On Street Night Car Parking Demand Estimation in Urban Residential Areas A Case Study in Roorkee and Delhi

Abstract

Nowadays, on-street parking is a challenging issue all around the world, especially in the residential areas during the night and Central Business District (CBD) during the day. The onstreet night parking demand is increasing in residential areas due to the non-availability of sufficient off-street parking facilities on the premises. In this study, three residential areas Ramnagar in Roorkee, Jyoti Nagar and East Loni in Delhi has been selected as the case study newlinearea. Socio-economic, demographic and parking characteristics were used as parameters to generate the parking demand model. The data were collected from the field using in-out, license plate and questionnaire surveys. Key findings revealed that peak parking hours vary from location to location. In Ramnagar the peak parking is found between 1 AM and 2 AM on Wednesdays, Jyoti Nagar from 11 PM to 12 MN on Tuesdays, and East Loni from 2 AM to 3 AM on Mondays and the average occupancy rates were 86.4%, 82.7%, and 81.3% respectively. Parking demand models for Ramnagar, Roorkee, and Jyoti Nagar, Delhi, focusing on socioeconomic factors and pricing policies. In Ramnagar, models with and without parking fees showed R² values of 0.698 and 0.697, with factors like income, trip duration and age influencing demand. In Jyoti Nagar, the inclusion of parking fees improved the model R² from 0.669 to 0.746, highlighting the impact of willingness to pay. Sensitivity analysis has been done using One Factor at a Time (OFAT) analysis to examine the influence of the independent variable on the dependent variable by changing each independent variable. Sensitivity analysis revealed that higher vehicle ownership and parking duration increase demand, while parking fees and search times reduce it. These results underscore the importance of integrating pricing and socioeconomic factors in urban parking management.