a traffic simulation model allowing for wide-ranged vehicle communication (being altered/worked on)...
TRANSCRIPT
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A Traffic Simulation Model Allowing For Wide-ranged Vehicle
Communication (being altered/worked on)
Timmy Galvin(Third Quarter)
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Abstract
Traffic Simulation Moving past optimal Model Types:
Fluid Flow Agent Based Modeling
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Introduction
Communication Calculation- information flow Human behavior Reaction and Response
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Background
Traffic Jams
– What causes a jam? Optimization of Models Variable speed limits
– Inferred effects Kai Nagel Steen Rasmussen
Micro models
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Fluid Flow Model
Opposing theory Terrible at small perturbations
Butterfly effect Mostly kept in the United States
Slow to change to agent based
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Development
World and environment Vehicles- all private information Reaction Algorithm
– Function of individuality User-definition Density versus Flow
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Reaction Algorithm
Delta X Smallest distance on same line of travel Function of two velocities Previously linear
– Not true human behavior, more development
Looking forward through intersections
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Intersections
• Defined by user
• N number of intersections
• Stoplights created with preset timing
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Results
Traffic jam moving backwards- speed trap Graphical analysis of density versus flow Traffic congestion and travel time How do different variables affect traffic patterns Altering timing on a system-wide scale
– Networking traffic lights
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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