Pedestrian velocity obstacles: pedestrian simulation through reasoning in velocity space ...

• Main Author: Curtis, Sean
• Format: Thesis
• Language: English
• Published: University of North Carolina at Chapel Hill 2014
• Subjects: Orca
• Online Access: https://dx.doi.org/10.17615/zbcj-xa48; https://cdr.lib.unc.edu/concern/dissertations/sn009z16b?locale=en

We live in a populous world. Furthermore, as social animals, we participate in activities which draw us together into shared spaces -- office buildings, city sidewalks, parks, events (e.g., religious, sporting, or political), etc. Models that can predict how crowds of humans behave in such settings would be valuable in allowing us to analyze the designs for novel environments and anticipate issues with space utility and safety. They would also better enable robots to safely work in a common environment with humans. Furthermore, credible simulation of crowds of humans would allow us to populate virtual worlds, helping to increase the immersive properties of virtual reality or entertainment applications. We propose a new model for pedestrian crowd simulation: Pedestrian Velocity Obstacles (PedVO). PedVO is based on Optimal Reciprocal Collision Avoidance (ORCA), a local navigation algorithm for computing optimal feasible velocities which simultaneously avoid collisions while still allowing the agents to ...