| The advent of GPS-based travel surveys offers an opportunity to develop empirically-rich route-choice models. However, the GPS traces must first be mapped to the roadway network, map-matching, to identify the network-links actually traversed. In the study, two enhanced map-matching algorithms are implemented and compared for their operational performance using data from a large-scale GPS survey. Once the traversed path is determined, the next step is to determine the other options (routes), choice set generation, that were available to the traveler for making the trip. For this, the enhanced version of the Breath First Search Link Elimination (BFS-LE) algorithm is implemented. The data assembled from the two steps, map matching and choice set generation, are then used for developing route choice.;The original Path Size Logit (PSL) model is used for developing models for route choice. The PSL models are developed for three different choice set sizes (15 alternatives, 10 alternatives, and 5 alternatives). The utility functions are expressed in terms of route attributes, trip characteristics and traveler characteristics. The estimation results indicate intuitive effects. Specifically, free-flow travel time, left turns, right turns, intersections, and circuity were found negatively associated with the attractiveness of a route. A positive sign on the path size attribute indicates that the route with less similarity with the alternatives is more likely to be chosen. Trips going to home are the least sensitive to the travel time and right turns than the other trips. Compared to home-based trips, non-home-based trips are less sensitive to intersections and time on local roads.;On average, the expected overlaps (probabilistic routes) with the chosen route are similar to the deterministic overlaps (shortest time path). Also, there is a probability of about 50% that the predicted route will outperform the shortest time path.;We envision this study as an important contribution towards the development of empirically rich route choice models. With increasing numbers of GPS surveys and benefits of using high-resolution roadway network, the availability of computationally efficient automatic procedures to generate the chosen routes and alternatives is critical. Further, the examination of route choice behavior in terms of travelers' demographics provides more insight into the route choice decisions. |
