200th Seminar! Travel Time Estimation for Traffic Management and Traveler Information

95
Robert L. Bertini Robert L. Bertini Department of Civil and Environmental Engineering Department of Civil and Environmental Engineering Nohad A. Toulan School of Urban Studies and Planning Nohad A. Toulan School of Urban Studies and Planning Portland State University Portland State University Oregon Transportation Research and Education Consortium Oregon Transportation Research and Education Consortium Transportation Seminar No. 200 Transportation Seminar No. 200 April 4, 2008 April 4, 2008 Travel Time Estimation for Travel Time Estimation for Traffic Management and Traffic Management and Traveler Information Traveler Information

Transcript of 200th Seminar! Travel Time Estimation for Traffic Management and Traveler Information

1Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Robert L. BertiniRobert L. BertiniDepartment of Civil and Environmental EngineeringDepartment of Civil and Environmental EngineeringNohad A. Toulan School of Urban Studies and PlanningNohad A. Toulan School of Urban Studies and PlanningPortland State UniversityPortland State UniversityOregon Transportation Research and Education ConsortiumOregon Transportation Research and Education ConsortiumTransportation Seminar No. 200 Transportation Seminar No. 200 •• April 4, 2008April 4, 2008

Travel Time Estimation for Travel Time Estimation for Traffic Management and Traffic Management and Traveler InformationTraveler Information

2Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

ObjectivesObjectives

Travel time visualizationsTravel time fundamentalsPrevious researchFramework for sensor spacingAnalytical tool for sensor spacingFuture researchSeminar perspectives

Travel time visualizationsTravel time fundamentalsPrevious researchFramework for sensor spacingAnalytical tool for sensor spacingFuture researchSeminar perspectives

3Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

What Can I Do With Travel Time?What Can I Do With Travel Time?

Travel time is fundamentalCan be used to generate other thingsTravel time is multimodal

Travel time is fundamentalCan be used to generate other thingsTravel time is multimodal

4Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

What Can I Do With Travel Time?What Can I Do With Travel Time?

Measure itGuess itReport itPredict itForecast it

Measure itGuess itReport itPredict itForecast it

5Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

If I Get It Wrong?If I Get It Wrong?

Annoy travelersDestroy confidence in systemIncrease congestionWorsen safetyDamage air qualityIncrease fuel consumption

Annoy travelersDestroy confidence in systemIncrease congestionWorsen safetyDamage air qualityIncrease fuel consumption

6Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

How Can I Affect Travel Time?How Can I Affect Travel Time?

Increase/decrease mean valueIncrease/decrease variabilityAffect comparison between modes

Increase/decrease mean valueIncrease/decrease variabilityAffect comparison between modes

7Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

ContextContextContext

“Prediction is very difficult, especially about the future.”

—Niels Bohr

8Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Portland Travel TimesPortland Travel TimesPortland Travel Times

9Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

London UndergroundLondon UndergroundLondon Underground

10Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

London UndergroundLondon UndergroundLondon Underground

11Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

2004 Tsunami2004 Tsunami2004 Tsunami

12Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Runoff Travel TimeRunoff Travel TimeRunoff Travel Time

13Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Fire Station Response TimeFire Station Response TimeFire Station Response Time

14Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

New York Commuter RailNew York Commuter RailNew York Commuter Rail

15Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

2004 Tsunami2004 Tsunami2004 Tsunami

Train journey times from Cambridge

16Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Travel time difference train vs. car from Cambridge

17Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

FundamentalsFundamentalsFundamentals

Time

Dis

tan

ce

Slope = Speed

Travel Time

18Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

FundamentalsFundamentalsFundamentals

Time

Dis

tan

ce

Actual Travel Time

Free Flow Travel Time Actual – Free Flow= Delay

19Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Fundamentals – One DetectorFundamentals Fundamentals –– One DetectorOne Detector

Time

Dis

tan

ce

Travel Time

20Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Midpoint MethodMidpoint MethodMidpoint Method

Influence

Area 4Travel Time 4

(at t = 0)

Travel Time 1Influence

Area 1

Travel Time 3

(at t = 0)

Influence

Area 3

Travel Time 2

(at t = 0)

Influence

Area 2

Link Travel Time

(TT1 + TT2 + TT3 + TT4)

21Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Fundamentals – Two DetectorsFundamentals Fundamentals –– Two DetectorsTwo Detectors

Time

Dis

tan

ce

Travel Time

22Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement ParametersMeasurement Parameters

Fixed LocationsStop Watch Method

Detectors (any kind)RF Toll TagsRF “Sign Posts”Video Image (license plate)Volume Based

