• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.253-273
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• 2022

Automated vehicles rely on information collected through sensors to drive. Therefore, the uncertainty of the information collected from a sensor is an important to address. To this end, research is conducted in the field of road and traffic to solve the uncertainty of these sensors through infrastructure or facilities. Therefore, this study developed a traffic cone that can maintaing the gaze guidance function in the construction site by securing sufficient LiDAR detection performance even in rainy conditions and verified its improvement effect through demonstration. Two types of cones were manufactured, a cross-type and a flat-type, to increase the reflective performance compared to an existing cone. The demonstration confirms that the flat-type traffic cone has better detection performance than an existing cone, even in 50 mm/h rainfall, which affects a driver's field of vision. In addition, it was confirmed that the detection level on a clear day was maintained at the 20 mm/h rain for both cones. In the future, improvement measures should be developed so that the traffic cones, that can improve the safety of automated driving, can be applied.

• Design Convergence Study
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• v.17 no.4
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• pp.17-29
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• 2018

In the semi-autonomous vehicle, before reaching a fully autonomous driving stage, it is imperative for the system to issue a take-over request(TOR) that asks a driver to operate manually in a specific situation. The purpose of this study is to compare whether head-up display(HUD) is a better human-vehicle interaction than head-down display(HUD) in the event of TOR. Upon recognition of TOR in the experiment with a driving simulator, participants were prompted to switch over to manual driving after performing a secondart task, that is, playing a game, while in auto-driving mode. The results show that HUD is superior to HDD in 'ease of use' and 'satisfaction' although there is no significant difference in reaction time and subjective workload. Therefore, designing secondary tasks through HUD during autonomous driving situation improves the user experience of the TOR function. The implication of this study lies in the establishing an empirical case for setting up UX design guidelines for autonomous driving context.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.305-306
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• 2017

본 논문에서는 커넥티드 카 서비스의 사용자경험 디자인을 위한 평가 요인을 제안한다. 모바일 및 IoT기술의 발전과 더불어 자율주행 자동차에 대한 관심이 증가하고 있는 가운데 네트워크와의 연결을 통한 다양한 디지털서비스 제공 플랫폼 경쟁이 가속화되고 있다. 플랫폼 개발을 위한 기술적 연구는 빠르게 진행되고 있으나 실재 서비스 소비의 주체인 사용자 관점에서의 연구는 아직 미비하다. 경쟁이 가속화 될수록 커넥티드 카 구현 기술은 평중화될 것으로 예상되어 결국 커넥티드 카 서비스의 핵심 쟁점은 주행 중 서비스 사용자의 긍정적 경험이 될 것으로 예측된다. 따라서 본 논문에서는 커넥티드 카에서 제공되는 기능과 이에 따른 주요 서비스 요인들을 살펴보고 자동차 구매에 영향을 미치는 사용자경험 요인을 도출하여 둘의 상관관계를 실증적으로 분석함으로써 앞으로 등장할 차세대 커넥티드 카 서비스 및 플랫폼의 사용자 경험평가 요인을 도출하고자 한다.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.115-122
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• 2018

The purpose of this study is to investigate the effect of technology acceptance model (TAM) on behavioral intention in order to grasp the degree of technology acceptance on autonomous driving among the various factors that consumers perceive as unmanned vehicle system becomes commercialized. In addition to the mediating effect of perceived usefulness proposed by the existing TAM, this study proposed the perceived trust (PT) and hypothesized its mediating effect on behavioral intention to use the self-driving. Path anlaysis is adopted to investigate our hypothesis using the structural equation model. The sample used for the analysis was 149 valid data among 160 responses. The effects of total effect, direct effect, and indirect effect were confirmed by hypothesis test on mediating effect. Non-parametric bootstrapping analysis was also performed to confirm the robustness. All the hypotheses were significant and we found a partial indirect effect, which implies that mediation effect of PT on behavioral intention.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.573-585
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• 2018

Services for navigation and entertainment through AI-based voice user interface devices are becoming popular in the connected car system. Given the classification of VUI agent developers as IT companies and automakers, this study explores attributes of agent persona and user experience that impact the driver's perceived safety and satisfaction. Participants of a car simulator experiment performed entertainment and navigation tasks, and evaluated the perceived safety and satisfaction. Results of regression analysis showed that credibility of the agent developer, warmth and attractiveness of agent persona, and efficiency and care of the UX dimension showed significant impact on the perceived safety. The determinants of perceived satisfaction were unity of auto-agent makers and gender as predisposing factors, distance in the agent persona, and convenience, efficiency, ease of use, and care in the UX dimension. The contributions of this study lie in the discovery of the factors required for developing conversational VUI into the autonomous driving environment.