Experiment-based modeling, simulation and validation of interactions between virtual walkers

Abstract

International audienceAn interaction occurs between two humans when they walk with converging trajectories. They need to adapt their motion in order to avoid and cross one another at respectful distance. This paper presents a model for solving interactions between virtual humans. The proposed model is elaborated from experimental interactions data. We first focus our study on the pair-interaction case. In a second stage, we extend our approach to the multiple interactions case. Our experimental data allow us to state the conditions for interactions to occur between walkers, as well as each one's role during interaction and the strategies walkers set to adapt their motion. The low number of parameters of the proposed model enables its automatic calibration from available experimental data. We validate our approach by comparing simulated trajectories with real ones. We also provide comparison with previous solutions. We finally discuss the ability of our model to be extended to complex situations

Modeling, Evaluation, and Scale on Artificial Pedestrians

“…Vukadinovic et al [2014] combine a graph search algorithm with a local collision avoidance strategy to evaluate ad-hoc network protocols in leisure parks. In [Pettré et al 2009;Olivier et al 2012], a metric named minimal predicted distance is defined to detect a critical distance in order to avoid collisions between walkers. With few parameters, the model is able to adapt motion to manage interactions.…”

“…From the data shown in Table II we can extract two main conclusions: the prevalence of the microscopic models respect to the macroscopic ones and the concentration of works in two bibliographic areas: on the one hand research publications related [Reynolds 1987;1999;Ondrej et al 2010;Martinez-Gil et al 2014 et al 2008a;Pettré et al 2009;Karamouzas et al 2009;Guy et al 2009;van den Berg et al 2011;Olivier et al 2012;He et al 2016] Path finding and route choice Mechanics Social force [Freimuth and Lam 1992;Helbing et al 1997c;Helbing et al 1997a;Gilman et al 2005 [Chenney 2004;Treuille et al 2006;Narain et al 2009;Golas et al 2014b] and virtual Agency Agent-based [Kuffner 1999] environments Datadriven Data-driven [Lerner et al 2007;Lee et al 2007;Ju et al 2010;] CA CA [Kneidl et al 2013 Yilmaz et al 2009;Pluchino et al 2014] to Computer Graphics and, more specifically, Computer Animation (Group A); on the other hand, publications related to Transportation Research. This indicates that fundamental studies have made way to research in fields where the models are applied.…”

“…The validation with real data is the most direct way of validating models [Pettré et al 2009] and simulation systems such as NOMAD ] have used it. In [Paris et al 2007] and [ Karamouzas and Overmars 2012], calibration and validation is carried out using videos of real crowds.…”

“…They calibrated five pedestrian models [Reynolds 1987;Helbing and Molnár 1995;van den Berg et al 2011;Pettré et al 2009;Ondrej et al 2010] using three different souces of data: real data acquired in several standard pedestrian situations, fundamental diagrams and human animation sketchs. They use optimization techniques to adjust the parameters for each model and then, a benchmarking analysis is carried out.…”

Path patterns

“…To model these myriad behavioral aspects, methods such as field and flow based [Narain et al 2009;Treuille et al 2006], force-based [Helbing and Molnár 1995;Karamouzas et al 2009], velocity and geometric optimization [van den Berg et al 2008;Pettré et al 2009;Ondřej et al 2010] and data-driven [Lee et al 2007;Lerner et al 2009b] have been proposed. Our aim is to provide an evaluation framework that imposes no assumptions on the underlying simulation mechanism and can therefore work on the output data of all such methods.…”