There are many R&D improvements on positioning systems for ITS (intelligent transportation systems) adopting GPS, cellular phones or other communication systems. But, a position from any signal is always corrupted to a few meters through several hundreds of meters because of multipath, atmospheric delay, NLOS (non-line-of-sight), low DOP and so on. When the positioning systems are employed for ITS, a digital road map can be used together to display their navigation solutions in most ITS applications. Due to the fact that land-vehicles almost always run on roads, most of CNS (car navigation systems) translate the measured position onto a road. This methodology called map-matching, if it depends on a contaminated position due to white noise and biased error, has not only low accuracy but also the road ambiguity problems in some crossroads. Therefore, this paper presents an efficient use of an advanced map-matching in order to get a more improved accuracy, which estimates a large bias being the main source of errors and corrects a vehicle's position. It is composed of a modeling of biased error and filtering by a Kalman filter. We have applied the proposed map-matching to not only GPS navigation but also CDMA location. The proposed approach represents that in addition to its original visual display, an accurate digital road-map can improve the positioning accuracy effectively by correcting the vehicle's position.
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Kim et al. (2002) studied this question.
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