The paper analyzes factors to affect pedestrian volumes by land-use type using 2012 Seoul Pedestrian Survey. First of all, five groups were classified based on land-use types around survey points such as residential, commercial, industrial and green uses, using k-average cluster analysis. Then, differences in average pedestrian volumes by group were compared for a day and time of day. In addition, multiple regression analysis was employed to identify factors to affect pedestrian volumes, considering physical features, land use types, public transportation accessibility, and socio-economic indices as independent variables by spatial hierarchy. Model results show that the walkway width positively influenced on pedestrian volumes for all groups, whereas other variables differently affected by group. Our results can be used as basic data for establishing polices with respect to pedestrian road design and improvement as well as estimating pedestrian demand by land-use type.
Nowadays the issue of aging society has received considerable critical attention, especially in transportation planning and demand forecasting. This study identified the factors related to travel time budget for elderly by purpose using seemingly unrelated regression model (SUR model). The SUR model is suitable when error terms of each equation are assumed to be correlated across the equations in terms of travel time budget which is constant in 2 hours per day commonly. The results showed that elderly's travel time budget was affected by individual, household, urban facility and transportation service. The leisure travel comprised a large proportion of total travel time and had a positive relationship with elderly, sports, religious facilities. Moreover, the elderly who had low income or unemployed person had low frequency of social activity such as leisure, shopping and business. This study can provide a comprehensive implications of forecasting the future travel demand and analyzing the travel behavior.
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