11

Decision Support under Uncertainty

Liping Fu, Ph.D., P.EngAssociate Professor

Department of Civil Engineering

UniversityUniversityof Waterlooof Waterloo

22

Outline

Part I: ITSPart II: Transit Planning and OperationsPart III: Winter Road MaintenancePart IV: A Few More…

33

Part I: Intelligent Transportation Systems (ITS)

Part I: Intelligent Transportation Systems (ITS)

ITS - better management and better information

Route Guidance and Fleet Operations

Uncertainties:TrafficIncidentWeather

Is ITS really going to help me?

44

1. Route Guidance under Uncertainty

Destination

Decision point

Start?

Key Issues:Dynamic and stochastic travel time

Large network

Availability of real-time info

User preferenceµ(T)

Link travel time

55

What We DidWhat We Did

Developed algorithms for solving the

dynamic and stochastic shortest path

problems (e.g., adaptive routing)

Developed new heuristic algorithms

Developed models for estimating

dynamic and stochastic travel times

(e.g., artificial neural network models)Information Extraction

Hidden Layer

Output

.

.

.

O-D travel time

XY

Origin (xo,yo)

Destination (xd,yd)

Distance Information

Information on origin

Information on destination

. . .

. . .

. . .

Input

66

2. Fleet Scheduling under Uncertainty

+1+1

+2+2

+3+3 --22

--11

Key Issues:

Dynamic and stochastic travel time

Benefits of AVL, comm., dispatching...

77

What We DidWhat We Did

Developed algorithms for solving the routing problem with dynamic and stochastic travel times

Developed a computer software package (FirstWin)

Developed a simulation software (SimParatransit)

88

3. Changeable Message Signs (CMS) – Where to Locate?3. Changeable Message Signs (CMS) – Where to Locate?

Uncertainties:

Benefits of CMS?

Route choice

behavior?

99

What We DidWhat We Did

ts

Cum

ulat

ive

Num

ber

of V

ehic

les

Timets+T1 ts+T2 ts+T3

Total Travel TimeSavings - TTSa

x(t)

to

x(t)

^Da^

T1

T2

T3

CMS

1 2 3INCIDENT

T*

TS(t)β-αe11P(t) •+

=

Developed a location

optimization model

Route choice

Path-based traffic

assignment

Genetic algorithm

1010

Part II:

Transit Planning and OperationsPart II:

Transit Planning and Operations

1111

1. Evaluate Transit Quality of Service1. Evaluate Transit Quality of Service

System

Availability

Frequency Service Span Coverage

Travel Time

Reliability

Loading

Routes

Stops

Convenience&Comfort

Evaluation FrameworkEvaluation Framework

Key Issues:Too many measuresNo comprehensive measureDo not consider demand

1212

What We DidWhat We Did

Developed A new performance index that integrates all performance measures in TCRP manual

Consider demand distribution (O-D)Consider traffic network congestionGIS based (TransCAD)

1313

2. Transit Operations Control Problem2. Transit Operations Control Problem

Control Methods:HoldingStop skippingShort turning

Vehicle bunching…

1414

Transit Operations ControlTransit Operations Control

( )

( )

( )

loadbusandalightingboardingonequationsStatedepartureandarrivalbusonequationsStatets

yrc

yrUc

HHL

HLUcyZmin.

otherwisejstopskipsibusif

yvariableDecision

i

N

jjijij

i

N

jk

k

jffififjki

i

N

j

jijiji

jijiji

ji

,..

)(

)(

22)(

10

:

2

1 2,,3

2

1

1-N

1j 1 1,,,2

2

1 1

,1,,1

,,1,1

,

−−

+++

⎟⎟⎠

⎞⎜⎜⎝

⎛+++

⎟⎟⎠

⎞⎜⎜⎝

⎛⎟⎟⎠

⎞⎜⎜⎝

⎛++−=

⎩⎨⎧==

=

∑∑

∑∑ ∑ ∑

∑∑

= =

= = += +=

= =

−−−

δτ

δτ

Developed a holding control model

Developed a stop-skipping control model

Developed a simulation model

Bus i

i+1

Di+1, f(f

-

1(k))

Time

CurrentTime

Ai,kDi,k

Stop 0 (for bus i!)

Stop 1

Stop k-1

Stop k

…

Bus i-1

1515

Part III: Winter Road MaintenancePart III: Winter Road Maintenance

Monitoring Processing Decision-making

Data Sources(Weather, ARWIS, TM, Patrol Reports, Traffic, Resources)

Strategic&OperationalDecisions:

Optimization

RoadSurface

Conditions:

Estimation &Forecasting

RoadWeather

Conditions:

Estimation &Forecasting

1616

1. Effectiveness of Chemicals

Uncertainties:Comparative performance of alternative chemicals and treatment methods?Factors influencing snow melting trend ?

1717

What We DidWhat We Did

Compared the performance of pre-wetted salt vs. dry salt

Compared the performance of alternative pre-wetting chemicals

Identified the factors influencing the effectiveness of pre-wetting

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

3:00 5:24 7:48 10:12 12:36

Time

Snow

Cov

er

CaCl2 Snow Cover Trend

Pre-wetted Rock Salt at 7%CaCl2

Plough Only

MgCl2 Snow Cover Trend

Pre-wetted Rock Salt at 7%MgCl2

Rock Salt - 56 kg/lane-km

1818

2. Road Surface Conditions Monitoring

New Technologies:RWISFriction devicesWeb-cam…Spectroscopic sensors

Issues:Alternative performance measures?Spatial and temporal variation?Correlation among the condition measures?

1919

3. Other Issues on Winter Road Maintenance

Performance benchmarking

Facility location (depot, RWIS stations, FAST, …)

Road surface conditions forecasting

Real-time routing and scheduling of maintenance operations

under uncertain road weather and traffic conditions

Impacts of adverse weather on traffic and driver behavior

Simulation …

2020

Part IV:

More Topics…Part IV:

More Topics…

GradeX – A decision support tool for hotspot identification and countermeasure analysis (with Prof. F. Saccomanno)

Traffic monitoring via cellular phone based location referencing (with Prof. B. Hellinga)

2121

Thanks

☯ 知不知上, 不知知病Knowing ignorance (uncertainty) is strength,Ignoring knowledge (about uncertainty) is sickness

- Lao Tzi (Chinese philosopher, B. C. 500)