Fixed TimesGPS + Wireless CommunicationCellular Phone

Fixed LocationsStop Watch Method

Detectors (any kind)RF Toll TagsRF “Sign Posts”Video Image (license plate)Volume Based

Fixed TimesGPS + Wireless CommunicationCellular Phone

23Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed LocationsMeasurement: Fixed LocationsMeasurement: Fixed Locations

Time

Dis

tan

ce

x1

x2

Location Time

x1

x2

24Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed LocationsMeasurement: Fixed LocationsMeasurement: Fixed LocationsD

ista

nce

x1

x2

Location Time

x1 t1

x2

Time

25Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed LocationsMeasurement: Fixed LocationsMeasurement: Fixed LocationsD

ista

nce

x1

x2

Location Time

x1 t1

x2 t2

Time

t1 t2

26Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed LocationsMeasurement: Fixed LocationsMeasurement: Fixed LocationsD

ista

nce

x1

x2

Location Time

x1 t1

x2 t2

Time

t1 t2

27Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed TimesMeasurement: Fixed TimesMeasurement: Fixed Times

Dis

tan

ce

x1

Time

t1 t2 t3 t4 t5

Time Location

t1 x1

t2

t3

t4

t5

28Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed TimesMeasurement: Fixed TimesMeasurement: Fixed Times

Dis

tan

ce

x1

Time

t1 t2 t3 t4 t5

x2

Time Location

t1 x1

t2 x2

t3

t4

t5

29Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed TimesMeasurement: Fixed TimesMeasurement: Fixed Times

Dis

tan

ce

x1

Time

t1 t2 t3 t4 t5

x3

x2

Time Location

t1 x1

t2 x2

t3 x3

t4

t5

30Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed TimesMeasurement: Fixed TimesMeasurement: Fixed Times

Dis

tan

ce

x1

Time

t1 t2 t3 t4 t5

x4

x3

x2

Time Location

t1 x1

t2 x2

t3 x3

t4 x4

t5

31Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Measurement: Fixed TimesMeasurement: Fixed TimesMeasurement: Fixed Times

Dis

tan

ce

x1

x5

Time

t1 t2 t3 t4 t5

x4

x3

x2

Time Location

t1 x1

t2 x2

t3 x3

t4 x4

t5 x5

32Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Use Counts (TTI Method)Use Counts (TTI Method)Use Counts (TTI Method)

33Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Use Counts (TTI Method)Use Counts (TTI Method)Use Counts (TTI Method)

34Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Flow (vph)

Sp

eed

(m

ph

)

Similar Idea Using Granular DataSimilar Idea Using Granular DataSimilar Idea Using Granular Data

35Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

WSDOT Travel TimesWSDOT Travel TimesWSDOT Travel Times

36Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Data Collection Was DifficultData Collection Was DifficultData Collection Was Difficult

Data CollectionGreenshields, et al., 1947

SpeedometerGreenshields, et al., 1957

37Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: LAFSPPrevious Research: LAFSPPrevious Research: LAFSP

38Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous: Highway 18Previous: Highway 18Previous: Highway 18

39Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: FrontierPrevious Research: FrontierPrevious Research: Frontier

40Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: ODOT VMS IPrevious Research: ODOT VMS IPrevious Research: ODOT VMS I

40

15 directional freeway 15 directional freeway linkslinks87 probe runs87 probe runs516 miles/12 drivers516 miles/12 drivers15 hours of data collected15 hours of data collected

41Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: ODOT VMS IPrevious Research: ODOT VMS IPrevious Research: ODOT VMS I

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Probe Travel Time (min)

Estim

ated

Tra

vel T

ime

(min

)Coifman (u/s)Coifman (d/s)MidpointCoifman - MidpointCoifman - DistwtMidpoint - Average

42Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: ODOT VMS IPrevious Research: ODOT VMS IPrevious Research: ODOT VMS I

43Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Previous Research: ODOT VMS IPrevious Research: ODOT VMS IPrevious Research: ODOT VMS I

00

2

4

6

8

10

12

14

16

0 2 4 6 8 10 12 14

Bus Travel Time (min)

Estim

ated

Tra

vel T

ime

(min

)Coifman (u/s)Coifman (d/s)MidpointCoifman - MidpointCoifman - Distwt

44Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

ODOT Phase II: TufteODOT Phase II: Tufte

Data quality

Congestion

300 ground truth runs on I-5 and OR 217

Other algorithms

Data quality

Congestion

300 ground truth runs on I-5 and OR 217

Other algorithms

45Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

ODOT Phase IIODOT Phase II

Average error ~5-7%Need for more detection, but where?Average error ~5-7%Need for more detection, but where?

