Incident-Management Incident-Management In Central ArkansasIn Central Arkansas

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

Incident-Management Incident-Management In Central ArkansasIn Central Arkansas

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

2

Motorist

sAn Integrated and Shared SystemAn Integrated and Shared System

IncidentS

ystem

Operator

s

3

Incident Management ActivitiesIncident 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 StudyGoals 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)

Incident Data of Arkansas Arkansas State Police Report (2000 ~ 2003)

rural or urban type of collisions

weekdays light conditions

roadway alignment

roadway profile

weather alcohol involvement

crash

severity

road system counties larger municipalities

Frequency

7

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 Architecture of Software System

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 ModelIncident 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 IncidentsReported & potential Incidents

Risk = 20%

Workload = 3×20 min

Potential workload at v=20

Delay at f = 80 min

11

Comparison between Rotation and SIMAN

Rotation SIMAN

Total Number of Vehicle Dispatches

66,757 66,757

Total Delay Cost (veh-min) 259,787,280.00 208,343,664.00

Mean of Work Time (min) 34.54 27.90

Standard Deviation of Work Time (min)

11.18 9.51

12

Multicriteria Routing Module

1

6

2

4

3

5

7

8

0

1215

13

11

9

10

14

13

Operational Model – Dynamic Routing

Operational Model – Dynamic Routing

15

10

10

15

CBA

0

5

10

15 35

2525

IntermediateStarting Arrival

20 35

14

Arkansas Crash Data for 2003

Fatal Injury PDO Fatalities Injuries

557 28,125 42,222 641 52,474

15

Users

Motorists

Operators Managerscxv

Environment

Travel Time

Incidents

System

Data Input & Analysis

Core Algorithms

Output Platforms

Functional Structure of the Prototype Incident Command Center

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?Thanks. Any Question?

http://syen.ualr.edu/metalab

20

Planning & Operational ModelsPlanning & 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.

21

Schedule of Incident ServiceSchedule 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 OptimizationPlanning 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.

23

Dominant ToursDominant Tours

Wt.Set

Tour Original Tour Dist.Expected

TimeTime Variance Risk Index

10-11-

10-15-00-12-11-8-9-10-

9-8-11-12-0-15-039.02 41.76 6.92 0.681

20-10-

11-15-00-12-11-8-9-10-

14-12-0-15-039.72 41.25 6.02 0.564

30-10-

11-15-00-12-14-10-14-

12-11-12-0-15-043.56 44.10 5.74 0.568

40-10-

11-15-00-12-14-10-9-8-

11-13-7-15-042.83 44.74 6.57 0.563

24

Path Dist, Time, Var & Risk on Network Path Dist, Time, Var & Risk on Network

NODES 0 10 11 15

0 ----

0.7595 0.7256 0.5231 0.4971

0.2840 0.2888 0.2312 0.3450

0.2405 0.2500 0.2168 0.1608

10

0.7595 0.7256 0.5231 0.4971

----

0.4409 0.4612 0.5520 0.4942

1.0000 0.9756 0.7399 0.6579

11

0.2840 0.2888 0.2312 0.3450

0.4409 0.4612 0.5520 0.4942

----

0.5245 0.5388 0.4480 0.5058

15

0.2405 0.2500 0.2168 0.1608

1.0000 0.9756 0.7399 0.6579

0.5245 0.5388 0.4480 0.5058

----

25

An ExampleAn Example

26

Objective functionObjective 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

27

10

4030

50f(1)

v(2)

2

1

Incident parametersIncident parameters

λ Z1 Z2 Z3 Z4 Z5

f(1) 0.0142 0.718 0.192 0.070 0.019 0.000

v(2) 0.0046 0.594 0.246 0.101 0.055 0.004

Df Dv --------- 1×20 2×20 3×20 4×20 5×20

Wf=3×20

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

28

Node v(2)

Node f(1)

10

4030

50f(1)

v(2)

2

1

Incident workloadIncident workload

R t0 t1 t2 t3 t4

0.2 15.69 86.81 ∞ ∞ ∞

R t0 t1 t2 t3 t4

0.2 48.22 146.4 ∞ ∞ ∞

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

29

Operational Model – Dynamic Routing

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 DetectionWork in Progress: Incident Detection

32

Functional ICC/TMC

33

Administrative RemarksAdministrative 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