Traffic Data Quality Analysis
James Sturrock, PE, PTOE, FHWA Resource Center Operations Team
Source Material Traffic Data Quality Measurementhttp://ntl.bts.gov/lib/jpodocs/repts_te/14058.htm
Seven DEADLY Misconceptions about Information Qualityhttp://www.fhwa.dot.gov/policyinformation/hpms/dataquality.cfm
Traffic Analysis Toolbox http://ops.fhwa.dot.gov/trafficanalysistools/
Traffic Data Recommendations
Air Quality Conformity Analysis Models
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Air Quality Conformity Analysis
VMT by vehicle class, hour and functional classification
10%
At a given location 50% - Two weeks per month, 24 hours
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Within three years of model validation year
75% Freeways/Expressways 25% principal and minor arterials 10% collectors
VMT by hour and vehicle classification (Distribution of VMT by speed)
+- 2.5 mph At a given location 25% - one week per month, 24 hours
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
75% Freeways/Expressways 25% principal and minor arterials 10% collectors
Traffic Demand Forecasting Models
Standard demand forecasting for Long Range Planning
Daily traffic volumes
Freeways: 7% Principal Arterials: 15% Minor Arterials: 20% Collectors: 25%
At a given location 25% - 12 consecutive hours out of 48-hour count
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Within three years of model validation year
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Hourly traffic volumes
Freeways: 7% Principal Arterials: 15% Minor Arterials: 20% Collectors: 25%
At a given location 25% - 12 con-secutive hours out of 48-hour count
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Vehicle occupancy 10-15%
At a given location 25% - 12 con-secutive hours out of 48-hour count
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
1-5% of total population (from surveys)
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Standard demand forecasting for Long Range Planning
Percentage single unit trucks Percentage combination trucks
7-10% 3-5%
Minimum 25% - 12 consecutive hours out of 48-hour count Minimum 50% - 12 consecutive hours out of 24-hour count
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Transit boardings and alightings by station and/or stop
15-20% 7-10% (Transit Planning)
75% of annual data collection
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
100% of rail boardings10% of bus route ridership from screen line data
Transit vehicle speeds by analysis time period
15-20% <5% - one peak and one off-peak route
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts
Within three years of model validation year
100%
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Standard demand forecasting for Long Range Planning
Free Flow link speeds 15-20%
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within three years of model validation year
100% Freeway mileage 100% Major arterial mileage 80-100% Collectors mileage 10% Local road mileage
Congested link speeds
At V/C < 1.0, 10 mph At V/C >1.0, 2.5 mph
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within three years of model validation year
100% Freeway mileage 100% Major arterial mileage 80-100% Collectors mileage 10% Local road mileage
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Traffic Simulation Models
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Traffic simulation
Traffic volumes by minute or sub-minute
2.50% 90% validityUp to 15% failure rate - portable traffic counts
Within one year of study 100% of study area
Turning movements by 15 minutes
5-10% error rate95% validity -manual traffic counts
0% failure - manual traffic counts
Within one year of study 100% of study area
Free Flow link speeds 5.00%
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within one year of study 100% of study area
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Traffic simulation
Congested link speeds and delay statistics
2.50%
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within one year of study 100% of study area
Queue length 95% validity -manual count
100% validity -manual count
Within one year of study 100% of study area
Congestion Management
Congestion management
Corridor-level vehicle speeds and/or travel times by hour
5%
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within six months of study 100% of study area
Origin-Destination travel times by hour 5%
90-100% validity for instrumented floating car data collection
90-100% validity for instrumented floating car data collection
Within six months of study
1-5% of study area (from surveys)
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Highway Performance Monitoring System
Highway Performance Monitoring System
AADT
5-10% Urban Interstate 10% Other urban 8% Rural Interstate 10% Other Rural Mean Absolute Error
80% continuous count data 70-80% for portable machine counts (24-/48-hour counts)
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Data three years old or less
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
K factor D factor
5-10% RMSE (relative) 1% RMSE (relative)
80% continuous count data 50% for portable machine counts (24-/48-hour counts)
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Data three years old or less
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Percent combination and single-unit trucks - Daily
20% RMSE 15% RMSE
80% continuous count data 50% for portable machine counts (24-/48-hour counts)
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Data three years old or less
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Highway Performance Monitoring System
VMT 5-10% RMSE Downward bias
80% continuous count data 50% for portable machine counts (24-/48-hour counts)
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Data one year old or less
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Percent combination and single-unit trucks -Peak
25% RMSE 20% RMSE
80% continuous count data 50% for portable machine counts
Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations
Data three years old or less
55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Monthly Count Station Volume Reports
Monthly count station volume reports
Hourly volumes for seven consecutive days each month
2% RMSE 100% valid data 100% valid data required
Data one month old or less
<1% of total roadway mileage
AVC stations: Hourly volumes by vehicle class category
15% Single-Unit Truck Classification Error
100% valid data 100% valid data required
Data one month old or less
<1% of total roadway mileage
Transportation Planning Applications
Data Quality Attribute:1
Accuracy2
Data Quality Attribute:
Completeness
Data Quality Attribute: Validity
Data Quality Attribute:
Timeliness
Data Quality Attribute:
Typical Coverage
Generalized Coverage DiscussionTraffic Planning Application Typical Coverage (Generalized from above)
Air Quality Conformity Analysis 75% of Freeways, 25% of Arterials, 10% of Collectors
Traffic Demand Models 60% of Freeways, 25%of Arterials, 15% of Collectors
Traffic Simulation Models 100% of Freeways, Arterials,& Collect
Congestion Management 100% of Freeways, Arterials, &Collect
HPMS 60% of Freeways, 25% of Arterials, 15% of Collectors
Monthly Count Sta. Report <1% of Total Roadway Milage
There are seven potentially fatal misconceptions about information quality that can hamper an information quality initiative.
Worse yet, if these misconceptions are strongly held, they will hamper business effectiveness (best case) or result in business failure.
The seven deadly misconceptions are:
The seven deadly misconceptions are:1. "Information quality is data cleansing" 2. "Information quality is data assessment" 3. "Conformance to business rules is the same as data accuracy" 4. Accuracy"; and its counterpoint: Information quality is fitness for
purpose" 5. "Information quality problems are caused by information producers; and
its corollary: Information quality is produced by an information quality group"
6. "Information quality problems can be edited out by implementing business rules"
7. "Information quality is too expensive"
Congestion Patterns are DynamicPortland DTA Study Example
Speed : Space-Time diagram with trajectories
Travel Times Are DynamicPortland DTA Study Example
Change in travel time for vehicles traveling entire route between 4PM and 6PM
Original network
Changes Influence Traveler BehaviorPortland DTA Study Example
Change in travel time for vehicles traveling entire route between 4PM and 6PM
Comparison of original network to alternative network
Traffic Modeling CalibrationReference Traffic Analysis Toolbox
Determine MOEs for calibration early in process to frame data needs
Utilize Statistical Methods for determining appropriate number of runs utilizing two MOEs
Calibrate to both global and local MOEs
Calibrate, Calibrate, Calibrate!
Source Material Traffic Data Quality Measurementhttp://ntl.bts.gov/lib/jpodocs/repts_te/14058.htm
Seven DEADLY Misconceptions about Information Qualityhttp://www.fhwa.dot.gov/policyinformation/hpms/dataquality.cfm
Traffic Analysis Toolbox http://ops.fhwa.dot.gov/trafficanalysistools/
Thank you
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