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With the rapid development of autonomous vehicle technology, modern taxi services will potentially witness an important revolution, where some regular cabs will be substituted by self-driving taxis. In this study, we propose a hybrid taxi recommendation system where both autonomous and human-driven ride-hailing vehicles are guided in order to meet the needs of taxi customers as well as the expectation of human drivers. Customers desire to wait the minimum time before finding a taxi, while drivers aim to maximize their profits by speeding up their customer hunting. Autonomous taxis are used to back-up human-driven taxis in areas where customers' demand levels are low. Three major components compose our system: a taxi demand predictor, taxi-to-region assigner, and taxi routing optimizer. Our simulation model is applied on the borough of Manhattan, New York City (NYC), and is validated with realistic data …