MINIMUM TAXI FLEET ALGORITHM CONSIDERING HUMAN SPATIOTEMPORAL BEHAVIORS

Abstract

Taxis play an important role in providing passenger mobility in many cities of the world. In a recent IRU/EU report taxis are considered as part of the collective public transport chain. The Land Transport Authority in Singapore states clearly in their website that while public transport is the most efficient means of travel, taxis bridge the gap between commuting and driving a car. In this context taxis can be considered as a complementary mobility option to public transport rather than as a competitive one. Currently many cities in the world have taxi fleets, where taxis are utilized by many local and foreign residences as well as by tourists and visitors. Riding a taxi should be a pleasant, comfortable, convenient and relatively affordable experience. In order for cities to continue providing acceptable taxi level of service the taxi fleet has to increase to meet the expected demand. The literature shows a limited number of taxi fleet prediction techniques. Towards this end this research identifies and reviews a number of taxi fleet prediction models, namely the model based on taxi availability indicator, the Hara model. The research further develops a generic algorithm of algebraic equations to estimate future taxi fleet requirements in cities of the world. This research demonstrates the utilization of the 3 models in estimating future taxi fleet requirement in a hypothetical city case study.