Volume 35, Issue 1, 2026
DOI: 10.53555/03276716.2026.03
Development of a Behavior-Based Parking Demand Model Integrating Driver Psychology and Statistical Analysis: A Case Study of Shopping Malls in Chennai
Abstract
The high rate of urbanization and rise of vehicles in urban areas such as Chennai have increased the demand for parking significantly and have resulted in congestion and inefficient parking controls. The conventional parking demand models mainly emphasize the physical factors and do not take into account the psychology and behavior of drivers. The model of behavioral parking demand that is developed in this paper is a combination of both the psychological and physical variables. The information was gathered using survey and field study in the chosen shopping malls. The key psychological variables included willingness to pay, stress associated with parking, perceived safety, and the tolerance of walking distance, and the variables of parking supply, travel time, and parking charges were also examined. The underlying factors were identified with Factor Analysis, and the Multiple Linear Regression (MLR) was applied to create a predictive model. The findings indicate that driver psychology is important in increasing the accuracy of parking demand estimation. The research offers valuable information on efficient parking management and policymaking in cities.
Keywords
Parking Demand; Driver Psychology; Behavioural Analysis; Parking Choice Behaviour; Multiple Linear Regression (MLR); Parking management; User Perception.