Leveraging Mobility Simulations with Realistic Origin-Destination Trajectory Filling

There is a shortage of mobility datasets - real or synthetic - available in the literature, limiting the development of new research. This generates demand for newer large-scale datasets, considering time, space, and population size. This work introduces a novel, two-step approach to generating large-scale mobility data considering the surrounding context, such as traffic. We validate our approach using two real mobility datasets, resulting in an enriched, large-scale dataset with more than 1 million origin-destination trips, which we share with the community to enable new research opportunities.