Map matching is the problem of how to match recorded geographic coordinates to a logical model of the real world, typically using some form of Geographic Information System. The most common approach is to take recorded, serial location points (e.g. from GPS) and relate them to edges in an existing street graph (network), usually in a sorted list representing the travel of a user or vehicle. Matching observations to a logical model in this way has applications in satellites navigation, GPS tracking of freight, and transportation engineering.
Map matching algorithms can be divided in real-time and offline algorithms. Real-time algorithms associate the position during the recording process to the road network. Offline algorithms are used after the data is recorded and are then matched to the road network.[1] Real-time applications can only calculate based upon the points prior to a given time (as opposed to those of a whole journey), but are intended to be used in 'live' environments. This brings a compromise of performance over accuracy. Offline applications can consider all points and so can tolerate slower performance in favour of accuracy. However, the defects on low accuracy can be reduced due to integration of spatio-temporal proximity and improved weighted circle algorithms.[2]
- ^ Pereira, Francisco Câmara; Costa, Hugo; Pereira, Nuno Martinho (2009-09-11). "An off-line map-matching algorithm for incompletemap databases". European Transport Research Review. 1 (3): 107–124. Bibcode:2009ETRR....1..107P. doi:10.1007/s12544-009-0013-6. hdl:10316/102766. S2CID 56046090. Retrieved 2014-11-23.
- ^ Teng, Wenxin; Wang, Yanhui (8 July 2019). "Real-Time Map Matching: A New Algorithm Integrating Spatio-Temporal Proximity and Improved Weighted Circle". Open Geosciences. 11 (1): 288–297. Bibcode:2019OGeo...11...23T. doi:10.1515/geo-2019-0023.