Incident-Management Incident-Management In Central ArkansasIn Central Arkansas

Federal-aid Project Number: ITSR(001)Federal-aid Project Number: ITSR(001)

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Motorists

An Integrated and Shared System

IncidentS

ystem

Operator

s

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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

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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

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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

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Assistant Parts

Incidents

Others

GPS/GIS

VC# Programming

Internal Inform

ation S

ystem

TransCAD Server

GISDK Script Programming

Up

date M

apSQL Database

Output PlatformsWeb ApplicationASP.NET programming

Core:1. Planning Model2. Operating Model

Architecture of Software System

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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)

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Incident Management Model

• Functions1. 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

10Potential workload at f =40

10

4030

50f(1)

v(2)

2

1

Reported & potential Incidents

Risk = 20%

Workload = 3×20 min

Potential workload at v=20

Delay at f = 80 min

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Comparison between Rotation and SIMAN

9.5111.18Standard Deviation of Work

Time (min)

27.9034.54Mean of Work Time (min)

208,343,664.00259,787,280.00Total Delay Cost (veh-min)

66,75766,757Total Number of Vehicle

Dispatches

SIMANRotation

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Multicriteria Routing Module

1

6

2

4

3

5

7

8

0

1215

13

11

9

10

14

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Operational Model – Dynamic Routing

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10

10

15

CBA

0

5

10

15 35

2525

IntermediateStarting Arrival

20 35

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Arkansas Crash Data for 2003

52,47464142,22228,125557

InjuriesFatalitiesPDOInjuryFatal

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Users

Motorists

Operators Managerscxv

Environment

Travel Time

Incidents

System

Data Input & Analysis

Core Algorithms

Output Platforms

Functional Structure of the Prototype Incident Command Center

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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

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Key Team Members

• Gregory Browning • Yupo Chan • Isabel Farrel • Adeyemi Fowe • Jian Hu • Heath McKoin • Weihua Xiao • Ildeniz Yayla

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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.

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Thanks. Any Question?

http://syen.ualr.edu/metalab

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Planning & Operational Models

• Functions1. Provide incident managers with best strategies to respond to an incident2. Assist motorists on re-routing around incidents, and incident response operators on dispatching response vehicles.

• Two Algorithms1. 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.

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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

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Planning Model – Multicriteria Optimization

• Four Criteria1) Distance Distance It has implications on operating cost, including oil price. 2) Travel Time:Travel Time: It is tied to operating cost and response time.3) Variance in Travel Time: Variance in Travel Time: It measures the travel time reliability..4) Risk Index: Risk Index: Risk exposure is an indicator of highway safety..

• Objective FunctionMinimize 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 = 12) The model yields all viable (dominant) routings for all weights.

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Dominant Tours

0.5636.5744.7442.830-12-14-10-9-8-1

1-13-7-15-00-10-11

-15-04

0.5685.7444.1043.560-12-14-10-14-12-11-12-0-15-0

0-10-11-15-0

3

0.5646.0241.2539.720-12-11-8-9-10-1

4-12-0-15-00-10-11

-15-02

0.6816.9241.7639.020-12-11-8-9-10-9-8-11-12-0-15-0

0-11-10-15-0

1

Risk IndexTime VarianceExpected

TimeDist.Original TourTour

Wt.Set

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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

1511100NODES

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An Example

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Objective function

∑∑∑∑∈ ∈ =∈

+Fi Lj

N

kijk

Fiii

j

xHTCMIN1

Delay CostDelay CostFor each incident in the networkDelay Cost = Cost × Delay

Cost = Traffic Volume (Vehicle)Delay = Work Time (Minute)

fixed costs for fixed costs for dispatching response dispatching response

vehiclesvehicles

= Number of response vehicles × Unit cost to dispatch a vehicle

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10

4030

50f(1)

v(2)

2

1

Incident parameters

5×204×203×202×201×20---------Df Dv

0.0040.0550.1010.2460.5940.0046v(2)

0.0000.0190.0700.1920.7180.0142f(1)

Z5Z4Z3Z2Z1λ

Wf=3×20

Cf=80 Cv=100 Jf=70 Jv=40 H=20 K=5

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Node v(2)

Node f(1)

10

4030

50f(1)

v(2)

2

1

Incident workload

∞∞∞86.8115.690.2

t4t3t2t1t0R

∞∞∞146.448.220.2

t4t3t2t1t0R

Wf=3×20 Cf=80 Cv=100 Jf=70 Jv=40 H=20 K=5

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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.

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ATIS Architecture

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Work in Progress: Incident Detection

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Functional ICC/TMC

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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 Highways2) Details on the current practice in servicing an incident3) Information on the available Towing Truck Companies