Y.Chan A.Fowe AHTD Presentation

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  • The Incident Management project is Part of the ITS architecture are Central Arkansas
  • Y.Chan A.Fowe AHTD Presentation

    1. 1. Incident-Management In Central Arkansas – An ITS Application Federal-aid Project Number: ITSR(001) ITS meta Lab University of Arkansas at Little Rock
    2. 2. An Integrated and Shared System Operators Motorists Incident System
    3. 3. Incident Management Activities <ul><li>Motorist Assistance Patrol </li></ul><ul><ul><li>3 vehicles operating on I-30, I-40, I-630, I-430, and I-440 in the urbanized area. </li></ul></ul><ul><ul><li>Proposed to provide some coverage of both US 67/167 and I-530, from I-30 to Dixon Road </li></ul></ul><ul><li>Towing and Wrecker Service </li></ul><ul><ul><li>A rotation list of qualified towing and wrecker services. </li></ul></ul><ul><ul><li>Current procedures do not specify a minimum response time. </li></ul></ul><ul><li>Emergency Medical Services (EMS) </li></ul><ul><ul><li>911 calls </li></ul></ul><ul><ul><li>Communications upgrades are needed . </li></ul></ul><ul><li>Traffic Management at Work Zones </li></ul><ul><ul><li>Queue detectors </li></ul></ul><ul><ul><li>Variable message signs (VMS) and highway advisory radio (HAR) </li></ul></ul><ul><li>Traveler Information System </li></ul><ul><ul><li>511 calls </li></ul></ul>
    4. 4. Goals of Our Study Model the distribution of incidents Investigate advanced incident detection techniques Choose the appropriate incident-response strategies Perform Benefit/Cost (B/C) analysis
    5. 5.
    6. 6. Incident Management Model <ul><li>1. Provide a good tactic to allocate available response vehicles to serve reported incidents. </li></ul><ul><li>2. Pay attention to potential incidents in ensuring a certain level of reliability in delivering quality service. </li></ul><ul><li>3. The model helps to reduce the negative impact of incidents as much as possible. </li></ul>
    7. 7. Reported & potential Incidents Potential workload at f =40 Risk = 20% Workload = 3 ×20 min Potential workload at v=20 Delay at f = 80 min (including response time) 10 40 30 50 f (1) v (2) 2 1
    8. 8. Comparison between Current and Proposed Current Proposed Total Number of Vehicle Dispatches 66,757 66,757 Total Delay Cost (veh-min) 259,787,280 208,343,664 Mean of Work Time (min) 34.54 27.90 Standard Deviation of Work Time (min) 0.79 0.67
    9. 9. Shortest Paths, Delays, and Risks
    10. 10. LINK ESTIMATES AND FORECASTING: A Case Study
    11. 11. FIFO path Non-FIFO path
    12. 12. <ul><li>Should s/he be more interested in arriving at the destination the fastest way, his/her regular non-FIFO travel time ( 24.9 minutes) is the expected value of taking the risk, with the concomitant savings in travel time. </li></ul><ul><li>As a risk-averse person, the non-FIFO/Risk-Avoiding driver is willing to pay the difference between the certainty equivalent and this expected value to ensure safety, or ( 27.8 − 24.9) = 2.9 min. </li></ul>To Impute the Value of Safety
    13. 13. Execution time (sec.) Actual Theoretical - in 5-min increments
    14. 14. Functional ICC/TMC
    15. 15. Technical Partners (in alphabetical order) <ul><li>Gary Dalporto, Joseph Heflin, & Sandra Otto, FHWA </li></ul><ul><li>Scott Bennett, Mark Bradley, Marc Maurer & Alan Meadors, AHTD </li></ul><ul><li>Karen Bonds, AR State Police </li></ul><ul><li>David Taylor & Brian Nation, Arkansas Department of Health and Human Services </li></ul><ul><li>Casey Covington, Minh Le, Richard Magee, & Jim McKenzie, Metroplan </li></ul><ul><li>Bill Henry & Jerry Simpson, City of Little Rock </li></ul><ul><li>Doug Babb, Routh Towing Service </li></ul>
    16. 16. Key Team Members <ul><li>Gregory Browning </li></ul><ul><li>Yupo Chan </li></ul><ul><li>Isabel Farrel </li></ul><ul><li>Adeyemi Fowe </li></ul><ul><li>Jian Hu </li></ul><ul><li>Heath McKoin </li></ul><ul><li>Weihua Xiao </li></ul><ul><li>Ildeniz Yayla </li></ul>
    17. 17. Publications <ul><li>Hu, J. and Chan, Y., “A Multi-criteria Routing Model for Incident Management,” Proceedings of the IEEE International Conference on SMC, Sept. 2005, Hawaii, pp. 832-839. </li></ul><ul><li>Hu, J. and Chan, Y., “Stochastic Incident-Management of Asymmetrical Network-Workloads,” TRB Pre-print 06-1596, 85th Annual Meeting of the Transportation Research Board, Washington D.C. January 22-26, 2006. </li></ul><ul><li>Hu, J. and Chan, Y. &quot;A Dynamic Shortest-Path Algorithm for Continuous Arc Travel-Times: Implication for Traffic Incident Management.” Transportation Research Record: No. 2089, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 51–57. </li></ul><ul><li>Hu, J. and Chan, Y. &quot;Dynamic Routing To Minimize Travel Time And Incident Risks&quot;, Paper No. 485, 10th International Conference on Applications of Advanced Technologies in Transportation, Athens, Greece, 27-30, May, 2008. </li></ul>
    18. 18. Thanks. Any Question? <ul><li>http://syen.ualr.edu/metalab </li></ul>

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