Pedestrian mobility models are used to quantitatively represent the stochastic nature of pedestrian movement. Research in such movement models has mainly been applied to planning tasks, such as estimating pedestrian flows when planning a train station or airport, or optimization of evacuation procedures and evacuation paths for a large shopping mall or theater. Another application area which is becoming increasingly important is that of dynamic indoor positioning and navigation. The reason that a movement model is needed in these cases lies in the dynamic nature of most pedestrian indoor navigation applications: The user’s position will be estimated continuously so as to allow services such as personalized travel assistance or indoor navigation directions. In addition, it can be shown that a dynamic positioning system is more accurate than a “single-shot” static estimator which essentially provides a position estimate based on positioning measurements of a single time instance. To implement mathematically sound dynamic estimators one needs an accurate and realistic movement model (also known as the a-priori state transition model) of the dynamic system: Here the user’s stochastic movement (position, velocity, attitude, etc). Additionally, a goal oriented movement model based on the diffusion algorithm is combined with the stochastic movement model to take goal oriented movement into account. All models are extended to handle the 3D environment.
In order to handle critical scenarios like large rooms new angular PDFs based on maps are applied in our cascaded Bayesian estimation architecture. The location dependent angular PDFs can serve also for predicting the heading within an motion model. More can be found here ...
Angular PDFs can also be used as a prior map for FootSLAM. More can be found here ...
Layout Matrix for areas with different accessibility levels. The walls are given in black, not easy reachable forest area is marked with dark gray, and flowerbed area is given in light gray. The area where people may walk is given in white.
Diffusion results after reaching steady state, where the gas concentration is high in the dark red area and low in the blue area.
More Information on Mobility Models:
Publications Slides Video Diffusion Demo