Analysis of time- and space-domain sampling for probe vehicle-based traffic information system

Abstract

Using vehicles as probes is a flexible and low-cost way to obtain real-time traffic information. A key problem of using probe vehicles is to determine vehicle's sampling period and probe sample size. This paper addresses the sampling issue of using probe vehicles for detecting traffic information. An extended Nyquist sampling theorem based on signal processing theory is proposed to derive bounds on the sampling period and probe sample size. We also develop a Traffic & Information-collecting Simulation Platform (TISP), to simulate the traffic flows in a road network and generate probe vehicle data for analysis. We demonstrate through simulations that the traffic situations can be reconstructed from the samples without distortion according to the designed sampling period and sample size. The methods proposed in this paper can be a valuable tool for designers on planning parameters in the probe vehicle-based traffic information system.