A Differentially Private Incentive Design for Traffic Offload to Public Transportation
A Differentially Private Incentive Design for Traffic Offload to Public Transportation
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DOI：
10.1145/3430847
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发表时间：
2019-06
影响因子：
2.3
通讯作者：
Luyao Niu;Andrew Clark
中科院分区：
文献类型：
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作者：
Luyao Niu;Andrew Clark
日益增长的出行需求使城市交通能力紧张，从而导致交通拥堵和温室气体排放的快速增长。在这项工作中，我们专注于通过激励乘客从私人汽车转向公共交通工具来实现可持续交通。我们应对以下挑战。首先，乘客因延误和不适而改变其交通行为时产生的不便成本，因此需要得到补偿。第二，政府在选择激励措施时不知道不便成本。此外，不断变化的交通行为引起了乘客的隐私问题。对手可以推断个人信息（例如，日常事务，兴趣区域和财富）通过观察政府所做的决定，这是公众所知道的。我们采用差分隐私的概念，并提出了隐私保护的激励设计在两种情况下，表示为双向通信和单向通信。在双向沟通中，乘客提交投标，然后政府确定激励措施，而在单向沟通中，政府只是设定价格，而不从乘客那里获得信息。我们将双向通信下的问题表示为一个混合整数线性规划，并提出了一个多项式时间近似算法。我们表明，所提出的方法实现了真实性，个人理性，社会最优性和差异隐私。在单向沟通下，我们关注的是政府应该如何设计激励措施，而不透露乘客的不便成本，同时仍然保护差异隐私。我们制定的问题作为一个凸规划，并提出了一个差分私人和近最优解算法。一个数值的案例研究，使用加州运输绩效测量系统（PeMS）的数据源作为评估。结果表明，所提出的方法实现了政府和乘客都获得非负效用的双赢局面。
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. We formulate the problem under two-way communication as a mixed integer linear program and propose a polynomial-time approximation algorithm. We show the proposed approach achieves truthfulness, individual rationality, social optimality, and differential privacy. 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 the 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.