Y.Chan A.Fowe AHTD Presentation
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
541
On Slideshare
541
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
3
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Incident-Management In Central Arkansas Federal-aid Project Number: ITSR(001) ITS meta Lab University of Arkansas at Little Rock
  • 2. An Integrated and Shared System Operators Motorists Incident System
  • 3. Incident Management Activities
    • Motorist Assistance Patrol
      • 3 vehicles operating on I-30, I-40, I-630, I-430, and I-440 in the urbanized area.
      • Proposed to provide some coverage of both US 67/167 and I-530, from I-30 to Dixon Road
    • Towing and Wrecker Service
      • A rotation list of qualified towing and wrecker services.
      • Current procedures do not specify a minimum response time.
    • Emergency Medical Services (EMS)
      • 911 calls
      • Communications upgrades are needed .
    • Traffic Management at Work Zones
      • Queue detectors
      • Variable message signs (VMS) and highway advisory radio (HAR)
    • Traveler Information System
      • 511 calls
  • 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.  
  • 6. Incident Data of Arkansas Arkansas State Police Report (2000 ~ 2003) larger municipalities Frequency counties road system crash severity alcohol involvement weather roadway profile roadway alignment light conditions weekdays type of collisions rural or urban
  • 7. Architecture of Software System Assistant Parts Incidents Others GPS/GIS VC# Programming Internal Information System TransCAD Server GISDK Script Programming Update Map SQL Database
      • Output Platforms
    Web Application ASP .NET programming Core: 1. Planning Model 2. Operating Model
  • 8. SIMAN Dynamic shortest path EMS fleet assignment & demand coverage MRM (Multicriteria Routing Module ) DRA (Dynamic Routing Algorithm) SIMANI (Stochastic Incident-Management of Asymmetric Network-Workload – Integrated )
  • 9. Incident Management Model
    • Functions
    • 1. Provide a good tactic to allocate available response vehicles to serve reported incidents.
    • 2. Pay attention to potential incidents in ensuring a certain level of reliability in delivering quality service.
    • 3. The model helps to reduce the negative impact of incidents as much as possible.
    • Algorithm
    • SIMAN
  • 10. Reported & potential Incidents Potential workload at f =40 Risk = 20% Workload = 3 ×20 min Potential workload at v=20 Delay at f = 80 min 10 40 30 50 f (1) v (2) 2 1
  • 11. Comparison between Rotation and SIMAN 9.51 11.18 Standard Deviation of Work Time (min) 27.90 34.54 Mean of Work Time (min) 208,343,664.00 259,787,280.00 Total Delay Cost (veh-min) 66,757 66,757 Total Number of Vehicle Dispatches SIMAN Rotation
  • 12. Multicriteria Routing Module
  • 13. Operational Model – Dynamic Routing 15 10 10 15 C B A 0 5 10 15 35 25 25 Intermediat e Starting Arrival 20 35
  • 14. Arkansas Crash Data for 2003 52,474 641 42,222 28,125 557 Injuries Fatalities PDO Injury Fatal
  • 15. Functional Structure of the Prototype Incident Command Center Users Motorists Operators Managerscxv Environment Travel Time Incidents System Data Input & Analysis Core Algorithms Output Platforms
  • 16. Technical Partners (in alphabetical order)
    • Gary Dalporto, Joseph Heflin, & Sandra Otto, FHWA
    • Scott Bennett, Mark Bradley, Marc Maurer & Alan Meadors, AHTD
    • Karen Bonds, AR State Police
    • David Taylor & Brian Nation, Arkansas Department of Health and Human Services
    • Casey Covington, Minh Le, Richard Magee, & Jim McKenzie, Metroplan
    • Bill Henry & Jerry Simpson, City of Little Rock
    • Doug Babb, Routh Towing Service
  • 17. Key Team Members
    • Gregory Browning
    • Yupo Chan
    • Isabel Farrel
    • Adeyemi Fowe
    • Jian Hu
    • Heath McKoin
    • Weihua Xiao
    • Ildeniz Yayla
  • 18. Publications
    • 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.
    • 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.
    • Hu, J. and Chan, Y. "A Dynamic Shortest-Path Algorithm for Continuous Arc Travel-Times: Implication for Traffic Incident Management.” Pre-print 08-0756, 87th Annual Meeting of the Transportation Research Board, Washington D.C. January 13-17, 2008.
    • Hu, J. and Chan, Y. "Dynamic Routing To Minimize Travel Time And Incident Risks", Paper No. 485, 10th International Conference on Applications of Advanced Technologies in Transportation, Athens, Greece, 27-30, May, 2008.
  • 19. Thanks. Any Question?
    • http://syen.ualr.edu/metalab
  • 20. Planning & Operational Models
    • Functions
    • 1. Provide incident managers with best strategies to respond to an incident
    • 2. Assist motorists on re-routing around incidents, and incident response operators on dispatching response vehicles.
