How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs
As a major component of riding comfort, surface roughness has a significant impact on peoples' decision to ride bicycles. Riding comfort is most commonly derived from accelerations measured by inertial measurement units (IMUs). However, roughness metrics from different works are not directly c...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Technology and Society, Faculty of Engineering, LTH, Lund University
2024-12-01
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| Series: | Traffic Safety Research |
| Subjects: | |
| Online Access: | https://tsr.international/TSR/article/view/26031 |
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| _version_ | 1846118639059599360 |
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| author | Moritz Beeking Hannah Wies Markus Steinmaßl Karl Rehrl |
| author_facet | Moritz Beeking Hannah Wies Markus Steinmaßl Karl Rehrl |
| author_sort | Moritz Beeking |
| collection | DOAJ |
| description |
As a major component of riding comfort, surface roughness has a significant impact on peoples' decision to ride bicycles. Riding comfort is most commonly derived from accelerations measured by inertial measurement units (IMUs). However, roughness metrics from different works are not directly comparable as no ‘benchmark data’ exists. This work aims at alleviating this problem by comparing several well-established methods from literature on the same data. Furthermore, to quantify the effect of different sensor systems, for each test run data from both a smartphone and an industrial grade IMU were collected. To compare the derived roughness measurements, the reliability and stability of each sensor-method combination is calculated using non-parametric statistics. The results indicate handlebar mounted smartphones to be sufficient for surface roughness assessment. Furthermore, the selected roughness calculation method has the biggest impact on resulting assessments, above the impacts of both sensor and analyzed segment length. Based on the results, recommendations for surface roughness assessment are provided in the conclusion.
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| format | Article |
| id | doaj-art-58c32935bb3346bfb31ae2b4be4635f5 |
| institution | Kabale University |
| issn | 2004-3082 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Technology and Society, Faculty of Engineering, LTH, Lund University |
| record_format | Article |
| series | Traffic Safety Research |
| spelling | doaj-art-58c32935bb3346bfb31ae2b4be4635f52024-12-17T13:09:40ZengTechnology and Society, Faculty of Engineering, LTH, Lund UniversityTraffic Safety Research2004-30822024-12-01710.55329/guai2275How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUsMoritz Beeking0https://orcid.org/0000-0002-7870-8127Hannah Wies1https://orcid.org/0009-0007-9169-1538Markus Steinmaßl2https://orcid.org/0000-0001-9407-9570Karl Rehrl3https://orcid.org/0000-0003-4052-5867Salzburg Research Forschungsgesellschaft mbH, AustriaSalzburg Research Forschungsgesellschaft mbH, AustriaSalzburg Research Forschungsgesellschaft mbH, AustriaSalzburg Research Forschungsgesellschaft mbH, Austria As a major component of riding comfort, surface roughness has a significant impact on peoples' decision to ride bicycles. Riding comfort is most commonly derived from accelerations measured by inertial measurement units (IMUs). However, roughness metrics from different works are not directly comparable as no ‘benchmark data’ exists. This work aims at alleviating this problem by comparing several well-established methods from literature on the same data. Furthermore, to quantify the effect of different sensor systems, for each test run data from both a smartphone and an industrial grade IMU were collected. To compare the derived roughness measurements, the reliability and stability of each sensor-method combination is calculated using non-parametric statistics. The results indicate handlebar mounted smartphones to be sufficient for surface roughness assessment. Furthermore, the selected roughness calculation method has the biggest impact on resulting assessments, above the impacts of both sensor and analyzed segment length. Based on the results, recommendations for surface roughness assessment are provided in the conclusion. https://tsr.international/TSR/article/view/26031cycling comfortinertial measurement unit (IMU)infrastructure assessmentsensor bikesurface roughness |
| spellingShingle | Moritz Beeking Hannah Wies Markus Steinmaßl Karl Rehrl How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs Traffic Safety Research cycling comfort inertial measurement unit (IMU) infrastructure assessment sensor bike surface roughness |
| title | How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs |
| title_full | How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs |
| title_fullStr | How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs |
| title_full_unstemmed | How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs |
| title_short | How smooth is your ride? Comparison of sensors and methods for surface quality assessment using IMUs |
| title_sort | how smooth is your ride comparison of sensors and methods for surface quality assessment using imus |
| topic | cycling comfort inertial measurement unit (IMU) infrastructure assessment sensor bike surface roughness |
| url | https://tsr.international/TSR/article/view/26031 |
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