A Traffic Simulation Model Allowing For Wide-ranged Vehicle Communication Timmy Galvin

Abstract Traffic Simulation Moving past optimal Model Types: Fluid Flow Agent Based Modeling

Introduction Communication Calculation- information flow Human behavior Reaction and Response

Background Traffic Jams Optimization of Models Variable speed limits Kai Nagel Steen Rasmussen Micro models

Development World and environment Vehicles- all private information Reaction Algorithm Turning Algorithm Density versus Flow

Fluid Flow Model Opposing theory Terrible at small perturbations Butterfly effect Mostly kept in the United States Slow to change to agent based

Reaction Algorithm Delta X Smallest distance on same line of travel Function of two velocities Previously linear Not true human behavior, more development

Turning Algorithm All angle-based Trigonometric Functions Leads to issues in detection algorithm for a 2d system

Results Traffic jam moving backwards- speed trap Graphical analysis of density versus flow Information sharing to alleviate traffic Adjustable speed limits Removing traffic impediments- stop signs

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