It is well known that the definition of bus schedules is critical for the service reliability of public transports. Several proposals have been suggested, using data from Automatic Vehicle Location (AVL) systems, in order to enhance the reliability of public transports. In this paper we study the optimum number of schedules and the days covered by each one of them, in order to increase reliability. We use the Dynamic Time Warping distance in order to calculate the similarities between two different dimensioned irregularly spaced data sequences before the use of data clustering techniques. The application of this methodology with the K­ Means for a specific bus route demonstrated that a new schedule for the weekends in non-scholar periods could be considered due to its distinct profile from the remaining days. For future work, we propose to apply this methodology to larger data sets in time and in number, corresponding to different bus routes, in order to find a consensual cluster between all the routes. I. I NTRODUCTION T HERE are several problems involved in public transport management. One of them, indeed a critical one, is to understand the factors that can change the transport schedule and, consequently, the transport's reliability. Unreliable schedules may reduce the number of clients and lead to a critical loss of revenue [15]. In order to increase schedules adherence and, consequently, the quality of the Dr. Roberto Frias, sin 4200-465 Porto -Portugal and with LIAAD-INESC Porto L.A. Rua de Ceuta, l1S, 6°; 4050-190 Porto -Portugal (corresponding author to provide Gama is with the Faculdade de Economia, Universidade do Porto, Rua Dr. Roberto Frias, sin 4200-465 Porto -Portugal and with LIAAD­ INESC Porto L.A. Rua de Ceuta, l1S, 6°; 4050-190 Porto -Portugal (e­ mail: jgama@fep.up.pt). J. Mendes-Moreira is with the