| Title |
Traffic Congestion Prediction System Using the Urban Data and Space Syntax |
| Authors |
Song, Yu-Mi ; Kim, Sung-Ah |
| DOI |
http://dx.doi.org/10.5659/JAIK_PD.2016.32.12.91 |
| Keywords |
Prediction Analysis ; Traffic congestion ; Design decision-making ; Urban information ; Public data ; Space syntax |
| Abstract |
Many cars cause the urban problems, such as environmental pollution and safety accidents and traffic congestion. This paper aim to prove that traffic congestion section is predicted by road layout with traffic data. Space syntax is used to find the spatial configuration of road; integration and angular connectivity. And the travel speed and traffic volume data of target road are acquired from public data (open data). Travel speed, traffic volume, integration and angular connectivity are across-correlated. So the relationship among them and the elements which affect the travel speed are founded. And then the regression analysis is implemented to examine that the elements predict the congestion section of road. The result of regression analysis report that vehicle's speed is affected by traffic volume, integration, and angular connectivity. Predicting the traffic congestion using the spatial configuration, people can prepare measures against the traffic congestion of newly constructed road. |