0

5

1015

20

25

30

3540

45

50

<-30 -30-20 -20-10 -10-0 0-10 10-20 20-30 >30% Error

% o

f Run

s

# of Runs - 67

II--5 N5 N

0

10

20

30

40

50

<-30 -30-20 -20-10 -10-0 0-10 10-20 20-30 >30% Error

% o

f Run

s

# of Runs - 60

II--5 S5 S

46Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

MotivationMotivation

Ongoing efforts to improve Ongoing efforts to improve freeway travel time estimatesfreeway travel time estimatesDisplay travel time ranges for key Display travel time ranges for key corridorscorridorsDesire to provide additional Desire to provide additional detectiondetectionNeed for Need for ““optimaloptimal”” decisiondecision--making aidmaking aid

47Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Portland ATMSPortland ATMS

Freeway Surveillance 502 inductive loop detectors~175 stations

Dual loop (act as single loop)1.2 mile average spacingUpstream of on-ramps

135 ramp meters98 CCTV

ATISwww.TripCheck.com

Real-time speed mapStatic CCTV images

18 dynamic message signs (DMS) 3 display travel times

Freeway Surveillance Freeway Surveillance 502 inductive loop detectors502 inductive loop detectors~175 stations~175 stations

Dual loop (act as single loop)Dual loop (act as single loop)1.2 mile average spacing1.2 mile average spacingUpstream of onUpstream of on--rampsramps

135 ramp meters135 ramp meters98 CCTV 98 CCTV

ATISATISwww.TripCheck.comwww.TripCheck.com

RealReal--time speed maptime speed mapStatic CCTV images Static CCTV images

18 dynamic message signs (DMS) 18 dynamic message signs (DMS) 3 display travel times 3 display travel times

48Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Freeway Detector LocationsFreeway Detector LocationsFreeway Detector Locations

49Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Portland Speed/Travel Time InfoPortland Speed/Travel Time InfoPortland Speed/Travel Time Info

50Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Bus/Arterial SpeedsBus/Arterial SpeedsBus/Arterial Speeds

51Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Hypothetical x-t PlaneHypothetical Hypothetical xx--tt PlanePlane

x1MeasuredSpeed

i

Actual Travel TimeFree Flow Travel Time

FreeFlowSpeed

Extrapolated Travel Time

l=

Segm

ent L

ength

x

tExtrapolatedSpeed

Over-prediction

t1 = Time Interval

Delay

52Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Freeway Corridor ExampleFreeway Corridor Example

305.67 Columbia

305

300

295

290

285

4:00

8:00

12:0

0

16:0

0

20:0

0

285.26 Wilsonville

291.00 Carman

298.48 Iowa

302.22 Rose Qtr.

80

60

40

20

0

vfvAC

VMSMP

Time 02/08/07 Northbound I-5

DOWNTOWN

1 mile

A

B

DA C

AC CD

vCD DA

53Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Traffic Flow Relation and DynamicsTraffic Flow Relation and Dynamics

q

k

qC

vf vc

vACqA

A

BC

D

A

B

C

D

A

x

t

vCD

bn

tdeact

vCDvAC

vfDAAC CD

Aassumptions:Aassumptions:

1 mile segment1 mile segmentss ~ 0.1~ 0.1--1.0 mile1.0 mileqqA A = 2000 vph= 2000 vphqqC C = 1800 vph= 1800 vphvvf f = 60 mph= 60 mphvvc c = 30 mph= 30 mphvvCD CD = = --17.1 mph17.1 mphvvAC AC = = --7.5 mph7.5 mph

54Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

0

500

1000

1500

2000

2500

0 50 100 150 200Density (veh/mi)

Flo

w (

veh

/h

r)

qA =2000

qC =1800

vf =60

vc =30vCD = -17.1

D

CB

AvAC = -7.5

55Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

0

500

1000

1500

2000

2500

0 50 100 150 200Density (veh/mi)

Flo

w (

veh

/h

r)

Real data I-5 Macadam2/8/07

56Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Types of TransitionsTypes of TransitionsTypes of Transitions

Time

Dis

tan

ce Frontal stationary

Backwardrecovery

Forwardrecovery

Forward forming

Backwardforming

Rear stationary

57Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Types of TransitionsTypes of TransitionsTypes of Transitions

