Vision-Based Detection of Personal Rapid Transit Guideway

AJ Peters; T Ross-Martin; AM Achim

Vision-Based Detection of Personal Rapid Transit Guideway

AJ Peters, T Ross-Martin, AM Achim

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

ULTra is a system of autonomous vehicles operating on a segregated guideway. The existing navigation system requires the use of raised kerbs to assess the vehicles position within the guideway. A vision-based system has the potential to be more flexible by sensing markings on the ground. It could also assist future obstacle detection systems. This paper implements three well known lane detection approaches developed for roads using images from a personal rapid transit (PRT) guideway. The Hough transform technique is found to be the least accurate, the LOIS algorithm is found to have reasonable performance and the RALPH algorithm is found to be the most accurate and robust to noise.

Translated title of the contribution	Vision-Based Detection of Personal Rapid Transit Guideway
Original language	English
Title of host publication	6th International Symposium on Image and Signal Processing and Analysis, Salzburg
Pages	164 - 169
Number of pages	6
Publication status	Published - Sep 2009

Bibliographical note

Conference Organiser: Co-sponsorship: EURASIP, IEEE Region 8, IEEE Austria Section

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Cite this

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title = "Vision-Based Detection of Personal Rapid Transit Guideway",

abstract = "ULTra is a system of autonomous vehicles operating on a segregated guideway. The existing navigation system requires the use of raised kerbs to assess the vehicles position within the guideway. A vision-based system has the potential to be more flexible by sensing markings on the ground. It could also assist future obstacle detection systems. This paper implements three well known lane detection approaches developed for roads using images from a personal rapid transit (PRT) guideway. The Hough transform technique is found to be the least accurate, the LOIS algorithm is found to have reasonable performance and the RALPH algorithm is found to be the most accurate and robust to noise.",

author = "AJ Peters and T Ross-Martin and AM Achim",

note = "Conference Organiser: Co-sponsorship: EURASIP, IEEE Region 8, IEEE Austria Section",

year = "2009",

month = sep,

language = "English",

pages = "164 -- 169",

booktitle = "6th International Symposium on Image and Signal Processing and Analysis, Salzburg",

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T1 - Vision-Based Detection of Personal Rapid Transit Guideway

AU - Peters, AJ

AU - Ross-Martin, T

AU - Achim, AM

N1 - Conference Organiser: Co-sponsorship: EURASIP, IEEE Region 8, IEEE Austria Section

PY - 2009/9

Y1 - 2009/9

N2 - ULTra is a system of autonomous vehicles operating on a segregated guideway. The existing navigation system requires the use of raised kerbs to assess the vehicles position within the guideway. A vision-based system has the potential to be more flexible by sensing markings on the ground. It could also assist future obstacle detection systems. This paper implements three well known lane detection approaches developed for roads using images from a personal rapid transit (PRT) guideway. The Hough transform technique is found to be the least accurate, the LOIS algorithm is found to have reasonable performance and the RALPH algorithm is found to be the most accurate and robust to noise.

AB - ULTra is a system of autonomous vehicles operating on a segregated guideway. The existing navigation system requires the use of raised kerbs to assess the vehicles position within the guideway. A vision-based system has the potential to be more flexible by sensing markings on the ground. It could also assist future obstacle detection systems. This paper implements three well known lane detection approaches developed for roads using images from a personal rapid transit (PRT) guideway. The Hough transform technique is found to be the least accurate, the LOIS algorithm is found to have reasonable performance and the RALPH algorithm is found to be the most accurate and robust to noise.

M3 - Conference Contribution (Conference Proceeding)

SP - 164

EP - 169

BT - 6th International Symposium on Image and Signal Processing and Analysis, Salzburg

ER -