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CE 451 - Urban Transportation Planning and ModelingIowa State University
Calibration, Adjustment and ValidationSources:
Calibration and Adjustment of System Planning Models Note: Date = 1990 (need to adjust for inflation, other changes)
Model Validation and Reasonableness Checking Manual
NHI course on Travel Demand Forecasting (152054A)
Objectives:
• Identify and interpret trends affecting travel demand • Explain difference between calibration and validation• Identify critical reasonableness checks
– socioeconomic– travel survey – network – trip generation – mode split – trip assignment
Terminology• Model Calibration
– Estimate parameters– Match observations (OD, AADT)
• Model Validation– Reasonableness checks– Sensitivity checks
• Special generators• Screen lines, cut lines, cordons
Is the model sensitive to policy options?
Planner responsibilities• Actively involve all participants
– Modelers– Planners– Decision makers– Public
• Fairly present all alternatives– Timely– Unbiased
• Identify (clearly) the decision making process– Who, when, and how– Allows input from all interested groups
• You must rely on the TDM– Therefore, must be validated– Accurate and easy to understand (documented)
www.readysetpresent.com
Scrutinize these characteristics: • Data requirements• Logic of structure and conceptual appeal • Ease of calibration • Effectiveness of the model (accuracy, sensitivity)• Flexibility in application• Types of available outputs• Operational costs• Experience and successes to date• Public or private domain availability
How do you judge a model/recommend improvement?
cio.com
• Planners should monitor the following trends:– Demographics– Composition of the labor force– Immigration and emigration– Regional economic development– Modal shares– Vehicle occupancy– Average trip length– Freight transport
• Are trends consistent with assumptions made in the modeling process?
Must be aware of trends to ensure reasonable forecasts
Trends Affecting Travel Demand
Image sources: scu.edu; usda.gov; illinois.edu; uwex.edu; mwcog.org; fhwa.gov; transportation1.org
How sensitive is travel
to fuel price?
http://www.eia.doe.gov/oiaf/aeo/pdf/trend_4.pdf
doe.gov
Tips for building a good model*• Build accurate road network• Use aerial photos behind• Make sure road attributes are
correct, esp. traffic• Use hourly counts• Income and auto ownership don’t
fully explain travel• age, gender, life cycle and personal
interest come into play• Use survey data
– visualize these data– Survey can be done cheaply – Cooperation will be good if there’s a
good reason for it – mayor sends letter, e.g.
• Employer based surveys get good response (but may be biased)
– Some will give home addresses, customer addresses, license plates
• Use trip chaining (tour based) and activity based trip generation
• We don’t know much about attractions – ITE sample too small – do your own
• Drive the network using GPS• Get some data and do some statistics
to derive your parameters
*Howard Slavin, Caliper Corp. 3/13/04 peer review
Tips for building a good model*• Some models are completely made
up except traffic counts– See if you really believe the counts
• Create your OD matrix from ground counts
– May be better than trip gen/dist if you “made up” the whole model (no surveys)
– TransCAD has a tool for this– If still want to use trip gen/dist, this
method can be used to determine K factors
– Could also use the row and column totals as the dependent variables in your trip gen model
*Howard Slavin, Caliper Corp. 3/13/04
• Examine individual links after model run
– Where are the trips coming from and going to that use the link?
– In TransCAD, what is the process used to determine this (for a particular link)?
– In TransCAD, what is the process used to show where traffic from a particular zone is going to?
• Familiarity with your region is helpful
Sources of Error
• Coding• Sampling• Computation (if done by
hand)• Specification• Data Transfer• Data aggregation
Improper structure of model, e.g., wrong variables
• Not enough attention on model evaluation and reasonableness checks
• Checks should be performed after each step– reduces error propagation
Errors can also “cancel”
Key Concepts
Reasonable?Methodology?
Source?
Current?Reasonable?
Complete?Level of Detail?
Sensitive?Documentation of
calibration?Valid for base year?