Time

Dis

tan

ce Frontal stationary

Backwardrecovery

Forwardrecovery

Forward forming

Backwardforming

Rear stationary

58Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

d =

l=

Segm

ent L

ength

x

t

A, D, DA: uncongested C: congested

vf vc

ttf = l/vf ttc = l/vc

Estimation When HomogeneousEstimation When Homogeneous

VHT Actual = VHT EstimatedVHT Actual = VHT Estimated

59Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Types of TransitionsTypes of TransitionsTypes of Transitions

Time

Dis

tan

ce Frontal stationary

Backwardrecovery

Forwardrecovery

Forward forming

Backwardforming

Rear stationary

60Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Types of TransitionsTypes of TransitionsTypes of Transitions

Time

Dis

tan

ce Frontal stationary

Backwardrecovery

Forwardrecovery

Forward forming

Backwardforming

Rear stationary

61Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Types of TransitionsTypes of TransitionsTypes of Transitions

Time

Dis

tan

ce Frontal stationary

Backwardrecovery

Forwardrecovery

Forward forming

Backwardforming

Rear stationary

62Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Traffic Flow Relation and DynamicsTraffic Flow Relation and Dynamics

A

B

C

D

A

x

t

bn

tdeact

vCDvAC

vfDAAC CD

63Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

64Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

65Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

66Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

67Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

UNDERUNDER OVEROVER

68Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalα = Lag Time

j1

Shockttf

l

z j3

j2

umaxttf

Transition UncongestedTransition Uncongested CongestedCongested

69Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

x

l

s=0.50

x

s=0.25

x

s=0.10

t

l

t

x

s=0.33

Sensor Density Affects Lag TimeSensor Density Affects Lag Time

70Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition UncongestedTransition Uncongested CongestedCongested

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

7.0

7.5

8.0

8.5

9.0

9.5

VHT

Predicted VHT

Actual VHT

71Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition UncongestedTransition Uncongested CongestedCongested

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r Error (Penalty)

Error (Absolute Value)

OVER

UNDER

Error (Additive)

72Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition UncongestedTransition Uncongested CongestedCongested

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

7.0

7.5

8.0

8.5

9.0

9.5

VHT

Actual VHT

Error (Additive)

Error (Penalty)

Error (Absolute Value)

Predicted VHT

73Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Traffic Flow Relation and DynamicsTraffic Flow Relation and Dynamics

A

B

C

D

A

x

t

bn

tdeact

vCDvAC

vfDAAC CD

74Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

s

tr

vCD

Recovery Signalα′ = Lag Time

vc

vf

j1

Wavettc

l

zj3j2

umax

ttf

Transition CongestedTransition Congested UncongestedUncongested

75Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

s

tr

vCD

Recovery Signalα′ = Lag Time

vc

vf

j1

Wavettc

l

zj3j2

umax

ttf

Transition CongestedTransition Congested UncongestedUncongested

UNDERUNDEROVOV ERER

76Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

s

tr

vCD

Recovery Signalα′ = Lag Time

vc

vf

j1

Wavettc

l

zj3j2

umax

ttf

Transition CongestedTransition Congested UncongestedUncongested

UNDERUNDEROVEROVER

77Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

s

tr

vCD

Recovery Signalα′ = Lag Time

vc

vf

j1

Wavettc

l

zj3j2

umax

ttf

Transition CongestedTransition Congested UncongestedUncongested

UNDERUNDEROVOV ERER

78Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition CongestedTransition Congested UncongestedUncongested

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

3.8

3.9

4.0

4.1

4.2

4.3

4.4

4.5

4.6

4.7

VHT

Predicted VHT

Actual VHT

79Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition CongestedTransition Congested UncongestedUncongested

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

Error (Additive)

Error (Penalty)

Error (Absolute Value)

OVER

UNDER

80Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Transition CongestedTransition Congested UncongestedUncongested

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

3.8

3.9

4.0

4.1

4.2

4.3

4.4

4.5

4.6

4.7

VHT

Error (Additive)

Error (Penalty)

Error (Absolute Value)

Predicted VHT

Actual VHT

81Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

2.0

2.5

3.0

3.5

4.0

4.5

5.0

VHT

Actual VHT

Underprediction OnlyUnderprediction Only

Predicted VHT

82Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

15%

16%

17%

18%

19%

20%

21%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r Error

Underprediction OnlyUnderprediction Only

83Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

15%

16%

17%

18%

19%

20%

21%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

2.0

2.5

3.0

3.5

4.0

4.5

5.0

VHT

Error

Predicted VHT

Actual VHT

Underprediction OnlyUnderprediction Only

84Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Considering Both TransitionsConsidering Both Transitions

