@article {VILLAR2009250,
	title = {Taximeter verification using imprecise data from GPS},
	journal = {Engineering Applications of Artificial Intelligence},
	volume = {22},
	number = {2},
	year = {2009},
	pages = {250 - 260},
	abstract = {Until recently, local governments in Spain were using machines with rolling cylinders for testing and verification of taximeters. However, the tyres condition can lead to errors in the process and the mechanical construction of the test equipment is not compatible with certain vehicles. Thus, a new measurement device should be designed. In our opinion, the verification of a taximeter will not be reliable unless measurements taken on an actual taxi run are used. Global positioning system (GPS) sensors are intuitively well suited for this process, because they provide the position and the speed with independence from those car devices that are under test. Nevertheless, since GPS measurements are inherently imprecise, GPS-based sensors are difficult to homologate. In this paper we will show how these legal problems can be solved. We propose a method for computing an upper bound of the length of the trajectory, taking into account the vagueness of the GPS data. The uncertainty in the GPS data will be modelled by fuzzy techniques. The upper bound will be computed using a multiobjective evolutionary algorithm. The accuracy of the measurements will be improved further by combining it with restrictions based on the dynamic behavior of the vehicles.},
	keywords = {fuzzy fitness function, Genetic Fuzzy Systems, GPS, Metrology, vague data},
	issn = {0952-1976},
	doi = {https://doi.org/10.1016/j.engappai.2008.07.002},
	url = {http://www.sciencedirect.com/science/article/pii/S0952197608001267},
	author = {Jos{\'e} Villar and Adolfo Otero and Jos{\'e} Otero and Luciano S{\'a}nchez}
}