Evaluation and Reasonableness Checks Overview
Transportation Transportation systemsystem(supply)(supply)
►Network DataNetwork Data
Number and location Number and location of households and of households and
employment (demand)employment (demand)►Socioeconomic DataSocioeconomic Data
TDFTDF►Model SpecificationModel Specification►Model validation and calibrationModel validation and calibration
Travel Travel survey datasurvey data
Transportation Transportation systemsystem
performanceperformance
Model CalibrationModel Calibration
Model ValidationModel Validation
Model ApplicationModel Application
Feed
back
Loo
pCALIBRATION and VALIDATION are sometimes confused.Model development is sometimes called calibration or estimation as we are estimating parameters and constants for the particular model structure.estimating is a statistical process … want high correlation coefficients and significant parameter valuescan "import" a model - or borrow structure and parameters from a "similar" areaVALIDATION is checking if the model is accurately estimating traffic volumes by calculated measures (like RMSE)
“Transportation Conformity Guidelines” (Air Quality) require model validated < 10 years ago
Model Validation
• Validation of new model– Model applied to complete model chain– Base year model compared to observed travel– Judgment as to model suitability, return to calibration
if not• Validation of a previously calibrated model
– Compare to a new base year, with new …• SE data• Special gen.• Network• Counts
- Systemwide- compare traffic counts across …
- Screenlines - (long lines, check major flows)
check trip interchange (distribution) between large sections or quadrants
- need a survey; local knowledge of commute patterns helps
- Cordon lines (surround a major generator, e.g. university, CBD...)- Cutlines (shorter, verify corridor flows, fine tuning)
if "importing" should validate all borrowed parameters and constants
Validation suggestions
IT IS VERY IMPORTANT TO HAVE A GOOD COUNT PROGRAM DESIGNED TO SUPPORT VALIDATION!
iowadotmaps.com
The Calibration and Adjustment manual is not intended to replace good OD data, and is intended more for small urban areas. (and has some old data in it! – more recent data area available in the Barton-Ashman publication).
To "calibrate" the model, need an OD database from a survey. This is time consuming and expensive. Few, if any cities have developed OD databases since 1980, but many have updated old ones since then using a small survey (e.g. 1%)
Calibration and Adjustment Steps:
1) verify network and socioeconomic data2) run the model3) develop region-wide values (e.g. trips/person, vmt/person)4) compare region wide values with “Appendix A” values5) develop screenlines and cutlines6) compare model results with ground counts for crossings7) determine problems (system level, local, combination)8) modify one or more equations, parameters or variables according to chapters on:
- networks- trip generation- auto occupancy- trip distribution- traffic assignment
Other chapters focus on:- transit- external stations- system vs. local changes- expected vs. required accuracy- conclusions- trouble shooting
Network Data Reasonableness Checks
• Check Trees for 2-3 major attractions*• Check coded facility types – how used (BPR?)?• Verify speed and capacity look-up table (what LOS used
for capacity?)*– Speed adjust (can lower the freeway speed if it is being
overloaded – tweak?)• Significant transportation projects – narrative included?
Still viable?• Consistency with MTP• Plot (facility types, # lanes,
speeds, area types) to detect coding errors*
* Items we can check in labs
Details2. Network Errors2.1 Centroid Connectors- represent local streets- check access (all 4 sides?)- not connected to intersections- make sure they are not blocked by a physical barrier (river, etc.)
Des Moines Model Capacity Look-up Table
Des Moines Model Capacity Look-up Table (cont.)
Des Moines Model Capacity Look-up Table (cont.)
Des Moines Model Capacity Look-up Table (cont.)
2.3 Intersection Penalties (check them!)- most congestion here- more important in sub-area modeling- turn penalties- account for congestion
- speed volume function- can include delay on approach links- can do it manually for small networks
-check for circuity (correct with small turn penalties!)
-See TransCAD Manual B “Chapter 10: Traffic Assignment with Volume Dependent Turning Delays”
2.4 Intrazonal times
• increasing intrazonal trips (in distribution) decreases interzonal trips (useful if too many trips are being loaded on the network)
•number of trips is a function of travel time (gravity model)
-can adjust travel time on intrazonals-can adjust friction factor curve to produce more shorter trips (which intrazonals usually are)-can change definition of zones (size, land use)
•Air quality analysis implications???
3.1 Trip generation- socioeconomic data can be a source of error- initial step is to check system trip totals, compare w/ Table 4 and A1 and A2 (next pages)- if there is a problem, check the system number of dwelling units- still a problem?, check production/attraction rates
Trip Generation CalibrationReasonableness checks – compare to other cities, check
future trends• Population 503,345• Households 201,116• Average Household Size 2.50• Basic employment 76,795 (33%)• Retail employment 50,465 (24%)• Service employment 101,697 (43%)• Military employment 42,800• Population per employee 1.81• Person trips per person 4.26• Person trips per household 10.65• HBW attractions per employee 1.44• HBW productions per household 1.74• HB shopping attractions per retail employee 5.99
Colorado Springs 1996 Travel Demand Model Calibration
Tabl
e A2
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
More recent data …
3.2 Income- be sure you are using “real” dollars
3.3 P and A rates• Problems: old, borrowed, small survey• may work OK at the system level, but not for sub-areas• check system-wide values (see tables, next pages)
– raise or lower trip generation rates– Person trip or vehicle trip rates used?
