《Hidden Markov Map Matching Through Noise and Sparseness》读书笔记

摘要

Our test shows how the algorithm breaks down as the sampling rate of the GPS is reduced. We also test the effect of increasing amounts of additional measurement noise in order to assess how well our algorithm could deal with the inaccuracies of other location measurement systems, such as those based on WiFi and cell tower multilateration. （这是本文的一个中心，测试频率变化和噪声对算法准确性的影响）

Our second contribution is a test of our map matching algorithm where we vary the levels of noise and sparseness of the sensed location data over a 50 mile urban drive（测试方式）

There is a feasible driving path, possibly very circuitous, from each of the nearest points on these three roads to points on the two roads near 𝑧2 at 𝑡 = 2, and similarly for 𝑡 = 3. The goal of our algorithm is to find the most probable path through the lattice by picking one road segment for each 𝑡. （如果只是最短距离的匹配，那么第二、第三个点将匹配错误）

One potential problem with purely