| dc.contributor.author | Bridgelall, Raj | |
| dc.contributor.author | Tolliver, Denver D. | |
| dc.description.abstract | Transportation agencies cannot afford to scale existing methods of roadway and railway condition monitoring to more frequently detect, localize, and fix anomalies throughout networks. Consequently, anomalies such as potholes and cracks develop between maintenance cycles and cause severe vehicle damage and safety issues. The need for a lower-cost and more-scalable solution spurred the idea of using sensors on board vehicles for a continuous and network-wide monitoring approach. However, the timing of the full adoption of connected vehicles is uncertain. Therefore, researchers used smartphones to evaluate a variety of methods to implement the application using regular vehicles. However, the poor accuracy of standard positioning services with low-cost geospatial positioning system (GPS) receivers presents a significant challenge. The experiments conducted in this research found that the error spread can exceed 32 m, and the mean localization error can exceed 27 m at highway speeds. Such large errors can make the application impractical for widespread use. This work used statistical techniques to inform a model that can provide more accurate localization. The proposed method can achieve sub-meter accuracy from participatory vehicle sensors by knowing only the mean GPS update rate, the mean traversal speed, and the mean latency of tagging accelerometer samples with GPS coordinates. | en_US |
| dc.rights | In copyright. Permission to make this version available has been granted by the author and publisher. | |
| dc.title | Accuracy Enhancement of Anomaly Localization with Participatory Sensing Vehicles | en_US |
| dc.type | Article | en_US |
| dc.description | Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM). | en_US |
| dc.date.accessioned | 2021-08-03T20:03:05Z | |
| dc.date.available | 2021-08-03T20:03:05Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://hdl.handle.net/10365/31977 | |
| dc.subject | Crowdsourced sensing. | en_US |
| dc.subject | GPS tagging latency. | en_US |
| dc.subject | GPS errors. | en_US |
| dc.subject | GPS resolution. | en_US |
| dc.subject | Low-cost GPS. | en_US |
| dc.subject | Pothole detection. | en_US |
| dc.subject | Roadway anomalies. | en_US |
| dc.subject | Railway anomalies. | en_US |
| dc.subject | Standard positioning service. | en_US |
| dc.identifier.orcid | 0000-0003-3743-6652 | |
| dc.identifier.orcid | 0000-0002-8522-9394 | |
| dc.identifier.citation | Bridgelall, Raj, and Denver Tolliver. 2020. "Accuracy Enhancement of Anomaly Localization with Participatory Sensing Vehicles" Sensors 20, no. 2: 409. https://doi.org/10.3390/s20020409 | en_US |
| dc.description.uri | https://www.ugpti.org/about/staff/viewbio.php?id=79 | |
| dc.language.iso | en_US | en_US |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.contributor.organization | Upper Great Plains Transportation Institute | |
| ndsu.college | College of Business | |
| ndsu.department | Transportation and Logistics | |
| dc.identifier.doi | 10.3390/s20020409 | |