• we usually have person trip by purpose, but can apply occupancy factor and check against vehicle rates (ITE)
• later, screen line counts can be adjusted by varying trip generation rates (post assignment)
• check cutlines and cordon counts
- coordinate all of the above
homeNon-
Trip Generation CalibrationTypical Values
• Person trips per household: 8.5 to 10.5• HBW person trips per household: 1.7 to 2.3• HBO person trips per household: 3.5 to 4.8• NHB person trips per household: 1.7 to 2.9• HBW trips: 18% to 27% of all trips• HBO trips: 47% to 54% of all trips• NHB trips: 22% to 31% of all trips
More recent data …
Trip Generation Reasonableness Checks• Examine trip production and attraction models
– Form?– sensitivity?– IMPORTANT: keep parameters reasonable (e.g. don't use negative coefficients in
regression models just because they provide the best fit.)• If you think you need to use unintuitive parameters, check the whole process...
• Check models for …– External-through and external-local trips– Truck trips
• To calibrate trip generation and trip distribution, sometimes we may use ...
– default values from past surveys– very limited new surveys– census journey to work data (CTPP)
Scale survey for participation (relative participation)
Note: each
income class is a purpose!
TRIP PURPOSES Scaling Factor
HBW low income 0.795
HBW low-middle income 0.823
HBW middle income 0.861
HBW upper middle income 0.908
HBW high income 0.936
HB elementary school 0.733
HB high school 1.991
HB university 0.895
HB shopping 0.698
HB social-recreation 0.945
HB other 0.875
NHB work-related 0.858
NHB other 0.820
Truck 0.985
Internal-external 0.591
Examine trip purposes used … Use more trip purposes?
Colorado Springs 1996 Travel Demand Model Calibration
Travel Survey Data Reasonableness Checks
• Determine source of travel survey data – Types of survey conducted– Year of survey
• Scale survey for participation • If no survey (borrowed)
– Check source of trip rates, lengths, TLFD– Is area similar
• Geographic area?• pop/HH/empl. characteristics?• Urban density and trans system?
• Compare to similar regions and to same region in earlier times:
– Person trip rates by trip purpose– Mean trip lengths by trip purpose
• HBW longest? HBO shortest?– TLFDs by trip purpose
Socioeconomic Data: Check Reasonableness
• Review source for estimates and forecasts• Visualize (plot) trends …
– Population and household size– Household income– automotive availability– distribution of employment by type (basic, retail, service)– employees per household and per capita … rate of increase is
decreasing• Check future household and employment changes by zone
3.4 Special generators-e.g. universities, airports, malls, ... -Use ITE or survey
3.5 trip balancing factors4.0 Auto occupancy
• initially, Ps and As should balance to should be 0.9 to 1.1; if not, check your PA rates and socioeconomic data
• NHB is usually out of balance• Automobile occupancy
– by trip purpose?– Basis? – Constant?
• see table 6 and A9 (next pages … are these still good?)
5.0 Trip Distribution
5.1 Mean Trip Length- recall: shape of curve affects trip length distribution-See below for effect of changing friction factors
F Curve trips link vols. internal vols.
F
ttmore long trips
more short trips
-varying trip length has a big impact on assigned volumes
-portions of a friction factor table can be adjusted (more flexible than adjusting equations)
5.2 Estimate Trip Length-compare average trip lengths (in minutes) by purpose to:
HBW t = 0.98 x p.19
HBSR t = 2.18 x p.12
HBSh t = 8.1NHB t = 0.63 x p.20
where p is population
SR = social/recreationSh = shopping
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
Source: Virginia Travel Demand Modeling Policies and Procedures Manual
Source: Virginia Travel Demand Modeling Policies and Procedures Manual
Source: Virginia Travel Demand Modeling Policies and Procedures Manual
5.3 Employment Distribution Problems (large cities, mostly)
problem: match low income households with low income jobs
solution #1: disaggregate trip purposes by income quartile
solution #2: use k-factors (trial and error) … yuk
Jobs/Housing
Imbalance!
