Development of Trip Generation Model of Bharatpur Metropolitan City

Abstract

Trip generation model, first step of four stage travel modelling in transportation system, is useful in predicting total number of trips generated and attracted to each zone based on household data and socio-economic attributes. Main objective of this study is to develop home based trip production model for Bharatpur Metropolitan City (BMC). Multiple linear regression analysis was used with the help of SPSS (Statistical Package of Social Science) to develop a trip production models for different trip purposes. Trip based approach was used in which household interview surveys were done to collect socio- economic as well as other home based trip related data. In this study, different trip generation models such as work trip model, shopping trip model, business trip model, educational trip model and leisure trip model were developed and their validation was checked by using chi-square test. The major conclusions obtained from this study are: Work trip is dominantly affected by number of employees in the house along with other parameters such as number of bicycles, number of four wheelers and low income. House having more number of females, more four wheelers and high income produces more shopping trips whereas greater distance to central business district from house have tendency to reduce shopping trips. Business trip production is influenced by number of own account workers, high income and occupation of main member as own account worker whereas educational trip is largely dependent on the number of students present in the house. Increase in number of family members results more leisure trip from the house. House having greater number of members of age 18 to 60 and greater than 60 year results more leisure trip. Total trip generation is affected by number of family members, number of bicycles, number of two wheelers, number of four wheelers, distance to central business district, number of members of age 18 to 60, number of employees, number of students, number of own account workers and high monthly family income. Outcome of this study is useful for making various decision in planning level of BMC for systematic and planned development of transport related infrastructure in near future.