TY - JOUR
T1 - Some map matching algorithms for personal navigation assistants
AU - White, Christopher E.
AU - Bernstein, David
AU - Kornhauser, Alain L.
N1 - Funding Information:
This research was sponsored by the NJ Center for Transportation Information and Decision Engineering (www.njtide.org) and the NJ Commission on Science and Technology. The authors would like to thank the anonymous referees for helpful comments on an earlier draft of this paper.
PY - 2000
Y1 - 2000
N2 - Third-generation personal navigation assistants (PNAs) (i.e., those that provide a map, the user's current location, and directions) must be able to reconcile the user's location with the underlying map. This process is known as map matching. Most existing research has focused on map matching when both the user's location and the map are known with a high degree of accuracy. However, there are many situations in which this is unlikely to be the case. Hence, this paper considers map matching algorithms that can be used to reconcile inaccurate locational data with an inaccurate map/network.
AB - Third-generation personal navigation assistants (PNAs) (i.e., those that provide a map, the user's current location, and directions) must be able to reconcile the user's location with the underlying map. This process is known as map matching. Most existing research has focused on map matching when both the user's location and the map are known with a high degree of accuracy. However, there are many situations in which this is unlikely to be the case. Hence, this paper considers map matching algorithms that can be used to reconcile inaccurate locational data with an inaccurate map/network.
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U2 - 10.1016/S0968-090X(00)00026-7
DO - 10.1016/S0968-090X(00)00026-7
M3 - Article
AN - SCOPUS:0033804494
SN - 0968-090X
VL - 8
SP - 91
EP - 108
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
IS - 1-6
ER -