@Article{cmes.2022.017663,
AUTHOR = {Haibao Jiang, Dezhi Han, Han Liu, Jiuzhang Han and Wenjing Nie},
TITLE = {Time Synchronized Velocity Error for Trajectory Compression},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {130},
YEAR = {2022},
NUMBER = {2},
PAGES = {1193--1219},
URL = {http://www.techscience.com/CMES/v130n2/45963},
ISSN = {1526-1506},
ABSTRACT = {Nowadays, distance is usually used to evaluate the error of trajectory compression. These methods can effectively
indicate the level of geometric similarity between the compressed and the raw trajectory, but it ignores the velocity
error in the compression. To fill the gap of these methods, assuming the velocity changes linearly, a mathematical
model called SVE (Time Synchronized Velocity Error) for evaluating compression error is designed, which can
evaluate the velocity error effectively, conveniently and accurately. Based on this model, an innovative algorithm
called SW-MSVE (Minimum Time Synchronized Velocity Error Based on Sliding Window) is proposed, which
can minimize the velocity error in trajectory compression under the premise of local optimization. Two elaborate
experiments are designed to demonstrate the advancements of the SVE and the SW-MSVE respectively. In the
first experiment, we use the PED, the SED and the SVE to evaluate the error under four compression algorithms,
one of which is the SW-MSVE algorithm. The results show that the SVE is less influenced by noise with stronger
performance and more applicability. In the second experiment, by marking the raw trajectory, we compare the
SW-MSVE algorithm with three others algorithms at information retention. The results show that the SW-MSVE
algorithm can take into account both velocity and geometric structure constraints and retains more information
of the raw trajectory at the same compression ratio.},
DOI = {10.32604/cmes.2022.017663}
}