Timmy Galvin Computer Systems Lab

Traffic simulation Communication Traffic Jams What causes a jam?

Kai Nagel Steen Rasmussen Micro models Reaching optimization Model Types: Fluid flow Agent-based modeling

Opposing theory to agent-based Small perturbations Butterfly effect Mostly kept in the United States Slow to change Larger systems

User-defined environment Random vehicles agents Reaction Algorithm Function of individuality Density versus Flow

Shortest linear distance on line of travel Power function of two velocities Previously linear Not true human behavior, more development Looking forward through intersections

Defined by user N number of intersections Stoplights created with preset timing

Traffic jam moving backwards Reaction speed Human variations and compounding Traffic congestion and travel time Altering timing on a system-wide scale Networking traffic lights

Traffic is dependent on human specific behavior More factors need to be taken into account Further research Micro model → macro model Compilation of parts