  Increasingly large trip demands have strained urban transportation capacity,
which consequently leads to traffic congestion and rapid growth of greenhouse
gas emissions. In this work, we focus on achieving sustainable transportation
by incentivizing passengers to switch from private cars to public transport. We
address the following challenges. First, the passengers incur inconvenience
costs when changing their transit behaviors due to delay and discomfort, and
thus need to be reimbursed. Second, the inconvenience cost, however, is unknown
to the government when choosing the incentives. Furthermore, changing transit
behaviors raises privacy concerns from passengers. An adversary could infer
personal information, (e.g., daily routine, region of interest, and wealth), by
observing the decisions made by the government, which are known to the public.
We adopt the concept of differential privacy and propose privacy-preserving
incentive designs under two settings, denoted as two-way communication and
one-way communication. Under two-way communication, passengers submit bids and
then the government determines the incentives, whereas in one-way communication
the government simply sets a price without acquiring information from the
passengers. Under one-way communication, we focus on how the government should
design the incentives without revealing passengers' inconvenience costs while
still preserving differential privacy. We formulate the problem as a convex
program, and propose a differentially private and near-optimal solution
algorithm. A numerical case study using Caltrans Performance Measurement System
(PeMS) data source is presented as evaluation. The results show that the
proposed approaches achieve a win-win situation in which both the government
and passengers obtain non-negative utilities.
