For applications in animal movement, we propose a random trajectory generator (RTG) algorithm that combines the concepts of random walks, space-time prisms, and the Brownian bridge movement model and is capable of efficiently generating random trajectories between a given origin and a destination point, with the least directional bias possible. Since we provide both a planar and a spherical version of the algorithm, it is suitable for simulating trajectories ranging from the local scale up to the (inter-) continental scale, as exemplified by the movement of migrating birds. The algorithm accounts for physical limitations, including maximum speed and maximum movement time, and provides the user with either single or multiple trajectories as a result. Single trajectories generated by the RTG algorithm can be used as a null model to test hypotheses about movement stimuli, while the multiple trajectories can be used to create a probability density surface akin to Brownian bridges.
In application domains other than humans' movement, there do exist interesting proposals; for instance, in the domain of animal ecology, REF recently proposed the random trajectory generator (RTG), an algorithm that combines the concepts of random walks, space-time prisms, and the Brownian bridge movement model.
From A to B, randomly: a point-to-point random trajectory generator for animal movement
International Journal of Geographical Information Science
Computer Science