Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization
Vibrations in road vehicles related to road surface damage have a number of harmful consequences for the health of the occupants and for the components of the vehicle. To mitigate these effects and support timely pavement repairs, continuous road condition monitoring is essential. Vibration-based me...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Measurement: Sensors |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917425000108 |
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| author | Roland Nagy István Szalai |
| author_facet | Roland Nagy István Szalai |
| author_sort | Roland Nagy |
| collection | DOAJ |
| description | Vibrations in road vehicles related to road surface damage have a number of harmful consequences for the health of the occupants and for the components of the vehicle. To mitigate these effects and support timely pavement repairs, continuous road condition monitoring is essential. Vibration-based measurement systems have gained prominence in recent years, but their accuracy can be significantly compromised by vehicle maneuvers, particularly on urban or curvy roads. Despite this, the influence of aggressive maneuvers has largely been overlooked in previous studies. In this paper, we address this gap by presenting a comprehensive investigation into the impact of abrupt maneuvers on vibration-based road quality measurement. We introduce a novel, computationally efficient soft-sensor algorithm that detects and isolates aggressive maneuvers using sensor data from existing road quality measurement systems, classifying them into four categories. This algorithm combines rule-based methods with machine learning, offering enhanced accuracy and lower computational costs compared to alternative approaches. In this way, the overall maneuver classification achieves an accuracy of 93%. By applying the introduced approach to identify and correct the influence of maneuvers, we achieved a 7% increase in accuracy of pavement quality classification in a suburban environment and a 10% increase in an urban environment. The proposed solution can be easily integrated into current vibration-based road quality measurement frameworks, enhancing their performance while maintaining scalability and low operational cost. |
| format | Article |
| id | doaj-art-26be09bc739e4ed7b29527c13fb461b9 |
| institution | Kabale University |
| issn | 2665-9174 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj-art-26be09bc739e4ed7b29527c13fb461b92025-02-11T04:35:28ZengElsevierMeasurement: Sensors2665-91742025-04-0138101816Vehicle maneuver recognition and correction algorithm for road quality measurement system optimizationRoland Nagy0István Szalai1University of Pannonia, Technical Sciences Research and Development Centre, Institute of Mechatronics Engineering and Research, Gasparich Márk st. 18/A, Zalaegerszeg, H-8900, Zala, Hungary; Corresponding author.University of Pannonia, Technical Sciences Research and Development Centre, Institute of Mechatronics Engineering and Research, Gasparich Márk st. 18/A, Zalaegerszeg, H-8900, Zala, Hungary; University of Pannonia, Mechatronics and Measurement Techniques Research Group, Egyetem st. 10, Veszprém, H-8200, Veszprém, HungaryVibrations in road vehicles related to road surface damage have a number of harmful consequences for the health of the occupants and for the components of the vehicle. To mitigate these effects and support timely pavement repairs, continuous road condition monitoring is essential. Vibration-based measurement systems have gained prominence in recent years, but their accuracy can be significantly compromised by vehicle maneuvers, particularly on urban or curvy roads. Despite this, the influence of aggressive maneuvers has largely been overlooked in previous studies. In this paper, we address this gap by presenting a comprehensive investigation into the impact of abrupt maneuvers on vibration-based road quality measurement. We introduce a novel, computationally efficient soft-sensor algorithm that detects and isolates aggressive maneuvers using sensor data from existing road quality measurement systems, classifying them into four categories. This algorithm combines rule-based methods with machine learning, offering enhanced accuracy and lower computational costs compared to alternative approaches. In this way, the overall maneuver classification achieves an accuracy of 93%. By applying the introduced approach to identify and correct the influence of maneuvers, we achieved a 7% increase in accuracy of pavement quality classification in a suburban environment and a 10% increase in an urban environment. The proposed solution can be easily integrated into current vibration-based road quality measurement frameworks, enhancing their performance while maintaining scalability and low operational cost.http://www.sciencedirect.com/science/article/pii/S2665917425000108Vehicle dynamicsManeuver identificationRoad quality measurementVibrationFeature extractionMachine learning |
| spellingShingle | Roland Nagy István Szalai Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization Measurement: Sensors Vehicle dynamics Maneuver identification Road quality measurement Vibration Feature extraction Machine learning |
| title | Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| title_full | Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| title_fullStr | Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| title_full_unstemmed | Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| title_short | Vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| title_sort | vehicle maneuver recognition and correction algorithm for road quality measurement system optimization |
| topic | Vehicle dynamics Maneuver identification Road quality measurement Vibration Feature extraction Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2665917425000108 |
| work_keys_str_mv | AT rolandnagy vehiclemaneuverrecognitionandcorrectionalgorithmforroadqualitymeasurementsystemoptimization AT istvanszalai vehiclemaneuverrecognitionandcorrectionalgorithmforroadqualitymeasurementsystemoptimization |