Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Addressing the Need for Map-Matching Speed: Localizing Globalb Curve-Matching Algorithms
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Are GSM Phones THE Solution for Localization?
WMCSA '06 Proceedings of the Seventh IEEE Workshop on Mobile Computing Systems & Applications
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Accurate GSM indoor localization
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Learning and recognizing the places we go
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Mobility detection using everyday GSM traces
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Practical metropolitan-scale positioning for GSM phones
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Mobile task computing: beyond location-based services and ebooks
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
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Tracking data has become a valuable resource for establishing speed profiles for road networks, i.e., travel-time maps. While methods to derive travel time maps from GPS tracking data sources, such as floating car data (FCD), are available, the critical aspect in this process is to obtain amounts of data that fully cover all geographic areas of interest. In this work, we introduce Wireless Positioning Systems (WPS) based on 802.11 networks (WiFi), as an additional technology to extend the number of available tracking data sources. Featuring increased ubiquity but lower accuracy than GPS, this technology has the potential to produce travel time maps comparable to GPS data sources. Specifically, we adapt and apply readily available algorithms for (a) WPS (centroid and fingerprinting) to derive position estimates, and (b) map matching to derive travel times. Further, we introduce map matching as a means to improve WPS accuracy. We present an extensive experimental evaluation on real data comparing our approach to GPS-based techniques. We demonstrate that the exploitation of WPS tracking data sources is feasible with existing tools and techniques.