SUMMARYNavigation systems providing route-guidance and traffic information are one of the most widely used driver-support systems these days. Most navigation systems are based on the map paradigm which plots the driving route in an abstracted version of a two-dimensional electronic map. Recently, a new navigation paradigm was introduced that is based on the augmented reality (AR) paradigm which displays the driving route by superimposing virtual objects on the real scene. These two paradigms have their own innate characteristics from the point of human cognition, and so complement each other rather than compete with each other. Regardless of the paradigm, the role of any navigation system is to support the driver in achieving his driving goals. The objective of this work is to investigate how these map and AR navigation paradigms impact the achievement of the driving goals: productivity and safety. We performed comparative experiments using a driving simulator and computers with 38 subjects. For the effects on productivity, driver's performance on three levels (control level, tactical level, and strategic level) of driving tasks was measured for each map and AR navigation condition. For the effects on safety, driver's situation awareness of safety-related events on the road was measured. To find how these navigation paradigms impose visual cognitive workload on driver, we tracked driver's eye movements. As a special factor of driving performance, route decision making at the complex decision points such as junction, overpass, and underpass was investigated additionally. Participant's subjective workload was assessed using the Driving Activity Load Index (DALI). Results indicated that there was little difference between the two navigation paradigms on driving performance. AR navigation attracted driver's visual attention more frequently than map navigation and then reduces awareness of and proper action for the safety-related events. AR navigation was faster and better to support route decision making at the complex decision points. According to the subjective workload assessment, AR navigation was visually and temporally more demanding.

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The aim of this study is to characterize the heavy metal phytoremediation potential of Miscanthus sp. Goedae-Uksae 1, a hybrid, perennial, bio-energy crop developed in South Korea. Six different metals (As, Cu, Pb, Ni, Cd, and Zn) were used for the study. The hybrid grass effectively absorbed all the metals from contaminated soil. The maximum removal was observed for As (97.7%), and minimum removal was observed for Zn (42.9%). Similarly, Goedae-Uksae 1 absorbed all the metals from contaminated water except As. Cd, Pb, and Zn were completely (100%) removed from contaminated water samples. Generally, the concentration of metals in roots was several folds higher than in shoots. Initial concentration of metals highly influenced the phytoremediation rate. The results of the bioconcentration factor, translocation factor, and enrichment coefficient tests indicate that Goedae-Uksae 1 could be used for phytoremediation in a marginally contaminated ecosystem.

A drowsy driving can bring severe traffic accidents.To prevent these accidents and give a warning to a driver, we analyzed the driving information collected from a vehicle simulator and made a model to detect drowsy driving based on vehicle's behavior such as steering-related and lane-related information. It will be able to provide more effective service for drivers when applied to a vehicle augmented reality system.

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This study was conducted to examine the usage effects of an augmented reality head‐up display (AR‐HUD) system on the risk perception and psychological changes of drivers. To do so, we conducted an experiment to collect the driver response times for vehicles and pedestrians as their risk perception behavior, and used a driving behavior determinants questionnaire consisting of Problem Evading, Benefits/Sensation Seeking, Anti‐Personal Anxiety, Anti‐Personal Angry, and Aggression factors for collecting the psychological characteristics of the drivers. Thirty drivers were randomly assigned into an in‐vehicle AR‐HUD using group and a control group. As a result, the Anti‐Personal Anxiety and Anti‐Personal Angry factors were negatively correlated with the response time for the control group. In contrast, these results were not shown for the in‐vehicle AR‐HUD system using group. These results indicate that the in‐vehicle AR‐HUD system may partially induce a relaxation of tension or stress for drivers with a high level of interpersonal anxiety. Therefore, the in‐vehicle AR‐HUD system might contribute to not only the visual safety driving behaviors of drivers, but also to their psychological driving safety with specific characteristics.

Urban digital twin (UDT) technology can be used to digitize physical urban spaces. Previous UDT or smart city research reconstructed the three-dimensional topography of urban spaces, buildings, and facilities. They collected various multimodal sensor data from cities and monitored conditions such as temperature, humidity, fine dust, and real-time road traffic. However, these studies lacked ways to manage individual mobility data, such as those of the vehicles and pedestrians, which constitute major components of a city. Here, we propose a geospatial platform based on the universal game engine Unity3D, which manages large-scale individual mobility data for a UDT platform. The proposed platform stores and manages individual vehicles or pedestrians using information from public closed-circuit television. It also allows the generation of long-term route information for a unique vehicle based on its license plate. We also propose methods to anonymize license plates, to ensure the security of individuals, and to compress individual mobility data. Unique UDT models with individual mobility functionalities can be built and visualized using our proposed geospatial platform.