Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach

@article{citeulike:1796006, abstract = {This paper addresses the problem of virtual pedestrian autonomous navigation for crowd simulation. It describes a method for solving interactions between pedestrians and avoiding inter-collisions. Our approach is agent-based and predictive: each agent perceives surrounding agents and extrapolates their trajectory in order to react to potential collisions. We aim at obtaining realistic results, thus the proposed model is calibrated from experimental motion capture data. Our method is shown to be valid and solves major drawbacks compared to previous approaches such as oscillations due to a lack of anticipation. We first describe the mathematical representation used in our model, we then detail its implementation, and finally, its calibration and validation from real data.}, author = {Paris, Sebastien and Pettre, Julien and Donikian, Stephane }, citeulike-article-id = {1796006}, doi = {http://dx.doi.org/10.1111/j.1467-8659.2007.01090.x}, issn = {0167-7055}, journal = {Computer Graphics Forum}, keywords = {character\_animation, collective, cooperative, crowd, emergence, group, obstacle\_avoidance, path\_planning, steering, vehicle}, month = {September}, number = {3}, pages = {665--674}, posted-at = {2008-07-19 00:59:12}, priority = {2}, publisher = {Blackwell Publishing}, title = {Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach}, url = {http://dx.doi.org/10.1111/j.1467-8659.2007.01090.x}, volume = {26}, year = {2007} }

TY - JOUR ID - citeulike:1796006 L3 - citeulike-article-id:1796006 TI - Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach JF - Computer Graphics Forum VL - 26 IS - 3 SP - 665 EP - 674 PB - Blackwell Publishing SN - 0167-7055 N2 - This paper addresses the problem of virtual pedestrian autonomous navigation for crowd simulation. It describes a method for solving interactions between pedestrians and avoiding inter-collisions. Our approach is agent-based and predictive: each agent perceives surrounding agents and extrapolates their trajectory in order to react to potential collisions. We aim at obtaining realistic results, thus the proposed model is calibrated from experimental motion capture data. Our method is shown to be valid and solves major drawbacks compared to previous approaches such as oscillations due to a lack of anticipation. We first describe the mathematical representation used in our model, we then detail its implementation, and finally, its calibration and validation from real data. KW - character_animation KW - collective KW - cooperative KW - crowd KW - emergence KW - group KW - obstacle_avoidance KW - path_planning KW - steering KW - vehicle AU - Paris, Sebastien AU - Pettre, Julien AU - Donikian, Stephane PY - 2007/09// UR - http://dx.doi.org/10.1111/j.1467-8659.2007.01090.x ER -