure and satisfaction showed a significant difference in virtual reality. This study makes a theoretical and practical contribution to the application of the next virtual reality game with a special function.

• Journal of Climate Change Research
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• v.7 no.1
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• pp.85-93
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• 2016

This study the efficiency of greenhouse gas reduction of 'low carbon car collaboration fund' and its alternative 'control of average fuel efficiency and greenhouse gas', and 'improving driving behavior' were analyzed by using LEAP, long term energy analysis model. Total 4 scenarios were set, baseline scenario, without energy-saving activity, 'low carbon car collaboration fund' scenario, 'fuel efficiency improving scenario', and 'improving driving behavior' scenario. The contents of analysis were forecast of energy demand by scenario and application as well as reduction of greenhouse gas emission volume, and the period taken for analysis was every 1 year during 2015~2030. Baseline scenario, greenhouse gas emission volume in 2015 would be 7,935,697 M/T and 13,081,986 M/T in 2030, increased 64.8%. The analysis result was average annual increase rate of 3.4%. The expected average annual increase rate of other scenarios was, 'low carbon car collaboration fund' scenario 1.7%, 'fuel efficiency improving' scenario 3.0%. and 'improving driving behavior' scenario 3.4%. and these were each 1.7%, 0.3%. 0.3% reduce from baseline scenario. The largest reduction was 'low carbon car collaboration fund' scenario, and there after were 'fuel efficiency improving scenario', and 'improving driving behavior' scenario.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.101-106
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• 2024

For the commercialization of automated vehicles, it is necessary to create various scenarios that can evaluate driving safety and establish a data system that can verify them. Depending on the vehicle's ODD (Operational Design Domain), there are numerous scenarios with various parameters indicating vehicle driving conditions, but no systematic methodology has been proposed to create and combine scenarios to test them. Therefore, projects are actively underway abroad to establish a scenario library for real-world testing or simulation of autonomous vehicles. However, since it is difficult to obtain data, research is being conducted based on simulations that simulate real road. Therefore, in this study, parameters calculated through individual vehicle trajectory data extracted based on roadside CCTV image-based driving environment DB was proposed through the extracted data. This study can be used as basic data for safety standards for scenarios representing various driving behaviors.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.109-118
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• 1999

A graphic software is one of the most important components of the vehicle simulator. To increase a visual reality of the simulator, the graphic software should require several technologies such as three-dimensional graphics, graphic modeling of the vehicle and the environment, drivers biomechanical models, and real-time data processing. This study presents a real time graphic driving simulator of a construction vehicle. The graphic simulator contains the three models of the construction vehicle, the human, and the environment, and employes a neural network approach to decrease an on-line dynamic computation. An excavator model is represented using an object-oriented paradigm and contains the detailed information about a real-size vehicle. The human model is introduced for objective visual evaluations of the developed excavator model. Since the environment model plays an important role in a real-time simulator, a block-based approach is implemented and a text format is utilized for easier construction of environment. The simulation results are illustrated in order to demonstrate the applicability of developed models and the neural network approach.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.603-608
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• 2006

As an important and relatively easy to implement technology for realizing Intelligent Transportation Systems(ITS), Adaptive Cruise Control(ACC) automatically adjusts vehicle speed and distance to a preceding vehicle, thus enhancing driver comfort and safety. One of the key issues associated with ACC development is usability and user acceptance. Control parameters in ACC should be optimized in such a way that the system does not conflict with driving behavior of the driver and further that the driver feels comfortable with ACC. A driving simulator is a comprehensive research tool that can be applied to various human factor studies and vehicle system development in a safe and controlled environment. This study investigated driving behavior with ACC for drivers with different driving styles using the driving simulator. The ACC simulation system was implemented on the simulator and its performance was evaluated first. The Driving Style Questionnaire(DSQ) was used to classify the driving styles of the drivers in the simulator experiment. The experiment results show that, when driving with ACC, preferred headway-time was 1.5 seconds regardless of the driving styles, implying consistency in driving speed and safe distance. However, the lane keeping ability reduced, showing the larger deviation in vehicle lateral position and larger head and eye movement. It is suggested that integration of ACC and lateral control can enhance driver safety and comfort even further.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.234-240
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• 2014

Driving-related injuries associated with elderly drivers are on the rise, although the overall rate of driving-related injuries has decreased. To determine the causes of this trend, we researched existing vehicle systems that use different sensors and signals to promote safe driving. We found that although the systems alert drivers to potential collisions and assist them in finding a location easily, they were created by people who rarely use the systems in their daily lives. For the most part, they're not created by people with driving difficulties caused by health problems, which in turn often afflict the elderly. To address this issue, we analyzed the drawbacks of the current systems and used a focus group of people with body conditions that have declined due to age to discover the problems they encounter while driving. With the focus group, we used diverse research activities, such as observation and interview to demonstrate how new system concepts could be developed for the elderly. Finally, we propose that adequate system concepts for the elderly would improve driving safety and provide a more enjoyable driving environment for this population.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.734-744
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• 2013

In this study, the telematics device was installed on the car (OBD-II) to collect the information on the operation conditions from each sample vehicle. Based on the information the domestic driving pattern was analysed and the ratio of cold start length was estimated. As a result of analysis for driving pattern, we found a difference in the frequency of driving on the hourly or seasonal basis. Then, the driving pattern of the rush hours, weekdays, and weekends could be derived. Also, from the study, an average of 2.22 times per day occurred in a single trip and average driving distance for the trip was 15.72 km. In addition, the proportion of cold start length was analyzed to be 16.11%. The seasonal cold start length has big difference from season to season (Winter 26.63%, Summer 8.22%, Intermediate 12.65%). There was an inverse relationship between the outside temperature and ratio of cold start length. In order to improve the accuracy of the cold emission estimation, it is necessary to apply domestic ratio of cold start length that driving pattern and temperature in Korea is reflected.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.1-8
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• 2013

Recently, the automotive technology has developed with electronics and information technology as convergence technology while vehicles had been regarded as machines. Moreover, vehicles are becoming more intelligent and safer devices, assembly of advanced technologies by customers' demand. Even though all of installations of vehicle have attracted as diverting devices, it cause drivers' mistakes like delay of response on traffic condition. Here, we proposed the Field Operational Test (FOT) environment which could be used as driving and road conditions collector(Vehicle motion, Traffic condition, Driver input, Driver state, etc.) for researches about Driver Friendly Intelligent System(SCC, LDWS, etc.), Human Vehicle Interface(Driving Workload, etc.) and Economic Drive Model. Furthermore driving patten and fuel consumption patten of drivers were analyzed by measured data and direction of future research was suggested.

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