• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.9-15
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• 2012

The purpose of this study was to investigate the effects of the secondary tasks such as sending text message (STM) and searching navigation (SN) on skin conductance level (SCL) and driving performance of relatively aged and high-experienced drivers. The subjects included 26 taxi drivers; 12 males aged $56.3{\pm}4.4$ with $28.4{\pm}6.4$ years of driving experiences and 14 females aged $55.5{\pm}3.5$ with $19.4{\pm}5.0$ years of driving experiences. All subjects were instructed to keep a constant following distance (30m) from the car ahead and a given vehicle speed (80km/h or 100km/h) in a driving simulator. The relative change of SCL, vehicle velocity deviations, and average following distances were measured during driving only and driving with secondary tasks. The relative change of SCL, average following distance, and vehicle velocity deviation were more increased during the driving with secondary tasks than driving only. The relative change of SCL, vehicle velocity deviation, and average following distance were more affected by driving with 100km/hr than 80km/hr of a given vehicle speed. Secondary tasks increased a work load of drivers in term of SCL change, and decreased driving performance in terms of the vehicle velocity deviation and average following distance.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.97-104
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• 2015

Due to the introduction of various IT devices, including the recently smartphones and the widespread use of the car navigation system to the location-based information service space has been increased. Spatial information users have been requiring higher levels of quality. In this paper, we study how to build accurate three-dimensional space information by integrating MMS(Moblie Mapping System) survey and airborne survey data. Thus, to analyze the tendency of deviation between the MMS survey and airborne survey data observed in the experimental region, the deviation tendency of the data, it was confirmed that was not consistent. Deviation correction model to select how to change the georeferencing information directly contained in the GPS/INS processing results for the determination, classifies the standard is a method for acquiring the correction reference point coordinates using the calibration model, and analyzed their advantages and disadvantages. With the information of the reference point obtained by airborne photograph of a project, using the method of correcting the MMS survey data. Not only clear the deviation existing between the MMS survey data, it was possible to confirm that the deviation exists between the airborne survey data and MMS survey data was also almost erased.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.131-140
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• 2012

The shortest path search algorithm of navigation is generally based on Dijkstra algorithm and considers only the distance using the weight. Dijkstra algorithm based on the distance mainly ought to perform the 'number of nodes 1' and requires a lot of memory, for it is to start from the starting node and to decide the shortest path for all the nodes. Also, it searches only the same identical path in case of any bottleneck due to an accident nearby, since it is based only on the distance, and hence does not have a system that searches the detour road. In order to solve this problem, this paper considers only the travelling time per road (travelling speed * distance), without applying speed criteria (smoothness, slow speed, stagnation and accident control) or road class (express road, national road and provincial road). This provides an advantage of searching the detour, considering the reality that there are differences in time take for the car to travel on different roads with same distance, due to any accident, stagnation, or repair construction. The suggested algorithm proves that it can help us to reach the destination within the shortest time, making a detour from any congested road (outbreak) on providing an information on traveling time continuously(real-time) even though there is an accident in a particular road.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.91-98
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• 2004

This study focuses on the development of dynamic assignment for evaluation and application for dynamic route guidance strategy. Travelers are classified according to information contents which they received pre/on trip. The first group have no traffic information, so they travel with fixed route. The second group have real-time shortest path and travel according to it. The last group have car navigation system or individual method(cellular phone, PDA-two way communication available) for traffic information on trip. And then they are assigned in accordance with the proposed multiclass dynamic assignment model. At this time the last group is gotten under control with DFS(decentralized feedback strategy). In use of this Process we expect that various traffic information strategy can be tested and also be the key factor for success of ITS, location of VMS(variable message sign), cycle of information, area of traffic information, etc).