This study seeks to find a strategy to capture the most observed trajectories with a minimum number of algorithms. GPS information on 4,538 real trips from 131 travelers in 2008 was collected and analyzed in Minneapolis-St. Paul (the Twin Cities) as part of the I-35W Bridge Collapse study. The high-resolution road network of the Twin Cities includes 108,561 nodes and 277,747 links. Labeling and link penalty approaches are combined to generate alternatives based on either observed or free-flow speed. Overall, with the best 10 labels, on average, 40 unique routes are generated for each origin-destination pair, and around 80% of all observed trips could be captured with an 80% overlap threshold. About 88% of all observed trips have an average deviation within 50 m compared with the best matching result when combining all labels introduced in this study. Freeway-preferred routes cover more observed trips than freeway-avoided routes, and the peak coverage occurs when freeway travel is weighted between 0.8 to 1 of travel on non-freeway links. A random effects panel model is used for predicting the overlap between alternative route and observed trajectory. Multinomial and mixed logit models with a path-size term are applied to model the route selection. These models indicate that alternative routes which are shorter in distance, have faster average free-flow speed, contain a higher freeway percentage, and incur fewer traffic lights, are more likely to have higher overlap with observed trajectories and are more likely to be selected.
Route Choice Set Generation on High-Resolution Networks
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2678 , 5 ; 112-126
2023-08-08
Article (Journal)
Electronic Resource
English
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