2015
DOI: 10.1007/978-3-319-24770-0_43
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Identifying Road Artefacts with Mobile Devices

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Cited by 5 publications
(8 citation statements)
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“…The next virtual road segments, described in the Table 4, built upon rubble road fragments, should be much higher, which is correct again, with values ranging from 23 to even 50. To check an another algorithm, the road artefact detection method using the modified Z-STDEV method [8] was performed on the same virtual road as before. Using these methods, road artefacts which were included in the virtual road (on position of 6th, 17th and 21st segment, respectively), were detected with one false positive in data point number 106, which is in a second good road segment (class A, variant b).…”
Section: Resultsmentioning
confidence: 99%
See 4 more Smart Citations
“…The next virtual road segments, described in the Table 4, built upon rubble road fragments, should be much higher, which is correct again, with values ranging from 23 to even 50. To check an another algorithm, the road artefact detection method using the modified Z-STDEV method [8] was performed on the same virtual road as before. Using these methods, road artefacts which were included in the virtual road (on position of 6th, 17th and 21st segment, respectively), were detected with one false positive in data point number 106, which is in a second good road segment (class A, variant b).…”
Section: Resultsmentioning
confidence: 99%
“…There are also works covering road quality calculation from accelerometer data [3,4], especially in the crowdsourcing manner [5,6] Finally, there are also discussed proposals of creation of road artefacts database for further reuse [7]. The authors were discussing usage of streaming analytics in the cloud computer pattern for such a research, as well as described road artefact detection algorithms [8,9].…”
Section: Similar Researchmentioning
confidence: 99%
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