5.4 Special Treatment, other trip purposes
- schools (ignore if small %?)- trucks (calibrate with externals?)-Taxi
normally, distortions are insignificant
Trip Distribution Reasonableness Checks
Examine …• Mean trip length (increasing or decreasing?)• TLFDs• Treatment of friction factors (same?)• Treatment of terminal times (logic?)• Treatment of K factors• Comparison with JTW trip length• Comparison with JTW sector interchange volumes or
percentages.
Calibrate friction
factors
1st iteration
Calibrating Friction Factors
Travel TimesTravel TimesRanges from Ranges from SkimsSkims
Observed Trip Observed Trip Expanded from Expanded from SurveysSurveys
Input Input Friction Friction FactorsFactors
Gravity Gravity Model TripsModel Trips
Adjustment Adjustment FactorFactorObservedObservedGravity Gravity ModelModel
New Friction New Friction FactorsFactorsFriction Friction AdjustmentAdjustmentFactor x Friction Factor x Friction FactorFactor
2.52.5 7,1007,100 30.030.0 8,2008,200 0.870.87 25.9825.98
5.05.0 14,95014,950 2.502.50 16,30016,300 0.920.92 2.292.29
7.57.5 17,85017,850 1.801.80 19,25019,250 0.930.93 1.671.67
10.010.0 16,00016,000 1.501.50 19,10019,100 0.840.84 1.261.26
12.512.5 15,50015,500 1.201.20 17,10017,100 0.910.91 1.091.09
15.015.0 15,90015,900 1.001.00 12,30012,300 1.291.29 1.291.29
17.517.5 16,40016,400 0.950.95 18,00018,000 0.910.91 0.870.87
20.020.0 15,15015,150 0.900.90 14,30014,300 1.061.06 0.950.95
22.522.5 13,50013,500 0.850.85 11,90011,900 1.131.13 0.960.96
25.025.0 11,00011,000 0.800.80 9,2509,250 1.191.19 0.950.95
27.527.5 9,5009,500 0.750.75 8,1008,100 1.171.17 0.880.88
30.030.0 9,1009,100 0.700.70 6,1006,100 1.491.49 1.041.04
32.532.5 5,7005,700 0.650.65 4,9004,900 1.161.16 0.760.76
…… …… …… …… …… ……
Calibrating a Gravity ModelAdjusting Friction Factors
2nd iteration
Commute Length in Commute Length in MinutesMinutes PercentPercent
Journey-to-WorkJourney-to-WorkFlowsFlows PercentPercent
< 15< 15 27.8727.87 Central-CentralCentral-CentralCountyCounty
31.4931.49
15-2915-29 41.6341.63 Central-SuburbanCentral-SuburbanCountyCounty
7.487.48
30-3930-39 17.0417.04 Suburban-Central Suburban-Central CountyCounty
15.1315.13
40-5940-59 7.707.70 Within Suburban Within Suburban CountyCounty
32.9832.98
>60>60 3.003.00 To Other Suburban To Other Suburban CountyCounty
10.8110.81
Mean 21.44Mean 21.44 Work out of areaWork out of area 2.112.11
Trip Distribution Calibration and Validation
• Check modeled vs. household survey TLFD and mean trip lengths• Get HBW area-to-area flows from JTW
HBW 1990 JTW TLFD and Area-to-Area Flows for Kansas City
Using cell phone and/or GPS location to determine travel patterns is nothing new. But leave it to Google to make it really easy - maybe too easy.http://googleblog.blogspot.com/2009/08/bright-side-of-sitting-in-traffic.html Adam ShellOffice of Systems PlanningIowa Department of Transportation
Link
OD data are destroyed! (privacy)
POA: price of anarchy (30%?)Nash equilibrium vs. system optimality
OD validation
6.0 Traffic assignment
6.1 All or nothing
- adjusting link speeds will change assigned volumes
- initial speeds should be set to LOS C speeds (0.87 x free flow speeds)
6.2 capacity restraint
- volume = f(time)- final volume is average of all iterations or later iterations can be weighted more heavily- adjust free flow time or c (capacity) to change volumes
IF… THEN…
Link Speed Travel AssignedCapacity Time Volume
6.2.1 definition of capacity
design: LOS C (0.87c)ultimate: LOS E (1.00c)
parameters differ depending on definition of capacity …
if defined as LOS C, 0.15(v/c)4
if defined as LOS E, 0.80(v/c)4 (see HCM)
6.3.2 free speeds in systems with good
progression should be coded at about 1.1 times
the speed limit time- more than 10 iterations may be needed for
small areas
6.3 equilibrium - multiple paths may be
selected
7.0 Transit Ridership- for small/medium cities, may not have to build a transit network
- If not using a transit network, can use the following method (if trip generation includes transit trips):
1. increase auto occupancy by transit percentage (e.g. if auto occupancy is 1.05, then change to 1.05 x 1.38 = 1.45) if transit percentage is 38%2. decrease trip production or attraction rates (one of them only, then balance) … if you use productions, can vary mode split by income class3. modify productions or attractions by zone - get data from transit company - adjust socioeconomic data or make direct P/A adjustments
Mode Split Reasonableness Checks• Mode split model? • Form?• Variables included in the utility functions?
