Experiments on route choice set generation using a large GPS trajectory set
This addresses route modeling for transportation planning by providing improved coverage with large GPS data, though it is incremental as it builds on existing algorithms.
The paper tackled route choice set generation by evaluating different path generation algorithms using a large GPS dataset of 6,000 observations from Tel-Aviv, finding that a single shortest path covered 60% of observations and a modified link penalty method achieved 97% coverage.
Several route choice models developed in the literature were based on a relatively small number of observations. With the extensive use of tracking devices in recent surveys, there is a possibility to obtain insights with respect to the traveler's choice behavior. In this paper, different path generation algorithms are evaluated using a large GPS trajectory dataset. The dataset contains 6,000 observations from Tel-Aviv metropolitan area. An initial analysis is performed by generating a single route based on the shortest path. Almost 60% percent of the 6,000 observations can be covered (assuming a threshold of 80% overlap) using a single path. This result significantly contrasts previous literature findings. Link penalty, link elimination, simulation and via-node methods are applied to generate route sets, and the consistency of the algorithms are compared. A modified link penalty method, which accounts for preference of using higher hierarchical roads, provides a route set with 97% coverage (80% overlap threshold). The via-node method produces route set with satisfying coverage, and generates routes that are more heterogeneous (in terms number of links and routes ratio).