Adapting Risk Management and Computational Intelligence Network Optimization Techniques to Improve Traffic Throughput and Tail Risk Analysis

Risk management techniques are used to analyze fluctuations in uncontrollable variables and keep those fluctuations from impeding the core function of a system or business. Examples of this are making sure that volatility in copper and aluminum prices do not force an aircraft manufacturer to abruptly shut down manufacturing and making sure a failed bank or state does not cause an entire financial system to fail. Computer network optimization techniques involve many nodes and routes communicating to maximize throughput of data while making sure not to deadlock high priority or time sensitive data. This project will involve exploring possible remappings of these application spaces from risk and computer networks to traffic. Some of these possible mappings include mapping flash crashes and black swans to traffic jams, bank failure to construction or traffic accidents, data packets to vehicles, network routers to traffic lights and other intersection policies. Due to the large data and large solution/ state/ policy spaces computational intelligence techniques are a natural fit for traffic as they are for risk management and computer network optimization.

• Record URL:
  http://transportation.mst.edu/research/r348/

Language

• English

Project

• Status: Completed
• Funding: $11099.00
• Contract Numbers:

  DTRT06-G-0014

  00042533

• Sponsor Organizations:

  Research and Innovative Technology Administration

  University Transportation Centers Program
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590

  Missouri University of Science and Technology, Rolla

  328 Butler-Carlton Hall
  1401 N. Pine Street
  Rolla, MO  United States  65401
• Principal Investigators:

  Wunsch, Donald

• Start Date: 20130501
• Expected Completion Date: 0
• Actual Completion Date: 20131231
• Source Data: RiP Project 34934

Subject/Index Terms

• TRT Terms: Control systems; Data quality; Financial analysis; Optimization; Risk analysis; Risk management; Traffic flow
• Uncontrolled Terms: Network optimization; Throughput (Traffic); Time sensitive industries
• Subject Areas: Data and Information Technology; Finance; Highways; Operations and Traffic Management; Security and Emergencies;

Filing Info

• Accession Number: 01530033
• Record Type: Research project
• Source Agency: Center for Infrastructure Engineering Studies
• Contract Numbers: DTRT06-G-0014, 00042533
• Files: UTC, RiP
• Created Date: Jul 3 2014 1:01AM