The use of GPS observations for investigating routing behaviors can be a good alternative to using more traditional traffic simulation models. In this paper, a method for inferring paths from GPS observations is proposed. Further, a route set generation algorithm is implemented. The inferred trips are used for the calibration of the parameters in the route set generation algorithm. The investigated network is part of the Interstate 210 freeway east of Los Angeles, USA. The results shows significant differences in number of eastbound travelers choosing to travel north of, south of, and on the freeway during regular days compared with the incident day. The travel times are also higher during the incident day. Different travel times as costs on the links have a large impact on the results from the route set generation algorithm. The conclusion is that the implemented methods can be used to gain a better understanding about routing behavior. However, to use the results for decision making, more input data with better precision should be used.