University of California Transportation Center

Despite its application in many fields, map matching in studies of travel/transport geography is unique in two aspects: 1) The correct road links traversed by the traveler need to be unambiguously identified; 2) All the identified links should form a meaningful travel route. This paper discusses the application of map matching methodologies in the context of deriving people’s travel behavior from GPS-traced multi-modal trip data. In recognition of the disadvantages associated with the existing algorithms, this research proposed and implemented a heterogeneous map matching approach suitable for travel/activity research needs which is uniquely characterized by: 1) data preprocessing with point cluster reduction and density leverage; 2) offering the candidate solution within a pool of “the best”; 3) the balancing of matching results from multiple matching factors with rank aggregation; 4) Utilizing the network constraint attributes to increase the matching accuracy; and 5) Use of the Dempster belief test to discern the noise and off-road travel.