Towards Incentive Mechanism for Taxi Services Allocation with Privacy Guarantee

With the development of online taxi-hailing systems (DiDi, Uber Lyft, etc.), how to effectively allocate taxis has attracted great attention in the recent past. Meanwhile, with the rapid increase of taxi-related crimes, the privacy of passengers' sensitive information such as location remains a critical concern. In this paper, we present a novel incentive-based scheme, which provides the differential privacy guarantee for passengers' locations in taxi-hailing systems. To be specific, to allocate limited taxis to passengers, we first present the Vickrey-Clarke-Groves (VCG)-based online auction mechanism for determining the winning passengers. Then, to match the taxis and winning passengers as well as to protect the location privacy of passengers, we present the new allocating rule based on the exponential differential privacy-based mechanism. Further, we prove that the proposed incentive-based scheme satisfies both economic properties and 2-ϵ differential privacy guarantee. Finally, we evaluate the performance of our proposed scheme. The experimental data confirms that our proposed scheme not only achieves better performance than the two baseline schemes with respect to social welfare and satisfaction ratio, but also is capable of protecting the location privacy of passengers with low privacy disclosure.