Date of Award

5-15-2009

Degree Type

Thesis

Degree Name

M.S.

Degree Program

Engineering

Department

Civil and Environmental Engineering

Major Professor

Jilkov, Vesselin

Second Advisor

Li, X. Rong

Third Advisor

Chen, Huimin

Abstract

Knowledge of the lane that a target is located in is of particular interest in on-road surveillance and target tracking systems. We formulate the problem and propose two approaches for on-road target estimation with lane tracking. The first approach for lane tracking is lane identification based ona Hidden Markov Model (HMM) framework. Two identifiers are developed according to different optimality goals of identification, i.e., the optimality for the whole lane sequence and the optimality of the current lane where the target is given the whole observation sequence. The second approach is on-road target tracking with lane estimation. We propose a 2D road representation which additionally allows to model the lateral motion of the target. For fusion of the radar and image sensor based measurement data we develop three, IMM-based, estimators that use different fusion schemes: centralized, distributed, and sequential. Simulation results show that the proposed two methods have new capabilities and achieve improved estimation accuracy for on-road target tracking.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.

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