    • Two Algorithms
    • 1. Multi-Criteria Optimization (as a planning tool):
    • Paper: Hu, J. and Chan, Y. (2005), “A Multi-criteria Routing Model for Incident Management,” Proceedings of the IEEE International Conference on SMC , Sept., Hawaii, pp. 832-839.
    • 2. Dynamic Routing (as an operational tool):
    • Paper: Hu, J. and Chan, Y. (2006), “Dynamic Routing to Minimize Travel Times and Incident Risks,” Accepted for presentation and Proceedings of the 9th International Conference on the Application of Advanced Technologies in Transportation, ASCE, Chicago, IL, August, 2006.
  • 21. Schedule of Incident Service Dispatch time Incident Occurrence Incident Notified Response Unit Assignment Response Unit Arrives at Scene Detection time Response vehicle travel time Incident clear time Work time Response time Incident Restoration
  • 22. Planning Model – Multicriteria Optimization
    • Four Criteria
    • 1) Distance It has implications on operating cost, including oil price.
    • 2) Travel Time: It is tied to operating cost and response time.
    • 3) Variance in Travel Time: It measures the travel time reliability .
    • 4) Risk Index: Risk exposure is an indicator of highway safety .
    • Objective Function
    • Minimize
    • Wt 1 × Tour Dist + Wt 2 × Travel Time + Wt 3 × Var + Wt 4 × Risk Indx
    • NOTE:
    • 1) Weight 1 + Weight 2 + Weight 3 + Weight 4 = 1
    • 2) The model yields all viable (dominant) routings for all weights.
  • 23. Dominant Tours 0.563 6.57 44.74 42.83 0-12-14-10-9-8-11-13-7-15-0 0-10-11-15-0 4 0.568 5.74 44.10 43.56 0-12-14-10-14-12-11-12-0-15-0 0-10-11-15-0 3 0.564 6.02 41.25 39.72 0-12-11-8-9-10-14-12-0-15-0 0-10-11-15-0 2 0.681 6.92 41.76 39.02 0-12-11-8-9-10-9-8-11-12-0-15-0 0-11-10-15-0 1 Risk Index Time Variance Expected Time Dist. Original Tour Tour Wt. Set
  • 24. Path Dist, Time, Var & Risk on Network ---- 0.5245 0.5388 0.4480 0.5058 1.0000 0.9756 0.7399 0.6579 0.2405 0.2500 0.2168 0.1608 15 0.5245 0.5388 0.4480 0.5058 ---- 0.4409 0.4612 0.5520 0.4942 0.2840 0.2888 0.2312 0.3450 11 1.0000 0.9756 0.7399 0.6579 0.4409 0.4612 0.5520 0.4942 ---- 0.7595 0.7256 0.5231 0.4971 10 0.2405 0.2500 0.2168 0.1608 0.2840 0.2888 0.2312 0.3450 0.7595 0.7256 0.5231 0.4971 ---- 0 15 11 10 0 NODES
  • 25. An Example
  • 26. Objective function Delay Cost For each incident in the network Delay Cost = Cost × Delay Cost = Traffic Volume (Vehicle) Delay = Work Time (Minute) fixed costs for dispatching response vehicles = Number of response vehicles × Unit cost to dispatch a vehicle
  • 27. Incident parameters W f =3 ×20 C f =80 C v =100 J f =70 J v =40 H=20 K=5 10 40 30 50 f (1) v (2) 2 1 5×20 4×20 3×20 2×20 1×20 --------- D f D v 0.004 0.055 0.101 0.246 0.594 0.0046 v (2) 0.000 0.019 0.070 0.192 0.718 0.0142 f (1) Z 5 Z 4 Z 3 Z 2 Z 1 λ
  • 28. Incident workload Node v (2) Node f (1) W f =3 ×20 C f =80 C v =100 J f =70 J v =40 H=20 K=5 10 40 30 50 f (1) v (2) 2 1 ∞ ∞ ∞ 86.81 15.69 0.2 t 4 t 3 t 2 t 1 t 0 R ∞ ∞ ∞ 146.4 48.22 0.2 t 4 t 3 t 2 t 1 t 0 R
  • 29. Operational Model – Dynamic Routing
    • Improved Feature:
    • 1) Time-dependent travel time
    • 2) Measuring of Incident Risk using Poisson Processes and Queuing Theory
    • 3) Allowing waiting at nodes along the path
    • 4) Incident risks are combined into the shortest path algorithm as paroxysmal delays, which are incorporated as part of the travel time.
  • 30. ATIS Architecture
  • 31. Work in Progress: Incident Detection
  • 32. Functional ICC/TMC
  • 33. Administrative Remarks
    • UALR is upgrading equipment (as additional matching)
    • Your guidance is necessary in designing the Software architecture
    • Need More Information:
    • 1) Time-dependent Travel Time for each Highways
    • 2) Details on the current practice in servicing an incident
    • 3) Information on the available Towing Truck Companies