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

11.1

11.3

11.5

11.7

11.9

12.1

12.3

12.5

12.7

12.9

13.1

VHT

Predicted VHT

Actual VHT

85Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Considering Both TransitionsConsidering Both Transitions

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

Error (Additive)

Error (Penalty)

Error (Absolute Value)

86Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Considering Both TransitionsConsidering Both Transitions

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

0.0 0.2 0.4 0.6 0.8 1.0Sensor Spacing (miles)

VHT

Erro

r

11.1

11.3

11.5

11.7

11.9

12.1

12.3

12.5

12.7

12.9

13.1

VHT

Error (Additive)

Error (Penalty)

Error (Absolute Value)

Predicted VHT

Actual VHT

87Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalttf=α = Lag Time

j1

Shock

l

z j3j2

umaxttf

Detector at End of SectionDetector at End of SectionDetector at End of Section

88Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

t

x

svc

vf

tc

vAC

Congestion Signalttf=α = Lag Time

j1

Shock

l

z j3j2

umaxttf

Detector at End of SectionDetector at End of SectionDetector at End of Section

89Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Effects of Detector at EndEffects of Detector at EndEffects of Detector at End

Regime ACUnderprediction

DetectorLocation

Umax(Min)

Lag Time(Min)

VHT/MilePred

VHT/MileAct

Under %Error

Midpoint 0.56 4.00 2.78 3.55 22%

Downstream 0.11 0.00 0.56 0.59 5%

OverpredictionDetectorLocation

Umax(Min)

Lag Time(Min)

VHT/MilePred

VHT/MileAct

Under %Error

Midpoint 0.56 4.00 4.44 3.95 -13%

Downstream 0.11 0.00 8.89 6.91 -29%

90Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

The FutureThe Future

Better estimates and forecastsFusion of fixed and mobile sourcesUbiquity of integrated information

In-vehicleIn-deviceMultimodal routing/decision-makingCustomizableBetter management

Better estimates and forecastsFusion of fixed and mobile sourcesUbiquity of integrated information

In-vehicleIn-deviceMultimodal routing/decision-makingCustomizableBetter management

91Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Seminar PerspectivesSeminar Perspectives

Inspired by Berkeley’s Transportation Science Seminar, originated by G.F. Newell, 1965

First seminar October 5, 2000, Benefits of Archived ITS Data: Measuring Capacity at a Freeway Bottleneck

200 seminars completed

Began streaming video October 2002: 165available for download and streaming

Began podcasts (mp3) in October 2007: 30podcasts now available

Venue for student/faculty interaction

Strong involvement of transportation community

Inspired by Berkeley’s Transportation Science Seminar, originated by G.F. Newell, 1965

First seminar October 5, 2000, Benefits of Archived ITS Data: Measuring Capacity at a Freeway Bottleneck

200 seminars completed

Began streaming video October 2002: 165available for download and streaming

Began podcasts (mp3) in October 2007: 30podcasts now available

Venue for student/faculty interaction

Strong involvement of transportation community

92Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

PodcastsPodcastsPodcasts

93Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

Seminar PerspectivesSeminar Perspectives

Organized by graduate students?More social interaction before/after?More point/counterpoint?We’re open to other ideas!First air transportation seminar on May 9Other topics we haven’t covered?

Organized by graduate students?More social interaction before/after?More point/counterpoint?We’re open to other ideas!First air transportation seminar on May 9Other topics we haven’t covered?

94Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information

AcknowledgementsAcknowledgements

Travel time project teams, past and presentKristin Tufte, Sirisha Kothuri, David Lovell, Ben Zielke, Rafael Fernandez, Ed Anderson Sutti Tantiyanugulchai, Roger Lindgren, Monica LealGalen McGill, Jack Marchant, Dennis Mitchell, Oregon Department of TransportationPortland State University Distance Learning Center for making the streaming easyMy colleagues Jennifer Dill, Chris Monsere and John GliebeSeminar enthusiasts and participantsRyan Gratzer

Travel time project teams, past and presentKristin Tufte, Sirisha Kothuri, David Lovell, Ben Zielke, Rafael Fernandez, Ed Anderson Sutti Tantiyanugulchai, Roger Lindgren, Monica LealGalen McGill, Jack Marchant, Dennis Mitchell, Oregon Department of TransportationPortland State University Distance Learning Center for making the streaming easyMy colleagues Jennifer Dill, Chris Monsere and John GliebeSeminar enthusiasts and participantsRyan Gratzer

95Travel Time Estimation for Traffic Management and Traveler InformationTravel Time Estimation for Traffic Management and Traveler Information