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Proceedings Paper

Probability hypothesis density tracking for interacting vehicles in traffic
Author(s): R. K. Prasanth; H. Hoang
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Paper Abstract

Recent work has shown that the random finite set (RFS) approach to multi-target tracking is a computationally viable alternative to the traditional data association based approaches. An assumption in these approaches is that the targets move independently of each other. In this paper, we introduce the concept of a random finite graph and study its application to the tracking of interacting vehicles in traffic. A random finite graph is a random variable taking values in the set of finite directed graphs. The graph describes the influence of vehicles on the motion of other vehicles. The connected components of the graph define groups of vehicles that move independently of other groups. We treat the connected components as the independent entities upon which to perform RFS-based tracking. The approach is illustrated with an arterial traffic simulation in which vehicles interact among themselves through car-following and with traffic control devices at intersections.

Paper Details

Date Published: 17 May 2012
PDF: 10 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920J (17 May 2012); doi: 10.1117/12.919544
Show Author Affiliations
R. K. Prasanth, BAE Systems (United States)
H. Hoang, BAE Systems (United States)


Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)

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