목적 : 본 연구는 시뮬레이터 훈련이 척수손상 환자의 운전시뮬레이터 도로 주행시간과 주행조작 능력에 미치는 영향을 알아보고자 하였다. 연구방법 : 본 연구는 단일사례실험연구 AB설계로 진행되었으며, 기초선 3회기, 중재기 10회기를 적용하였다. 기초선 3회, 중재기 5회 도로주행코스(중급) 수행 시 운전시간, 주행조작 능력 자료가 수집되었으며, 연구결과 분석을 위하여 시각적 분석 방법과 평균 ±2*표준 편차를 사용한 양적 분석을 동시에 사용하였다. 결과 : 연구대상자 3명의 총 주행시간은 기초선 A보다 중재기 B에서 3분 내외의 감소하였고, 세 명 모두에서 통계학적으 로 의미있는 주행 능력의 향상이 확인되었다. 주행조작능력 또한 오류 점수가 감소하였고, 첫 번째 참여자와 세 번째 참 여자의 경우 그 변화가 통계학적으로 유의하였다. 결론 : 본 연구에서 연구대상자의 총 주행시간 및 수행 오류의 감소가 확인되어 운전시뮬레이터 훈련의 효과가 있었다. 이 와 같은 결과는 운전시뮬레이터 훈련의 적용 가능성을 뒷받침 한다.

PURPOSES : The desire of drivers to increase their driving speeds is increasing in response to the technological advancements in vehicles and roads. Therefore, studies are being conducted to increase the maximum design speed in Korea to 140 km/h. The stopping sight distance (SSD) is an important criterion for acquiring sustained road safety in road design. Moreover, although the perception-reaction time (PRT) is a critical variable in the calculation of the SSD, there are not many current studies on PRT. Prior to increasing the design speed, it is necessary to confirm whether the domestic PRT standard (2.5 s) is applicable to high-speed driving. Thus, in this study, we have investigated the influence of high-speed driving on PRT. METHODS : A driving simulator was used to record the PRT of drivers. A virtual driving map was composed using UC-Win/Road software. Experiments were carried out at speeds of 100, 120, and 140 km/h while assuming the following three driving scenarios according to driver expectation: Expected, Unexpected, and Surprised. Lastly, we analyzed the gaze position of the driver as they drove in the simulated environment using Smarteye. RESULTS: Driving simulator experimental results showed that the PRT of drivers decreased as driving speed increased from 100 km/h to 140 km/h. Furthermore, the gaze position analysis results demonstrated that the decrease in PRT of drivers as the driving speed increased was directly related to their level of concentration. CONCLUSIONS : In the experimental results, 85% of drivers responded within 2.0 s at a driving speed of 140 km/h. Thus, the results obtained here verify that the current domestic standard of 2.5 s can be applied in the highways designated to have 140 km/h maximum speed

Storytelling has become increasingly of interest for marketing and management in the last years and promises both aesthetic design and effecting consumers’ perception of fashion brands positively. Nevertheless, the complexity of story design, still being rather focussed by the humanities, and its effective adaption for luxury fashion brands regarding value perception and related behavioural consequences are still poorly understood and have not been explored so far. We seek to fill this research gap. In our study, we chose a luxury brand’s existing story and applied story concepts of narratology to rearrange plot, characters, and style first. In a second step, we examined the effect of applying the story concepts by testing the perception of three different groups (no story, original story, and rearranged story). Using PLS path modelling, we proved our hypotheses empirically. Our examination suggests that an application of narrative concepts for creating fashion brand stories has a measurable impact on consumer’s reception and behavioural outcome. On the one hand, this involves dimensions of luxury value, such as financial, functional, individual, and social consumer perceptions as well as an overall likability perception of the brand. On the other hand, this perception obviously impacts consumption habits regarding luxury fashion as much as it is related to recommendation behaviour, willingness to pay a premium price, and purchase intentions. Our findings strongly advice to consult established theories, concepts, and models of the humanities for storytelling in marketing and management. While measuring specific elements already proves their applicability, it will be a major task for theoretical and qualitative research to discuss existing material for the demands of marketing and management as well as (fashion) brands. Even for professionals in brand management, our study advices to have a closer look on traditional storytelling concepts to create effective campaigns. The particular value of our study is to present and empirically verify design elements of storytelling with respect to theoretical narrative approaches, which may have specific impact on certain luxury values and their causal effects on luxury fashion consumption. Our results reflect remarkable implications for luxury brand management as well as future research in luxury fashion, brand management, and marketing storytelling. A luxury company may stimulate purchase behaviour with a storytelling campaign. Nevertheless our study proved that a rather appropriate design, respecting research approaches of narratology, is able to increase the impact on consumers’ perception and behavioural outcome.

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.

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

A* algorithm is a global path generation algorithm, and typically create a path using only the distance information. Therefore along the path, a moving vehicle is usually not be considered by driving characteristics. Deceleration at the corner is one of the driving characteristics of the vehicle. In this paper, considering this characteristic, a new evaluation function based path algorithm is proposed to decrease the number of driving path corner, in order to reduce the driving cost, such as driving time, fuel consumption and so on. Also the potential field method is applied for driving of UGV, which is robust against static and dynamic obstacle environment during following the generated path of the mobile robot under. The driving time and path following test was occurred by experiments based on a pseudo UGV, mobile robot in downscaled UGV’s maximum and driving speed in corner. The experiment results were confirmed that the driving time by the proposed algorithm was decreased comparing with the results from A* algorithm.