Paper Info
Title
Genetic algorithms for estimating longest path from inherently fuzzy data acquired with GPS
Abstract
Measuring the length of a path that a taxi must fare is an obvious task: when driving lower than certain speed threshold the fare is time dependent, but at higher speeds the length of the path is measured, and the fare depends on such measure. When passing an indoor MOT test, the taximeter is calibrated simulating a cab run, while the taxi is placed on a device equipped with four rotating steel cylinders in touch with the drive wheels. This indoor measure might be inaccurate, as the information given by the cylinders is affected by tires inflating pressure, and only straight trajectories are tested. Moreover, modern vehicles with driving aids such as ABS, ESP or TCS might have their electronics damaged in the test, since two wheels are spinning while the others are not. To surpass these problems, we have designed a small, portable GPS sensor that periodically logs the coordinates of the vehicle and computes the length of a discretionary circuit. We will show that all the legal issues with the tolerance of such a procedure (GPS data are inherently imprecise) can be overcome if genetic and fuzzy techniques are used to process and analyze the raw data.
Year
DOI
Venue
2006
10.1007/11875581_28
IDEAL
Keywords
Field
DocType
cab run,certain speed threshold,drive wheel,genetic algorithm,fuzzy technique,portable gps sensor,gps data,fuzzy data,longest path,indoor measure,discretionary circuit,indoor mot test,raw data,genetics
Computer science,Simulation,Fuzzy logic,Taximeter,Global Positioning System,Fuzzy number,Longest path problem,Complete information,Trajectory,Genetic algorithm
Conference
Volume
ISSN
ISBN
4224
0302-9743
3-540-45485-3
Citations 
PageRank 
References 
0
0.34
11
Authors
4
Name
Order
Citations
PageRank
José Ramón Villar117627.02
Adolfo Otero2151.71
José Otero355224.66
Luciano Sánchez437726.34