1. Traffic Estimation with Space-Based Data
Mark R. McCord
NCRST-F
The Ohio State University
Workshop on
Satellite Based Traffic Measurement
Berlin, Germany
9-10 September 2002

2. Satellite Imagery for Vehicle Identification
High Resolution Required
Cars 1m - 2m panchromatic
Trucks 4m panchromatic

3. High Resolution
=> Low orbits
=> Limited temporal sampling
(dynamic traffic)
=> Long time scale, geographically extensive applications
=> Traffic Monitoring
Average Annual Daily Traffic (AADT)
Vehicle Kilometers Traveled (VKT)

4. Y. Yang,C. Merry, Past Students
Improved AADT and VKT Estimation from High-Resolution Satellite Imagery
Acknowledgments
P. Goel, Z. Jiang, B. Coifman,
Y. Yang,C. Merry, Past Students

5. National, Regional Network Coverage AADT and VKT

6. Average Annual Daily Traffic Vehicle Kilometers Traveled
AADT: Traffic on a highway segment
AADTs  Σ=1,365 V24s,  / 365
V24s,   24-hour volume, segment s, day 
VKT: Travel over the network
(avg daily) VKT = Σs=1,S Lengths * AADTs

7. Estimating AADT on System
(Permanent) Automatic Traffic Recorders
V24s, ,  = 1, 2, …, 365, s  Spatr
~3% segments equipped with PATRs
=> Calculate AADTs s  Spatr
=> Estimate temporal variability
(“expansion factors”)
e.g., EF() = EFMD[m(),d()], m() = 1,2, …, 12
d() = 1, 2, …, 7

8. Estimating AADT on System (cont.)
Moveable ATRs (Coverage Counts)
V24s, , V24s, +1,   {1, 2, …, 364},sSmatr
~33% segments per year
=> Estimate AADTs s  Smatr
AADTests = f[V24s, , V24s, +1, EF(), EF(+1)]
e.g. AADTests = [V24s, /EF()+V24s,+1/EF(+1)]/2

9. Estimating AADT on System (cont.)
Unsampled Segments in Year, Suns
(S= Spatr  Smatr  Suns)
AADTs  Suns = f[AADTs’, s’  SpatrSmatr], s  Suns
e.g. AADTs  Suns = Average[AADTs’, s’  SpatrSmatr]
AADTs  Suns = f[AADTs sampled in previous year, network growth factors]

10. Accuracy Sampling, Estimation Methodology Cost Large Labor and Equipment Expenses

11. Satellite Imagery Potential Difficulty Added Data Off-the-Road
Spatial Perspective
Access of Remote Areas
Difficulty
Unfamiliar (Density Based)
Potential Error (“Short Interval” Observation)

12. Original
Image
Binary
Image

13. Flowest(x,t+t) = Density(x+x,t)*Velocity(x+x,t)
Flowest(x,t+t) [vph]
t short (3-15 minutes)
V24,ests,  = f[Flowest(x,t+t; s,), EFh(h(t))]
e.g., V24,ests,  = 24*Flowest(x,t+t; s,) / EFh(h(t))
EFh: hourly expansion factor

14. V24,ests,  = f[Flowest(x,t+t; s,), EFh(h(t))]
AADTimgs = f[ V24,ests, , EFMD[m(),d()] ]
EFMD: seasonal factor (month-of-year, day-of-week)

15. Relative Error (AADT Image-based – AADTTrue) / AADTTrue AADTTrue  AADTGround-based

19. Relative Errors, RE N = 18 N(RE > 0) = 12 N(RE < 0) = 6
Sample Mean = 0.03
Sample St. Dev. = 0.15
RELATIVELY UNBIASED

20. Sample St. Dev. (w. mean = 0) = 0.15 Lower RE with better AADTGr-based
Relative Errors, RE
Sample St. Dev. (w. mean = 0) = 0.15
Maximum RE = 0.34
Lower RE with better AADTGr-based
Equiv. Count Interval: 0.6 – 12.6 mins
SURPRISING, PROMISING PERFORMANCE

21. RE Decreases with Increased Simulated Time Interval

22. NETWORK LEVEL ANALYSIS

23. Computer Simulation Inputs Outputs Traffic Patterns
AADT distribution, Link Lengths, EFM, EFD
- Ground-Based Sampling
• % Permanent ATR’s (PATR’s)
• % Coverage Counts (MATR’s)
Satellite-Based Sampling*
Variability/Error/Random Terms**
Outputs
- AADT and VKT (VMT) Estimation Error
• Ground-Based Data Only
• Satellite- and Ground-Based Combination

24. Satellite-Based Sampling* Physical Relations
FCD[lat1,lat2] = 2(1-Fnpgt)*NPIX*RES*NORB
*L[lat1,lat2;i, NORB])10-3)/EAR[lat1, lat2] (5)
NORB = 8,681,665.8/ (R+H)1.5 [orbits/day] (9)
H > 200 km => NORB < 16.3 [orbits/day] (10)
H = (FL/WPI)(RES)(103) [km] (12)
NORB>8,681,665/((FL/WPI)max(RES(103)+6371)1.5 [orb/day] (14)
Vsg = (NORB) [km/sec] (17)
DBR = 3.706(NORB)(NPIX)(10-3)/(RES*COMP) [Mbits/sec] (18)
(NPIX)( NORB) < (RES)(DBR*COMP)max (20)

25. Satellite-Based Sampling* Maximal Coverage
(P1) Max: Z1=NORB*NPIX*L[lat1,lat2;i,NORB]
NORB,NPIX,i
s.t. 90 < i < 180
8,681,665.8/((FL/WPI)max RES(103)+6371)1.5
< NORB < 16.3
0 < NPIX < NPIXmax
(NPIX)(NORB) < 269.8(RES)(DBR*COMP)max

26. Satellite-Based Sampling. : Daily Coverage vs
Satellite-Based Sampling*: Daily Coverage vs. Resolution and Inclination Angle

27. Variability/Error/Random Terms**
Ground-based sample: (gr)
V24(gr)s, = AADTs*EFMM()-1 *EFDD()-1
* exp((gr) - (gr)2/2),
(gr) ~ N(0, (gr))
(gr): Daily deviation from deterministic model
Satellite-based sample: (sat)
V24(sat)s, = AADTs*EFMM()-1 *EFDD()-1
* exp((sat) - (sat)2/2),
(sat) ~ N(0, (sat))
(sat): Error in Expanding Short-Duration Counts
and Daily Variability

30. Impact of Satellite Supply
— Equivalent Satellite Coverage (ESC)

32. Extensions More image- vs. ground-based comparisons
Expansion of short-interval flows
Improved hourly factors
Quantification of uncertainty in sub-hour expansion
Bayesian and model-based estimation
Spatial correlations
Satellite and air-based sampling strategies
Other Uses of Volume Data
Statewide truck OD estimation
Screening tool: growth factors, ground-based sample strategies
Implementation strategies …