Balance of Car Ownership under User Demand and Road Network Supply Conditions—Case Study in Hong Kong

Abstract

In this paper we present a new concept for balancing car ownership from both user demand and road network supply conditions. On the demand side, territory-wide and zonal car ownership is first estimated by an aggregate and a disaggregate car ownership models, respectively. A simulated probability distribution of the territory-wide car ownership is also established to assess the reliability of the estimated car ownership. From the road network supply conditions, the maximum number of cars by zone is determined in view of the capacity of the road network and the number of available parking spaces by a bilevel programming model. The proposed bilevel programming model is aimed at examining whether existing road network supply conditions are capable for accommodating future zonal car ownership growth. A case study in a Hong Kong urban area is presented to integrate the results of user demand and network supply conditions to obtain the balance of territory-wide car ownership. The balanced car ownership is found to be the most efficient scenario in terms of total network travel time and utilization of network facilities.