14. A method for increasing route accuracies, the method comprising: receiving a first GPS waypoint and a first position accuracy prediction (PAP) parameter, wherein the first PAP parameter comprises a first quality parameter set having a first weight value, a first confidence value for the first GPS waypoint, and a first error distance for the first GPS waypoint; reading, with a computer processor, corpus route data from a computer readable medium, the corpus route data comprising a corpus GPS waypoint and an associated corpus PAP parameter, wherein the corpus PAP parameter comprises a second quality parameter set having a second weight value, a second confidence value for the corpus GPS waypoint, and a second error distance for the corpus GPS waypoint; calculating a weight average based on a ratio of the first weight value of the first quality parameter set and the second weight value of the second quality parameter set; computationally extending the first error distance from the PAP parameter of the first GPS waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus GPS waypoint to provide a second probability distribution circle; and computationally generating a vector line between the first GPS waypoint and the corpus GPS waypoint; determining, with the computer processor, an updated GPS waypoint along the vector line between the first GPS waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average; replacing the corpus GPS waypoint with the updated GPS waypoint; adding the first weight value and the second weight value to attain a summed weight value; and replacing the second weight value in the second quality parameter set with the summed weight value.
15. The method of claim 14 , and further comprising: comparing the first confidence value of the first quality parameter set to the second confidence value of the second quality parameter set; and comparing the first error distance of the first quality parameter set to the first error distance of the second quality parameter set.