Shared vehicle systems like bike-sharing, car-sharing and ride sharing have be-come an essential part of the urban transit system. Ride-sharing services provided by companies like Uber or Lyft make it easier for those who are unable to operate a personal vehicle in big cities like NYC to find a ride with a lower price. This study demonstrates the advantages of the ride sharing service compared to the ordinary non-shared ride service based on the simulation model of both systems. This study also illustrates a method to optimize the ride sharing systems by utilizing an individualist pricing strategy. An optimal discount foreach ride sharing request to maximize the total expected profit of the system can be found based on the decision tree model and discrete choice model implemented in this study. The purpose of the decision tree model is to determine whether a ride-sharing request can be shared with others in the system while the discrete choice model is used to estimate the passenger’s willingness to accept a certain price for the ride-sharing service. These two factors are of vital importance when calculating the expected profit of serving a request.The individual pricing strategy makes the price of the ride-sharing service more rational according to the features of the requests and thus can be an efficient way to attract more potential customers.