Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. One way to answer these questions is route choice analysis. Route choice models in a real network deal with identifying the route a traveler would take to go from one location to another. The discrete choice framework and revealed preference GPS data is used to define a choice probability distribution over paths in the network. Using GPS-based bike trajectories, we analyze the preferences of cyclists in Eugene, Oregon, and we reveal the relative attractiveness of different types of facilities. We also show how the model can be used to predict bike traffic on the network’s links. Finally, we explain the advantages of our approach which does not require to compute choice sets of paths.
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