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Inferring Road Maps from Global Positioning System Traces
| Content Provider | Semantic Scholar |
|---|---|
| Author | Biagioni, James Eriksson, Jakob |
| Copyright Year | 2012 |
| Abstract | As a result of the availability of Global Positioning System (GPS) sensors in a variety of everyday devices, GPS trace data are becoming increasingly abundant. One potential use of this wealth of data is to infer and update the geometry and connectivity of road maps through the use of what are known as map generation or map inference algorithms. These algorithms offer a tremendous advantage when no existing road map data are present. Instead of the expense of a complete road survey, GPS trace data can be used to generate entirely new sections of the road map at a fraction of the cost. In cases of existing maps, road map inference may not only help to increase the accuracy of available road maps but may also help to detect new road construction and to make dynamic adaptions to road closures—useful features for in-car navigation with digital road maps. In past research, proposed algorithms had been evaluated qualitatively with little or no comparison with prior work. This lack of quantitative and comparativ. |
| Starting Page | 61 |
| Ending Page | 71 |
| Page Count | 11 |
| File Format | PDF HTM / HTML |
| DOI | 10.3141/2291-08 |
| Volume Number | 2291 |
| Alternate Webpage(s) | https://www.cs.uic.edu/~jakob/papers/biagioni-trr12.pdf |
| Alternate Webpage(s) | http://www.cs.uic.edu/~jakob/papers/biagioni-trr12.pdf |
| Alternate Webpage(s) | https://doi.org/10.3141/2291-08 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
