Bongiorno and colleagues set out to learn more about how people find their way through cities. The group reports that they “analyze salient features of human path planning through a statistical analysis of a massive dataset of GPS traces, which reveals that (1) people increasingly deviate from the shortest path when the distance between origin and destination increases and (2) chosen paths are statistically different when origin and destination are swapped. We posit that direction to goal is a main driver of path planning and develop a vector-based navigation model; the resulting trajectories, which we have termed pointiest paths, are a statistically better predictor of human paths than a model based on minimizing distance with stochastic effects. Our findings generalize across two major US cities with different street networks, hinting to the fact that vector-based navigation might be a universal property of human path planning.” So, we’ll choose the route that seems to point most directly toward our destination, even if traveling this route actually requires us to walk a longer distance; we choose the path that allows us to most directly face our goal as we begin to walk. Also, we tend to choose different routes for each direction of a round trip journey.
Christian Bongiorno, Yulun Zhou, Marta Kryven, David Theurel, Alessandro Rizzo, Paolo Santi, Joshua Tenenbaum, and Carlo Ratti. 2021. “Vector-Based Pedestrian Navigation in Cities.” Nature Computational Science, vol. 1, pp. 678-685, https://doi.org/10.1038/s43588-021-00130-y