Visual Odometry Based Vehicle Lane-changing Detection

Lane-changing detection is necessary for accurate positioning, to allow vehicle navigation system to generate more specific path planning. Lane-changing detection method in this paper is more of a deterministic task, proposed based on curve analysis obtained from visual odometry. From the visual...

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Main Authors: Dayang Nur Salmi Dharmiza, Awang Salleh, Seignez, Emmanuel, Kuryati, Kipli
Format: Proceeding
Language:English
Published: 2022
Subjects:
Online Access:http://ir.unimas.my/id/eprint/40423/1/Visual%20Odometry%20Based%20Vehicle.pdf
http://ir.unimas.my/id/eprint/40423/
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Institution: Universiti Malaysia Sarawak
Language: English
id my.unimas.ir.40423
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spelling my.unimas.ir.404232022-11-11T08:09:37Z http://ir.unimas.my/id/eprint/40423/ Visual Odometry Based Vehicle Lane-changing Detection Dayang Nur Salmi Dharmiza, Awang Salleh Seignez, Emmanuel Kuryati, Kipli TK Electrical engineering. Electronics Nuclear engineering Lane-changing detection is necessary for accurate positioning, to allow vehicle navigation system to generate more specific path planning. Lane-changing detection method in this paper is more of a deterministic task, proposed based on curve analysis obtained from visual odometry. From the visual odometry trajectory, we have the estimation of vehicle lateral/longitudinal position, yaw, and speed. We also used the road lane information from digital map provided by OpenStreetMap to narrow the lane-changing event possibility. The analysis is conducted on sequences from KITTI dataset that contains lane-changing scenarios to study the potential of lanechanging detection by using visual odometry trajectory curve. Cumulative sum and curve fitting methods were utilized for the lane-changing detection from visual odometry curve. The detection was conducted on several visual odometry approaches for comparison and system feasibility. Our analysis shows that trajectory generated by visual odometry is highly potential for a low-cost and effective lane-changing detection with 90.9% precision and 93.8% recall accuracy to complement more accurate routing service and safety application in Advanced Driver Assistance System. 2022 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/40423/1/Visual%20Odometry%20Based%20Vehicle.pdf Dayang Nur Salmi Dharmiza, Awang Salleh and Seignez, Emmanuel and Kuryati, Kipli (2022) Visual Odometry Based Vehicle Lane-changing Detection. In: 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 13 - 15 September 2022, Kota Kinabalu, Malaysia.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Dayang Nur Salmi Dharmiza, Awang Salleh
Seignez, Emmanuel
Kuryati, Kipli
Visual Odometry Based Vehicle Lane-changing Detection
description Lane-changing detection is necessary for accurate positioning, to allow vehicle navigation system to generate more specific path planning. Lane-changing detection method in this paper is more of a deterministic task, proposed based on curve analysis obtained from visual odometry. From the visual odometry trajectory, we have the estimation of vehicle lateral/longitudinal position, yaw, and speed. We also used the road lane information from digital map provided by OpenStreetMap to narrow the lane-changing event possibility. The analysis is conducted on sequences from KITTI dataset that contains lane-changing scenarios to study the potential of lanechanging detection by using visual odometry trajectory curve. Cumulative sum and curve fitting methods were utilized for the lane-changing detection from visual odometry curve. The detection was conducted on several visual odometry approaches for comparison and system feasibility. Our analysis shows that trajectory generated by visual odometry is highly potential for a low-cost and effective lane-changing detection with 90.9% precision and 93.8% recall accuracy to complement more accurate routing service and safety application in Advanced Driver Assistance System.
format Proceeding
author Dayang Nur Salmi Dharmiza, Awang Salleh
Seignez, Emmanuel
Kuryati, Kipli
author_facet Dayang Nur Salmi Dharmiza, Awang Salleh
Seignez, Emmanuel
Kuryati, Kipli
author_sort Dayang Nur Salmi Dharmiza, Awang Salleh
title Visual Odometry Based Vehicle Lane-changing Detection
title_short Visual Odometry Based Vehicle Lane-changing Detection
title_full Visual Odometry Based Vehicle Lane-changing Detection
title_fullStr Visual Odometry Based Vehicle Lane-changing Detection
title_full_unstemmed Visual Odometry Based Vehicle Lane-changing Detection
title_sort visual odometry based vehicle lane-changing detection
publishDate 2022
url http://ir.unimas.my/id/eprint/40423/1/Visual%20Odometry%20Based%20Vehicle.pdf
http://ir.unimas.my/id/eprint/40423/
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