• International Journal of Highway Engineering
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• v.19 no.1
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• pp.91-106
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• 2017

PURPOSES : Because elderly drivers are more prone to becoming confused when approaching an urban intersection and thus may yield prolong judgment and decision times than non-elderly drivers, to increase the comfort and safety of the intersection environment for elderly drivers, this study applied autonomous driving tests at an urban intersection to examine their driving characteristics. METHODS : To obtain a more comprehensive understanding of driving features, this study collected drive data of non-elderly drivers and elderly drivers via an autonomous experiment using OBD2 and an eye-tracker, in addition to performing a literature review on the measured visibility range of elderly drivers at intersections. This literature review was conducted considering the general knowledge of elderly drivers having relatively reduced visibility. Additionally, as they are commonly more vulnerable, this study analyzes characteristics of elderly drivers as compared to those of non-elderly drivers. CONCLUSIONS : The results of this study can be summarized as follows: 1) the peripheral visible distance of elderly drivers is reduced as compared to that of non-elderly drivers; 2) elderly drivers approach and proceed through intersections at slower speeds than non-elderly drivers; and 3) elderly drivers yield increased driving distances when performing a right or left turn as compared to non-elderly drivers as a result of their reduced speed and acceleration and larger turning radii relative to non-elderly drivers.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.