Developing a Model to Predict Pedestrian Movement in Urban Spaces by Incorporating Space Syntax and EPR: Case Study Khazaneh Neighborhood in City of Tehran-Iran

Abstract:     
Predicting intensity and various uses of urban open spaces is an important urban open space management issue. Also, it is an important challenge for urban planners and designers to pursue their goals in urban environment. In a research that examines the use of urban spaces in zone 16 of city of Tehran, the capital city of Iran a predictive model has been developed using Space Syntax method and Evolutionary Polynomial Regression. An encounter model has been used to survey the pedestrian movement in the city.

Several research experiments indicated that space syntax technique can develop models that can interpret and predict pedestrian movement in regard to urban morphology, regardless of this capability it has some shortcoming, that is not able to specify the effect of all dependent and independent variables and their combination as a factor on pedestrian movements. To overcome this shortcoming Evolutionary Polynomial Regression has been utilized.

Number of Pages in PDF File: 14

Keywords: Space Syntax, and Evolutionary Polynomial Regression, pedestrian, urban space, Tehran

Accepted Paper Series