Crowd Simulation in the Airline Industry

Crowd Simulationin the Airline Industry CSCI 6175 Rodger Irish Mar 4, 2014

Outline • Introduction to Crowd Simulation • Purposes of Crowd Simulation • Tools used • Airport and Airline Emergency Evacuations • The future of Crowd Simulation

Introduction to Crowd Simulation • Crowds are a group of individual parts that show characteristics of a group instead of the individual. • Reynolds’ Boids and Marvel’s Swarm are examples

Human Crowds Human crowd simulation started much like Reynolds’ flocks. Their actions were based on a small set of rules primarily composed of following a set of paths and avoiding collisions. They were adequate but did not seem very realistic and many times had problems. Several techniques have approached the problem including taking examples of actions from video of real crowds, making complex databases for different sets of rules, adding psychological and goal –oriented modules for the agents (individuals), etc, etc. The goals are to mimic a group of individuals with some shared goals but also unique attributes and actions so that the crowd acts more like real life. Simulations should use an intelligent agent that is autonomous, reactive, adaptive, cooperative, proactive, and has social and learning abilities.

Purposes of Crowd Simulation • Movies like Braveheart, Troy, Lord of the Rings involve thousands of “characters” in battle scenes. • Braveheart did the scenes with actual people. It was costly and there were some minor injuries. • LOR did the scenes with CGI for a fraction of the cost and no injuries. • Modern computer games incorporate lots of characters many of whom react to the player. • Architects, city planners, etc use crowd simulations to predict traffic flow, obstacles, and problems without the cost of trial and error. • Emergency planners use crowd simulations for evacuation scenarios to practice 1000’s of possibilities with no injuries.

Purposes of Evacuation Sims • Find most effective schemes • Help train response personnel • Find problems • Run lots of scenarios quickly • No need for special access to facilities • Low Cost • No Risk

Tools used in Simulations

Crowd behavior in evacuation is different There is one goal –exiting Emotion changes behavior Panic, fear, confusion Injury, death Training simulations often involve a user interacting as a rescuer or a guide for the crowd Things to check for: Total time for evac Speed of the danger How do the number of exits, guides affect outcome How often does crowd choose the best exit? General Evacuation Simulation

Extended BDI Perceptual Processor turns environmental observations into beliefs Deliberator filters the Desires to select Intention like finding exit or police Real-Time Planner generates different possible plans based on KOA Decision Extractor selects plan & quality depends on agent Confidence Index –if confident carry out plan otherwise return to planner Algorithm Map a human’s actions in the CAVE running scene. This data builds the State Charts. The Crowd BDI Agent Collection creates the input files for each agent The BDI input and the 1st responder and environment maps are input into AnyLogic Run the simulation and get the statistics General Evacuations (cont 1)

General Evacs (cont 2) • Most simulations have a before and after emergency event set of agent goals. • Dijkstra’s algorithm and Knowledge of Area are combined to determine the agents’ paths for evacuation • Other characteristics of the agent may include: age, sex, leadership, independence, panic scale, and injury scale.

Airport Evacuations • “Airports are the most authoritarian facilities open to public use.” • Time pressures, invasive surveillance, and high emotions make non-emergency situations tense. Imagine an emergency

Airport Evacuations (cont 1) • Problems in designing airports with evacuation in mind • Building (roof) is extremely large & holds lots of smoke. • The distances to evacuations can be long. • The population is numerous, complex, and mostly unfamiliar with the building. • Many places where bottlenecks may occur.

Airport (cont2) • Exodus simulation characteristics • Uses C++ and rule based agents. • Tracks every individual • 5 sub modules employed – Occupant, Movement, Behavior, Toxicity, and Hazard • Pathfinder Characteristics • Agent based simulator that uses steering behaviors • 3 modules – Pre-processor writes files for the Simulator, and the Post-Processor reads files from the Simulator module • Agent mode uses AI; FPE mode uses scripts from Report Engineering Guide. • FDA+EVA Characteristics • Uses and equation of motion that totals a force from the surroundings, agent properties, and escape strategy to choose where the agents go

Airplane Evacuations • Airplanes are densely populated structures with limited ability to move and evacuate. • With an emergency, quick exiting is essential to save as many lives as possible. • To help train flight personnel, Sharma has produced a game to simulate evacuations.

Why is this necessary • Though most flights are safe, there have been over 100 airline crashes since 2009. • Of those, roughly 40% have survivors, but only a few did not have fatalities. • Some famous examples • US Airways 1549 landed on the Hudson, 0 fatalities • Asiana 214 hit a sea wall in San Francisco, only 6 were killed, but 180 were injured partly due to fire.

Airplane Evacuations (cont 1) • The 3D environment is important since 2D lacks the alternate perspectives, size, height, and texture • Aircraft cabin made with 3DSMax from schematics on the Internet. This includes chair layout, textures, even simulated TV screens to make the immersion believable • AvatarSim is used to model the agents with either a Fuzzy Logic AI or control by a user in the VR gear. • Fuzzy Logic includes Psychological, Environmental, and Physical factors • Several users can run a simulation at once via the OpenSim server • The agents have a wire skeleton that controls the movements, but have a 3D mesh covering by Maya. • AI agents have 3 characteristics: goal seeking, collision avoidance, and path following behavior.

Aiplane (cont 2) • These simulations can be enacted for various hazards (fire, explosion, water) • The data is collected for analysis and debriefing. • Eventually, Sharma wants to add a point system for users who achieve (or don’t) certain sub-goals, timing, etc.

The Future • Demonstrate a simulation to show the evacuation of an airport due to a man-made emergency. • Post-911, it’s necessary to prepare these simulations. • Call of Duty Modern Warfare 2 already has an airport scene simulating an attack. • Combining the VR of the airplane simulation with the evacuation processes of an entire airport would be a 1st step in this process, but the design and programming would be daunting on such a large scale.

References • Sharma, Sharad. Otunba and Han. “Crowd Simulation in Emergency Aircraft Evacuation using Virtual Reality.” 16th International Conference on Computer Games. 2011. • Peng, Yi feng. Zha, Ziao Xiong. “Characteristics of the evacuation of the airport-type spacious constructions and the comparison of commonly used evacuation softwares.” • Zhao, Mingbi. Turner, Stephen. Cai, Wentong. “A Data-driven Crowd Simulation Model based on Clustering and Classification.” 17th IEEE Symposium on Distributed and Real Time Applications. • Shendarkar, Ameya. Vasudevan, Karthik. “Crowd Simulation for Emergency Response Using BDI Agend Based On Virtual Reality.” 2006 Winter Simulation Conference. • Szymanezyk, Oliver. Duckett and Dickinson. “Agent-Based Crowd Simulation in Airports Using Game Technology.”

Crowd Simulation in the Airline Industry