• Coefficients logical?• Value of time assumptions• Parking cost assumptions
• How do mode shares change over time?
• Mode share comparisons with other cities
http://www.bts.gov/publications/journal_of_transportation_and_statistics/volume_08_number_02/html/paper_05/figure_05_03.html
• Experienced planning consultant required …– Form of LOGIT model– Variables included in utility functions– Calibration of coefficients for utility function variables– Testing for IIA properties– Analysis of household survey data– Analysis of on-board transit survey data
• Calibration tasks we can do:• Compare highway and transit trips
• Total• By purpose
• Compare Ridership by route• CBD cordon line survey (if bus service is downtown only)
Mode Split Calibration and Validation
8. External stations- externals have no socioeconomic data- Ps and As are prepared by matching ground counts- I/E treated with the gravity model-E/E
- compare with Table 11 below
9. System vs. local checks
check 1. system wide (screenlines)2. major movements (cutlines)3. links
if all screenlines are high or low, vary- auto occupancy- trip generation rates- trip lengths- intrazonal times - all zones- socioeconomic data - all zones
if corridor volumes are high or low, vary (for zones affecting corridor…)- auto occupancy - trip generation rates- intrazonal travel times- land use- centroid connectors- intersection penalties
if links are high/low, vary - speed- intersection penalty- centroid locations- special generators- local network configuration
10. Expected/Required accuracy
We are concerned about errors that would require a design change (e.g. number of lanes)
Note that ground counts also contain error Perfectly calibrated models produce link estimates with 1/3 above
the standard error in ground counts and 2/3 below the standard error.
Need ground counts for 65% of freeways and arterials, and a good sample from other facilities
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
10. Expected/Required accuracy (cont.)
The correlation coefficient should be greater than .88 VMT estimate (region-wide) should be within 5% (take care to
compare same roads in systems) VMT/person should be 17-24 for large areas, 10-16 for smaller areas
(see also Table A7, next page) VMT/household should be 40-60 for large areas, 30-40 for smaller
areas
From CTRE Employment Data Project:
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
Source: Virginia Travel Demand Modeling Policies and Procedures Manual
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
Source: Virginia Travel Demand Modeling Policies and Procedures Manual
From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
• All-or-nothing assignment • study effect of increasing capacity• Compare to Equilibrium assignment
• Check volume delay equation (BPR parameters)• Compare
• screen line volumes• Cut line volumes
• Time-of-day assignments?• Source of factors• Peak spreading used for future?• If not, conversion factors source?
(peak hour to 24-hour) • Local VMT (% assigned to
intrazonals and centroid connectors All or
Nothing
Equil
ibrium
Trip Assignment Reasonableness Checks
Assignment calibration
performed last
Trip Assignment Calibration and Validation
Overall VMT or VHT check• 40 to 60 miles per day per HH in large metro areas• 30 to 40 miles per day per HH in medium metro• +/- 10% OK on screen lines• Sign is important
Compute by …- volume group- facility type- transit assignments- time of day
12. TROUBLE SHOOTING
Other Factors Impacting Forecasted Travel Demand
• Can be implied in travel surveys (but not explicit)– Telecommuting– Flexible work hours– HB business
• How to account for …– Aging population– Internet shopping– Roadway congestion (will it affect generation in the future)– New modes
Issues for modeling
• Transferability of parameters– More research is needed
• Forensic analysis– How well did the models work?
• Confidence and Credibility– How to improve
• “Official” versions vs. what-if models– Integrity of the model
• Need more transparency, documentation, appropriateness of techniques