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1Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Robert L. Bertini, Christopher Monsere, Robert L. Bertini, Christopher Monsere, Michael Wolfe and Mathew BerkowMichael Wolfe and Mathew BerkowPortland State UniversityPortland State University2008 CITE District and Quad Regional Conference2008 CITE District and Quad Regional ConferenceApril 28, 2008April 28, 2008
Using Automatic Vehicle Location Data to Using Automatic Vehicle Location Data to Determine Detector PlacementDetermine Detector Placement
2Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
ObjectiveObjective
Develop an automated way to report speeds, travel times and performance measures using: Existing ITS signal infrastructure Automatic Vehicle Locator (AVL) data
Expand PORTAL to include arterial data
Develop an automated way to report speeds, travel times and performance measures using: Existing ITS signal infrastructure Automatic Vehicle Locator (AVL) data
Expand PORTAL to include arterial data
3Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Selected Arterial Performance MeasuresSelected Arterial Performance MeasuresSelected Arterial Performance MeasuresSelected Arterial Performance Measures
TABLE 1 SELECTED ARTERIAL PERFORMANCE MEASURES
Metric Measurement Interval Location Maximum Speed
per Vehicle per Person
per Distance per Time
(cycle, 15 min, hour, day)
per Lane per Lane Group per Approach per Segment per Facility
per Area
Average Speed Speed Indexa Density Running Time Travel Time Travel Time Variance Average Delay Maximum Delay Queue Length Platoon Ratio Number of Stops Signal Failure Duration of Congestion per Day Number of Incidents per Day/Peak Period Duration Incidents per Event Nonrecurring Delay aRatio of average speed to posted speed.
4Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Inspiration – Signal System Data OnlyInspiration – Signal System Data OnlyInspiration – Signal System Data OnlyInspiration – Signal System Data Only
5Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Inspiration – Bus AVL System Data OnlyInspiration – Bus AVL System Data OnlyInspiration – Bus AVL System Data OnlyInspiration – Bus AVL System Data Only
I-5
I-5
I-205
US 26
SR 217
Powell Blvd.
6Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
This Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVL
7Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Signal System DataSignal System DataSignal System DataSignal System Data
8Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
DDDD
Signal System Data:Signal System Data:Portland’s Portland’s Detection Detection InfrastructureInfrastructure
Signal System Data:Signal System Data:Portland’s Portland’s Detection Detection InfrastructureInfrastructure
Data AggregationData AggregationCount Station Count Station
5 min5 minOther Detector Other Detector
15 min15 min7 Day Sample7 Day Sample
9Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Case Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed Map
SheridanHooker
Hamilton
3rdTerwilligerBertha
19th
I-5 Off-ramp
30th
Park & Ride
N
10Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Detectors at Barbur and BerthaDetectors at Barbur and BerthaDetectors at Barbur and BerthaDetectors at Barbur and Bertha
11Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Density vs. OccupancyDensity vs. Occupancy
Density = number of vehicles per distance
Occupancy = percent of time with a vehicle on the sensor
Density = Occupancy X 1/(vehicle length + sensor length)
Density = number of vehicles per distance
Occupancy = percent of time with a vehicle on the sensor
Density = Occupancy X 1/(vehicle length + sensor length)
Density = 2 vehicles / 45 feet =.044
45’12’
6’
Density = .80 * 1 / (12 + 6) = .044
Occupancy = 80%
12Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Flow vs. Occupancy: 5 Minute DataFlow vs. Occupancy: 5 Minute DataFlow vs. Occupancy: 5 Minute DataFlow vs. Occupancy: 5 Minute Data
Barbur & Hamilton, Northbound 2-12-07 to 2-20-07
0
500
1000
1500
2000
2500
3000
3500
4000
0 10 20 30 40 50 60 70 80
Occupancy (%)
Flo
w (
v/h
)
13Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)
0
10
20
30
40
50
60
70
80
90
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
Time
Sp
eed
(m
ph
)
0
10
20
30
40
50
60
70
80
Occ
up
ancy
(%
)
Speed
Occupancy
14Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Barbur Northbound Contour PlotBarbur Northbound Contour Plot
15Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
AM Peak Speed Map From Detector DataAM Peak Speed Map From Detector DataAM Peak Speed Map From Detector DataAM Peak Speed Map From Detector Data
16Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
ConclusionsConclusions
Lack of Access to Real Time Data Limited Detection Very Limited Aggregation (5 Minute Won’t
Work) Detector Spacing
Lack of Access to Real Time Data Limited Detection Very Limited Aggregation (5 Minute Won’t
Work) Detector Spacing
17Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Bus AVL System DataBus AVL System DataBus AVL System DataBus AVL System Data
18Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
TriMet Archived AVL DataTriMet Archived AVL DataTriMet Archived AVL DataTriMet Archived AVL DataR
ou
te N
o.
Ser
vice
D
ate
Lea
ve T
ime
Sto
p T
ime
Arr
ive
Tim
e
Bad
ge
Dir
ecti
on
Tri
p N
o.
Lo
cati
on
ID
Dw
ell
Do
or
Lif
t
On
s
Off
s
Est
. L
oad
Max
Sp
eed
Pat
tern
D
ista
nce
X C
oo
r.
Y C
oo
r.
