In this project, a method for systematical analysis of GPS-data is presented, in order to get timetables in public bus service that is closer to reality. Besides this, it also assess the potential of adjusting travel times after the variation of days, considering the variation of the travel time and dispersion between the data, within Monday to Friday and also in the concerned weekdays. To inform about how public transport and particularly the bus system are composed, the public transport system in the metropolitan area is described, focusing on Copenhagen and the central municipalities. Subsequently, the evaluation in public transport shows that the system overall, in spite of major investments, has had difficulties in retaining passengers for a number of years. This has even happened during a period where traffic has increased significantly. The study suggests that several factors that affect use of public transport are external, and thus parameters that traffic operators in the metropolitan area can not directly change. Nevertheless, a number of internal factors, especially inferior reliability and longer travel times have contributed to the negative tendency in the passenger number. The study also shows that the negative trend in the overall public transport is attributable to the bus service, reflecting that the trends are worst in this area and affect the entire system as busses carry many more passengers than other public transport together. To improve the overall system, focus on the bus service and the internal factors, reliability and travel time, is therefore considered necessary. One way of improving reliability and travel time is achieved by analyzing the timetables that busses operate within. This is due to the transport authority Movia’s lack of a systematic tool to determine the optimal travel time based on a larger amount of data. To document and identify where the timetables usefully could be optimized based on its position by GPS, data from the bus line 5A from Sundbyvester Plads to Husum Torv is collected over a period of one month. In addition to optimize the travel times of the timetables, the variation of average travel time Monday to Friday and during a single day will first be analyzed. This analysis of travel time between traveling and dispersion measurements provides a general insight into travel time and indicates the need for different timetables Monday to Friday. Today Movia operates with different timetables weekdays, Saturdays, Sundays and Holidays. Analysis of the variation of day shows no clear trend, but there should, however, be different travel times on Fridays in a northwesterly direction towards Husum Torv. The analysis of travel time variation over the weekdays is interesting but does not meet the projects purpose, with intention to analyze the travel times in the timetables. For this a method, to statistically assemble the actual travel time with those who are scheduled into the timetables, is developed. This calculates differences between planned and actual travel times, and the statistical test for the means assess to what extent there is a difference between these. Since the project’s main objective is a Method development, only sections from Nørrebro Station to Husum Torv in line 5A has been chosen. This is due to the project only making a screening of line 5A, and thus the results are not ends in themselves. The screening of sections in line 5A shows that travel times in timetables can be optimized with benefit. The timetables can and should be strengthened, especially in northwesterly direction from Nørrebro Station towards Husum Torv. In the opposite direction towards Nørrebro Station is the potential smaller, and at some points should the travel time in the timetables even be extended. With the method, the transport authority Movia get a tool they can systematically apply, when new timetables should be amended or created. The developed method for analysis of GPS data is simple, understandable and easy for planners to use. It is however recommended to select a larger temporal boundary than the project has used, thus resulting in greater reliability to the results of the investigated lines. It can advantageously be chosen to consider the four months in October to November and January to February. The goal is 100 travel time measurements in each period in the concerned data extraction.