A method is proposed to probabilistically map location observations to the underlying network. Instead of generating a single path as the map matching algorithms do, this method aims at calculating a likelihood for each potentially true path to have been the actual path. The result can be used in route choice modeling to avoid biases introduced by a deterministic map matching algorithm. Both spatial and temporal relationships existing in the location data trace and network are taken into account in the method. An algorithm is designed to calculate path probability, starting by defining the measurement for the topological relationship between location observation and network data. Results from the algorithm for a simulated trip are presented to demonstrate the viability of the algorithm.