Paper
23 May 2013 Urban multitarget tracking via gas-kinetic dynamics models
Author Affiliations +
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) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ronald Mahler "Urban multitarget tracking via gas-kinetic dynamics models", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450B (23 May 2013); https://doi.org/10.1117/12.2015448
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Cited by 4 scholarly publications.
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KEYWORDS
Electronic filtering

Particles

Motion models

Systems modeling

Filtering (signal processing)

Probability theory

Molecules

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