Terrain-based road vehicle localization on multi-lane highways

Adam J. Dean; Sean N. Brennan

doi:10.1109/ACC.2009.5160078

Terrain-based road vehicle localization on multi-lane highways

Adam J. Dean, Sean N. Brennan

Institute for Computational and Data Sciences (ICDS)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Scopus citations

Abstract

This work develops an algorithm for estimating the lateral lane index of road vehicles on multi-lane roadways by correlating vehicle attitude measurements to terrain maps of the individual lanes of travel. To localize a vehicle, a Bayesian belief algorithm and a particle filter algorithm are described and applied off-line using data collected from two lanes along a local highway. Results demonstrate that terrain-based algorithms are capable of measuring lane index. Because these measurements are immune to lighting conditions, this solution is a good complement to existing lane-detection camera systems.

Original language	English (US)
Title of host publication	2009 American Control Conference, ACC 2009
Pages	707-712
Number of pages	6
DOIs	https://doi.org/10.1109/ACC.2009.5160078
State	Published - 2009
Event	2009 American Control Conference, ACC 2009 - St. Louis, MO, United States Duration: Jun 10 2009 → Jun 12 2009

Other

Other	2009 American Control Conference, ACC 2009
Country	United States
City	St. Louis, MO
Period	6/10/09 → 6/12/09

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2009.5160078

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Cite this

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title = "Terrain-based road vehicle localization on multi-lane highways",

abstract = "This work develops an algorithm for estimating the lateral lane index of road vehicles on multi-lane roadways by correlating vehicle attitude measurements to terrain maps of the individual lanes of travel. To localize a vehicle, a Bayesian belief algorithm and a particle filter algorithm are described and applied off-line using data collected from two lanes along a local highway. Results demonstrate that terrain-based algorithms are capable of measuring lane index. Because these measurements are immune to lighting conditions, this solution is a good complement to existing lane-detection camera systems.",

author = "Dean, {Adam J.} and Brennan, {Sean N.}",

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language = "English (US)",

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AB - This work develops an algorithm for estimating the lateral lane index of road vehicles on multi-lane roadways by correlating vehicle attitude measurements to terrain maps of the individual lanes of travel. To localize a vehicle, a Bayesian belief algorithm and a particle filter algorithm are described and applied off-line using data collected from two lanes along a local highway. Results demonstrate that terrain-based algorithms are capable of measuring lane index. Because these measurements are immune to lighting conditions, this solution is a good complement to existing lane-detection camera systems.

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