9 01NOV2001 8:53:32 8:49:15 8:53:28 285 0 1120 4964 0 0 0 0 0 21 41 10558.58 7644468 676005
9 01NOV2001 8:55:00 8:51:41 8:54:46 285 0 1120 4701 4 0 0 0 1 20 50 15215.05 7649112 676328
9 01NOV2001 8:56:22 8:52:00 8:55:08 285 0 1120 4537 36 3 0 6 0 26 34 15792.35 7649674 676220
Route Number Vehicle Number Service Date Actual Leave Time Scheduled Stop Time Actual Arrive Time Operator ID Direction Trip Number Bus Stop Location
Dwell Time Door Opened Lift Usage Ons & Offs (APCs) Passenger Load Maximum Speed
on Previous Link Distance Longitude Latitude
19Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
0
0.5
1
1.5
2
2.5
3
1:04:00 PM 1:09:00 PM 1:14:00 PMTime
Dis
tan
ce (
mil
es)
Ross Island
Bridge
Test VehicleBusHypothetical BusPseudo BusModified Pseudo Bus B
us
Hyp
o
Pse
ud
oM
od
ified
Pse
ud
o
Veh
icl
e
Powell Blvd. Corridor StudyPowell Blvd. Corridor StudyPowell Blvd. Corridor StudyPowell Blvd. Corridor Study
20Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Building on Powell Blvd. StudyBuilding on Powell Blvd. StudyBuilding on Powell Blvd. StudyBuilding on Powell Blvd. Study
Begin with limited signal system data.Begin with limited signal system data.
Gather Gather archivedarchived TriMet AVL data. TriMet AVL data.
Merge two data sources to examine synergies due to Merge two data sources to examine synergies due to data fusion.data fusion.
Use AVL data to calibrate influence areas from loops.Use AVL data to calibrate influence areas from loops.
21Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07
22Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07
23Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Midpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute Data
24Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Adjust Influence Areas ManuallyAdjust Influence Areas ManuallyAdjust Influence Areas ManuallyAdjust Influence Areas Manually
25Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Bus Data Confirms AdjustmentBus Data Confirms AdjustmentBus Data Confirms AdjustmentBus Data Confirms Adjustment
26Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Reveals Gaps in DetectionReveals Gaps in DetectionReveals Gaps in DetectionReveals Gaps in Detection
27Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
New Occupancy Map From Combined SourcesNew Occupancy Map From Combined SourcesNew Occupancy Map From Combined SourcesNew Occupancy Map From Combined Sources
28Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
An Improvement Over Mid-Point MethodAn Improvement Over Mid-Point MethodAn Improvement Over Mid-Point MethodAn Improvement Over Mid-Point Method
29Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Average Link Travel TimesAverage Link Travel TimesAverage Link Travel TimesAverage Link Travel TimesNorthbound - Mean Travel Time
ActualHypo-
thetical PseudoModified Pseudo
Loop Detectors
Pseudo * 1.25
Signal + Bus
Weekday Morning Peak (n = 38) 15.31 6.11 7.71 9.89 14.90 9.64 10.79
Weekday Midday Off-Peak (n = 132) 12.84 7.02 7.30 8.94 11.09 9.12 7.97
Weekday Evening Peak (n = 46) 13.83 7.95 7.80 9.54 13.14 9.75 8.36
Northbound - Mean Speed
ActualHypo-
thetical PseudoModified Pseudo
Loop Detectors
Pseudo * 1.25
Signal + Bus
Weekday Morning Peak (n = 38) 17.63 44.18 35.00 27.29 18.12 28.00 25.03
Weekday Midday Off-Peak (n = 132) 21.03 38.45 37.01 30.21 24.34 29.60 33.87
Weekday Evening Peak (n = 46) 19.52 33.94 34.60 28.30 20.55 27.68 32.29
30Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Average Link Travel Times – AM PeakAverage Link Travel Times – AM PeakAverage Link Travel Times – AM PeakAverage Link Travel Times – AM Peak
Travel Time Observations (95% CI)Travel Time Observations (95% CI)Travel Time Observations (95% CI)Travel Time Observations (95% CI)
Link
Tra
vel T
ime
(Min
)Li
nk T
rave
l Tim
e (M
in)
Link
Tra
vel T
ime
(Min
)Li
nk T
rave
l Tim
e (M
in)
ActualActualActualActual HypoHypoHypoHypo PseudoPseudoPseudoPseudo Mod.Mod.PseudoPseudoMod.Mod.
PseudoPseudoLoopLoop
DetectorsDetectorsLoopLoop
DetectorsDetectorsPsuedoPsuedo* 1.25* 1.25
PsuedoPsuedo* 1.25* 1.25
Signal-BusSignal-BusSignal-BusSignal-Bus
31Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Conclusions and Next StepsConclusions and Next Steps
TriMet Buses Can Be Probes Detailed AVL Data (Stop Level) Not Available
in Real Time (?) No Access to Real Time Data (Transit Tracker) Travel Times Limited by Detector Data
TriMet Buses Can Be Probes Detailed AVL Data (Stop Level) Not Available
in Real Time (?) No Access to Real Time Data (Transit Tracker) Travel Times Limited by Detector Data
32Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
AcknowledgementsAcknowledgements TransPort Members FHWA: Nathaniel Price ODOT: Galen McGill PSU & OTREC (Local Matching Funds) City of Portland: Bill Kloos, Willie Rotich TriMet: David Crout, Steve Callas JPACT and Oregon Congressional Delegation ITS Lab: John Chee, Rafael Fernandez
TransPort Members FHWA: Nathaniel Price ODOT: Galen McGill PSU & OTREC (Local Matching Funds) City of Portland: Bill Kloos, Willie Rotich TriMet: David Crout, Steve Callas JPACT and Oregon Congressional Delegation ITS Lab: John Chee, Rafael Fernandez
33Using Automatic Vehicle Location Data to Determine Detector PlacementUsing Automatic Vehicle Location Data to Determine Detector Placement
Thank You!www.its.pdx.edu