Urban multitarget tracking via gas-kinetic dynamics models

Abstract

Multitarget tracking in urban environments presents a major theoretical and practical challenge. A recently suggested approach is that of modeling traffic dynamics using the fluid-kinetic methods of traffic-flow theory (TFT). I propose use of the newer, more general, gas-kinetic (GK) approach to TFT. In GK, traffic flow is modeled as a one- or two-dimensional constrained gas. The paper demonstrates the following. (1) The foundational concept in GK-the "phase-space density"-is the same thing as the probability hypothesis density (PHD) of multitarget tracking theory. (2) The theoretically best-that-one-can do approach to TFT-based tracking is a PHD filter. (3) Better performance can be obtained by augmenting this PHD filter as a cardinalized PHD (CPHD) filter. A simple example is presented to illustrate how PHD/CPHD filters can be integrated with conventional macroscopic, mesoscopic, and microscopic TFT. © 2013 SPIE.