A Self-Organizing Architecture for Traffic Management

1. A Self-Organizing Architecture for Traffic Management R. Z. Wenkstern, T. Steel, G. Leask MAVs Lab, University of Texas at Dallas

2. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

3. Introduction • Soteria: a multi-layered, integrated traffic infrastructure for safety enhancement and congestion reduction • Developed by a team of researchers at UTD • 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

4. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

5. Overview of Soteria • Premises • Traffic model consists of micro- and macro-level components • Traffic is a bottom up phenomenon • Traffic management is a top-down activity MAVs Lab, University of Texas at Dallas

6. Soteria’s Components Our goal Enforce communication, interaction and collaboration between all stakeholders both at the micro and macro levels • Micro-level components • Vehicles • Traffic lights • Relays • Data collection devices • Macro-level components • Cell controllers • Cell Controller Infrastructure • Vehicle Infrastructure • Traffic Flow Infrastructure MAVs Lab, University of Texas at Dallas

7. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

8. Micro-Level Components • Environment Monitoring System • Collects and stores information about the environment Impact Mitigation System • Takes all actions necessary to prevent major injury Context-Aware Intelligent Vehicles • Advanced Traveler Information System • Adaptive navigation system • Driver 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

9. Micro-level Components • Autonomous Adaptive System • Determine best course of action when unexpected events occur Traffic Lights • Traffic Information Collection System • Collects and manages traffic information on highways Data Collection Devices • Pass on information when physical distance is too great. Relay Units MAVs Lab, University of Texas at Dallas

10. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

11. Soterias’s Macro-level Components CA-IVS Infrastructure Traffic Flow Infrastructure Interaction/Data Exchange MAVs Lab, University of Texas at Dallas

12. MAVs Lab, University of Texas at Dallas

13. The Super-Infrastructure Cell Controller Infrastructure CAI Vehicle Infrastructure Traffic Flow Infrastructure MAVs Lab, University of Texas at Dallas

14. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

15. MATISSE • 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 MAVs Lab, University of Texas at Dallas

16. Visualization Framework Env. Data Managmt System 2D Visualization System 3D Visualization System Data Management System MATISSE Agent-Environment System Message Transport Service CAI Vehicle Platform Environment Platform Traffic Device Platform CAI Vehicle agent Management Component Environment Management Component Traffic Device agent Management Component … … … Collection Device Vehicle1 Vehicle n Controller 1 Controller n Traffic Light Vehicle–Vehicle Message Transport Service Controller –Controller Message Transport Service Device –Device Message Transport Service Controller-Vehicle Message Transport Service Controller-Traffic Device Message Transport Service Vehicle-Traffic Device Message Transport Service MAVs Lab, University of Texas at Dallas

17. Agent Architecture: Vehicles, Traffic Devices Agent Information Management Module InteractionManagement Module Environment Communication Module Agent Communication Module Self Model Cell Model Planningand Control Module Acquaintance Model TaskManagement Module Constraint Model … Task n Task 1 MAVs Lab, University of Texas at Dallas

18. Cell Controller Architecture Cell Controller Information Management InteractionManagement Agent Communication Module Environment Communication Module Agent Model Synchronizer Linked Cell Model Planningand Control Module Graph Model Self Model TaskManagement … Task n Task 1 MAVs Lab, University of Texas at Dallas

19. Outline • Introduction • Overview of Soteria • Micro Level Components • Macro-Level Components • MATISSE • MATISSE’s High Level Architecture • MATISSE’s agent architecture • MATISSE’s cell controller architecture • Conclusion MAVs Lab, University of Texas at Dallas

20. Conclusion • 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 MAVs Lab, University of Texas at Dallas

21. ? : Centralized Setting of the Self-Adapting Perspective Cell Controller 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, CAI Vehicle Infrastructure Traffic Flow Infrastructure MAVs Lab, University of Texas at Dallas

22. Thank you MAVs Lab, University of Texas at Dallas