MAVs Lab, University of Texas at Dallas

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A Self-Organizing Architecture for Traffic Management

R. Z. Wenkstern, T. Steel, G. Leask

MAVs Lab, University of Texas at Dallas

Introduction Overview of Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High Level

Architecture MATISSE’s agent

architecture MATISSE’s cell

controller architecture Conclusion

MAVs Lab, University of Texas at Dallas

Soteria: a multi-layered, integrated traffic infrastructure for safety enhancement and congestion reduction

Developed by a team of researchers at UTD

Introduction

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Contributors• P. Boyraz• J. Hansen• A. Fumagalli• M. Tacca• O. Daescu• K. Trumper• R. Z. Wenkstern

Electrical Engineering

Telecom Engineering

Computer Science• AI• Computational Geometry• Software Engineering

MAVs Lab, University of Texas at Dallas

Introduction Overview of

Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High Level

Architecture MATISSE’s agent

architecture MATISSE’s cell

controller architecture Conclusion

MAVs Lab, University of Texas at Dallas

Premises Traffic model consists of micro- and macro-

level components Traffic is a bottom up phenomenon Traffic management is a top-down activity

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Overview of Soteria

MAVs Lab, University of Texas at Dallas

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Soteria’s Components

Micro-level components

Vehicles Traffic lights Relays Data collection devices

Macro-level components

Cell controllers Cell Controller

Infrastructure Vehicle Infrastructure Traffic Flow

InfrastructureOur goal

Enforce communication, interaction and collaboration between all stakeholders both at the micro and macro levels

MAVs Lab, University of Texas at Dallas

Introduction Overview of Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High Level

Architecture MATISSE’s agent

architecture MATISSE’s cell

controller architecture Conclusion

MAVs Lab, University of Texas at Dallas

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Micro-Level Components

Impact Mitigation System Takes all actions necessary to

prevent major injury

Context-Aware Intelligent Vehicles

Environment Monitoring System Collects and stores information

about the environment

Advanced Traveler Information System

Adaptive navigation systemDriver Monitoring System Collects information about driver’s

condition

Temporary Collision Avoidance System

Assists the driver into directing the car to the closest safe area

MAVs Lab, University of Texas at Dallas

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Micro-level Components

Traffic Lights

Data Collection Devices

Relay Units

Autonomous Adaptive System Determine best course of action

when unexpected events occur

Traffic Information Collection System Collects and manages traffic

information on highways

Pass on information when physical distance is too great.

MAVs Lab, University of Texas at Dallas

Introduction Overview of Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High Level

Architecture MATISSE’s agent

architecture MATISSE’s cell

controller architecture Conclusion

MAVs Lab, University of Texas at Dallas

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Soterias’s Macro-level Components

CA-IVS Infrastruct

ure

Traffic Flow

Infrastructure

Interaction/Data Exchange

MAVs Lab, University of Texas at Dallas

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MAVs Lab, University of Texas at Dallas

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The Super-Infrastructure

CAI Vehicle Infrastruct

ure

Cell Controller

Infrastructure

Traffic Flow

Infrastructure

MAVs Lab, University of Texas at Dallas

Introduction Overview of Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High

Level Architecture

MATISSE’s agent architecture

MATISSE’s cell controller architecture

Conclusion

MAVs Lab, University of Texas at Dallas

Multi-Agent based TraffIc Safety Simulation systEm

Simulation framework designed to specify and execute scenarios for Soteria

Vehicles, traffic lights, relays, data collection devices, and cell controllers are modeled as agents

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MATISSE

MAVs Lab, University of Texas at Dallas

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CAI Vehicle agentManagementComponent

Vehicle1 Vehicle n

Vehicle–Vehicle Message Transport Service

…

CAI Vehicle Platform

Traffic Device agent

ManagementComponent

Traffic Light

Collection Device

Device –Device Message Transport Service

…

Traffic Device Platform

Controller-Traffic Device Message Transport Service

Controller-VehicleMessage Transport Service

Vehicle-Traffic Device Message Transport Service

MATISSE Agent-Environment System

Message Transport Service

Data Management System

Visualization Framework 2D

VisualizationSystem

3D VisualizationSystem

Environment Platform

…

Environment ManagementComponent

Controller 1

Controller n

Controller –Controller Message Transport Service

Env. Data

Managmt System

MAVs Lab, University of Texas at Dallas

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Agent Architecture: Vehicles, Traffic Devices

Planning and Control Module

EnvironmentCommunication

Module

Task 1 Task n

Agent

Interaction Management Module

Task Management Module

Agent Communication

Module

…

Information ManagementModule

Self Model

Cell Model

Acquaintance Model

Constraint Model

MAVs Lab, University of Texas at Dallas

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Cell Controller Architecture

Planning and Control Module

EnvironmentCommunication

Module

Task 1 Task n

Cell Controller

Interaction Management

Task Management

Agent Communication

Module

…

Information Management

Synchronizer

Agent Model

Linked Cell Model

Graph Model

Self Model

MAVs Lab, University of Texas at Dallas

Introduction Overview of Soteria Micro Level

Components Macro-Level

Components

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Outline

MATISSE MATISSE’s High

Level Architecture MATISSE’s agent

architecture MATISSE’s cell

controller architecture

Conclusion

MAVs Lab, University of Texas at Dallas

Soteria: novel traffic organizational structure

MATISSE: simulation system tailor-made for Soteria

Hybrid Systems

Implement both macroscopic and microscopic models

Use a top-down/bottom-up strategy

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Conclusion

MAVs Lab, University of Texas at Dallas

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? : Centralized Setting of the Self-Adapting Perspective

CAI Vehicle Infrastruct

ure

Cell Controller

Infrastructure

Traffic Flow

Infrastructure

Micro-level: each autonomous agent influences and adapts to changes while interacting, cooperating and coordinating actions with other agents

Macro-level: cell controllers monitor and guide the global system behavior in a decentralized fashion,

MAVs Lab, University of Texas at Dallas

Thank you

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