Relationship between Pedestrian Network and Pedestrian Volume Using Connectivity
Sangjin Han, Young-Ook Kim, Soon-Mi Oh
Abstract
Sangjin Han, Young-Ook Kim, Soon-Mi Oh
Abstract
It is important to know pedestrian volume to carry out pedestrian safety analysis and pedestrian friendly design. However, it is too difficult to come across research work related to pedestrian volume analysis in the field of transport, due to lack of interests on pedestrian movement. Most transport research has been focused on vehicles and highways rather than pedestrian. On the other hand, in the field of urban studies, there comes an effective tool to estimate pedestrian volumes using Space Syntax theory. This theory twins out to be effective and economic because it only requires network information, which is easy to acquire from maps and field survey. However, this method is different in the way representing networks from the way that is common in the field of transport. To make up for this point, this paper develops a novel measure for estimating pedestrian volume using Dial's algorithm, and applies the model in the two test networks; Insadong and Soongryemoon networks. The application results reveals that developed measure is an effective tool to explain pedestrian volume; a correlation coefficient between the measure and pedestrian volume is 0.713 in Insadong and 0.492 in Soongryemoon, and the goodness of fit() of regression models are 0.893 in Insadong and 0.671 in Soongryemoon. This estimation method is significantly less complicated to estimate the effect of a pedestrian network change than Space Syntax theory, which requires special softwares not readily available.
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It is important to know pedestrian volume to carry out pedestrian safety analysis and pedestrian friendly design. However, it is too difficult to come across research work related to pedestrian volume analysis in the field of transport, due to lack of interests on pedestrian movement. Most transport research has been focused on vehicles and highways rather than pedestrian. On the other hand, in the field of urban studies, there comes an effective tool to estimate pedestrian volumes using Space Syntax theory. This theory twins out to be effective and economic because it only requires network information, which is easy to acquire from maps and field survey. However, this method is different in the way representing networks from the way that is common in the field of transport. To make up for this point, this paper develops a novel measure for estimating pedestrian volume using Dial's algorithm, and applies the model in the two test networks; Insadong and Soongryemoon networks. The application results reveals that developed measure is an effective tool to explain pedestrian volume; a correlation coefficient between the measure and pedestrian volume is 0.713 in Insadong and 0.492 in Soongryemoon, and the goodness of fit() of regression models are 0.893 in Insadong and 0.671 in Soongryemoon. This estimation method is significantly less complicated to estimate the effect of a pedestrian network change than Space Syntax theory, which requires special softwares not readily available.
Key concepts: Pedestrian, Space syntax, Measure (data warehouse), Computer science, Field (mathematics), Street network, Data mining, Transport engineering