Privacy preserving origin-destination flow measurement in vehicular cyber-physical systems

Abstract

Traffic volume measurement is one of the most basic functions of road planning and management. In this paper, we investigate an important problem of privacy preserving “point-to-point” traffic volume measurement. We formalize “point-to-point” traffic as an origin-destination (O-D) flow, which represents the set of vehicles traveling from one geographical location (origin) to another location (destination). We take advantage of vehicular cyber-physical systems (VCPS) to exploit the potential for a fundamental shift in the way how O-D data are collected. The challenge is to allow the collection of statistical O-D flow information, yet protect identities of individual vehicles. To address that, we design two novel schemes which utilize both the latest technological advance in VCPS and the nice properties of a family of commutative one-way hash functions. Furthermore, we adopt statistical methodology and use sampling to achieve far better efficiency with graceful degradation in measurement accuracy. We perform simulations to demonstrate the feasibility and scalability of our schemes.