ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ ΕΜΠ Εργαστήριο Συγκοινωνιακής Τεχνικής Χρήση συστημάτων πληροφορικής στην οδική υποδομή Συσχέτιση δεδομένων GPS και χάρτη Βύρωνας Νάκος Καθηγήτης ΕΜΠ bnakos@central.ntua.gr
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Συστήματα Γεωγραφικών Πληροφοριών & Μεταφορές Συσχέτιση δεδομένων GPS και χάρτη (map matching) Βύρωνας Νάκος, Καθηγητής Ε.Μ.Π.
Contents What is map matching? Application area Deterministic map matching Probabilistic map matching
What is map matching? Placing GPS data onto a base map in a GIS may produce a result in which points and arcs are not congruent Map-matching integrates positioning data with spatial road network data to identify the correct link on which a vehicle is travelling and to determine the location of a vehicle on a digital map Map matching results from one of four error sources: Accurate GIS with less accurate GPS points that do not match the GIS base map Accurate GPS data placed into a less accurate GIS base map Accurate GPS data placed into a GIS base map that does not have the features present to accept the GPS data Accurate GPS data placed into a GIS base map that has a scale too small to differentiate the GPS points
The map-matching problem Digital base map GPS data
Application area: Travel surveys Locating travel routes within a digital base map when provided with a route generated from in-vehicle GPS collected points and identifying points that are trip origins and destinations Speed studies Comparing GPS locations along a specified route to predetermined intersection locations on a digital map to calculate travel speed
Application area: Fleet management Identifying the location of a vehicle on a road network Roadway inventory Comparing the alignment of a roadway on an existing 1:24,000 scale digital map and the alignment as shown by GPS points collected at an accuracy of 1 m Incident locations Location of accidents as identified by GPS points and the need to dynamically segment a road network associated with a given location
The two options of map matching On-line scenario Only the current and the previous GPS points are available. Snap GPS positions to the base reference in real-time Off-line scenario All the GPS points are available
Map matching basic steps Matching the output of the navigation system to the road network of the digital map generally involves three steps: 1. A set of candidate segments is selected 2. The likelihood of the candidate segments is evaluated using geometrical and topological information as well as the correlation between the trajectory history of the vehicle and the candidate paths in the map 3. The vehicle location on the most likely road segment is determined
Deterministic map matching (Point-to-point / point-to-curve / curve-to-curve matching) The method assumes an initial vehicle location on a road in the digital base map and a given direction The algorithm then compares turns from the vehicle location to a segment of the digital base map The algorithm must include a distance limit ( about 10 15 m) that will indicate when the vehicle is no longer on the road A correction is made whenever the heading of the vehicle changes
Probabilistic map matching The major advantage of the probabilistic approach is that it does not need to assume the vehicle is on the road A vehicle heading error must be generated into a position determination An elliptical or rectangular confidence region (such as a probability density function) and error models are calculated within which the true vehicle location can be found
Probabilistic map matching If the vehicle position within the region contains one intersection or road segment, a match is made and the coordinates on the road are used in the next position calculation If more than one road or intersection lies within the region, connectivity checks are made to determine the most probable location of the vehicle given earlier vehicle positions Finally, the best match segment is presented to the system along with a most probable matching point on the segment
References Transportation Research Board, 2002, Collecting, Processing, and Integrating GPS data into GIS, NCHRP SYNTHESIS 301, Washington D.C.: National Academy Press. White, C.E., Bernstein D. & Kornhauser A.L., 2000, Some Map Matching Algorithms for Personal Navigation Assistants, Transportation Research Part C: Emerging Technologies, 8(1): 91 108.
Χρηματοδότηση Το παρόν υλικό έχει αναπτυχθεί στα πλαίσια του εκπαιδευτικού έργου του διδάσκοντα. Το έργο υλοποιείται στο πλαίσιο του Επιχειρησιακού Προγράμματος «Εκπαίδευση και Δια Βίου Μάθηση» και συγχρηματοδοτείται από την Ευρωπαϊκή Ένωση (Ευρωπαϊκό Κοινωνικό Ταμείο) και από εθνικούς πόρους. 1