Mode Choice Modeling to Shift Car Travelers towards Park and Ride Service in the City Centre of Karachi

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Currently, congestion in Karachi’s central business district (CBD) is the result of people driving their cars to work. Consequently, a park and ride (P&R) service has proved successful in decreasing traffic congestion and the difficulty of finding parking spaces from urban centers. The travelers cannot be convinced to shift towards the P&R service without an understanding of their travel behavior. Therefore, a travel behavior survey needs to be conducted to reduce the imbalance between public and private transport. Hence, mode choice models were developed to determine the factors that influence single-occupant vehicle (SOV) travelers’ decision to adopt the P&R service. Data were collected by an adapted self-administered questionnaire. Mode choice models were developed through logistic regression modeling by using the Statistical Package for the Social Sciences version 22. The findings concluded that more than 70%, specifically motorbike users, to avoid mental stress, and to protect the environment are willing to adopt the P&R service. Moreover, to validate the mode choice models, logit model training and a testing approach were used. In conclusion, by overcoming these influencing factors and balancing push and pull measures of travel demand management (TDM), SOV users can be encouraged to shift towards P&R services. Thus, research outcomes can support policymakers in implementing sustainable modes of public transportation.