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CHAPTER 3
Data Collection and Processing
3.1 Introduction agency or source. Before initiating an independent data collec-
tion effort the analyst should first see if the data they need is
This chapter provides guidance on the collection of travel already being collected by other agencies. If so, analysts should
time, delay, and variability data from TMC, as well as other assess the extent to which this data meets their needs.
sources. The purpose of this chapter is to advise the analyst Using data being collected for other purposes saves on data
on the development of a data collection plan to support collection costs, which are not insignificant. Using data
measures of travel time, delay, and reliability data for use in already being used for other purposes also is likely to ensure
typical planning applications. that the data is of acceptable quality. However, the data may
This chapter is designed to address two very different data not be in exactly the format or contain all of the variables
collection situations that the analyst is likely to confront. Most required by the analyst. Additional time and effort may be
agencies will either be data-rich or data-poor. A data-rich needed to fill gaps and reformat the data to satisfy the needs
agency will have continuous surveillance capabilities on some of the analyst.
of the facilities being studied, usually from a TMC. A data- A custom data collection effort has the advantage that the
poor agency may have typical traffic volume data, but must analyst gets exactly the data they need for the study. However,
put in place temporary data collection equipment or vehicles the set-up time and cost of custom data collection efforts are
to gather travel-time data. high. Exhibit 3.1 lists some of the typical advantages and
Both data-rich and data-poor agencies can estimate mean disadvantages of using data collected for other purposes to
travel time and mean delay using the strategies described in generate travel time performance measures. The term typical
this chapter. This guidebook provides methods for estimat- is used to alert the reader that conditions, cost, and quality
ing mean travel time and mean delay for either data-rich or vary; each situation should be examined to reveal its unique
data-poor situations. Recommended minimum sample sizes characteristics.
are provided in this chapter. Exhibit 3.2 highlights typical agency or third-party travel
In contrast, data-poor agencies generally cannot measure time and delay data collection programs.
travel-time reliability very well in the field without significant The FHWA publication, Travel-Time Data Collection
expense to gather the required data. An agency must have con- Handbook is an excellent source of information on the
tinuous surveillance capabilities, or nearly so, in order to de- strengths, weaknesses, and costs of various travel-time data
velop useful, cost-effective measures of reliability. As such, this collection methods. Exhibits 3.3 and 3.4 highlight the
guidebook does not provide a method for estimating travel- strengths and weaknesses of various travel-time data collec-
time reliability for data-poor situations, and no minimum tion methods.
sample sizes are provided for estimating travel-time reliabil-
ity. The analyst generally must have continuous monitoring
capabilities in order to adequately estimate reliability. 3.3 Data Collection Sampling Plan
It is necessary to develop a sampling plan to collect data for
selected time periods and at selected locations within the re-
3.2 Data Collection Methods
gion. Data collection that supports the desired analysis and
Analysts have the option of conducting their own travel-time measures will be more cost-effective and less problematic if a
data collection effort or obtaining the needed data from another rigorous sampling plan is first developed.
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Option Typical Advantages Typical Disadvantages
Custom Data Collection Tailor to specific analysis needs Expensive
Greater quality control Time-consuming to collect
Obtaining Data from Others Less expensive May not be exactly what is needed
Readily available Quality less well known
Exhibit 3.1. Advantages/disadvantages of using data collected for other purposes.
3.3.1 Sampling Strategies beyond the means of most urban areas (unless the system is
for O-D Trip Time Monitoring 100 percent instrumented with permanent vehicle detectors
or travel time data collection devices). Even if the system is 100
The collection of origin to destination trip times can be percent instrumented, the number of locations and the
very expensive because of the numerous possible origins volume of data may be much greater than the analyst can han-
and destinations within any region. A region divided dle. In either case it becomes desirable to reduce the resources
into 1,000 traffic analysis zones will have 1,000,000 possible required by focusing on a select sample for freeway or road
O-D combinations. In addition, there are numerous paths system segments within the region.
between each O-D pair to further complicate the process of A wide variety of sampling strategies are possible. The
trip-time measurement. following two are described to illustrate the approach.
The analyst must therefore adopt a stratified sampling If the objective of the study is to obtain travel-time meas-
approach to reduce the measurement problem to a tractable urements that could be used to characterize overall system
size. A wide range of sampling strategies may be pursued, performance then one sampling strategy would be to collect
depending on the objectives of the analysis. Two strategies data every 5 miles (or every 10th detector) on the system. The
are described here to illustrate the general approach. length and mean speed for each sample location would be
The first sampling strategy described here seeks to gather measured. The travel-time results for the individual sample
travel-time data representative of the region as a whole. segments would be expanded to system totals and averages
Possible O-D pairs are grouped into 10 categories (The num- using the ratio of total system miles to sample miles, or the
ber of categories is determined by the analyst based upon the ratio of total system vehicle-miles traveled to the vehicle-miles
resources available to perform the data collection.) according traveled on the sample sections.
to the minimum path trip length between each O-D pair. For If the objective of the study is to identify system deficien-
example the O-D pairs might be grouped into those with trip cies, then the analyst might adopt a different sampling
lengths under 5 miles, those with trip lengths between 5 and strategy that focuses on system bottlenecks. Travel-time
10 miles, etc. The analyst then randomly selects three O-D information would be collected only for the congested peri-
pairs from each category and measures the travel time several ods or days and only on the higher volume segments of the
times for each O-D pair. The results can be summed to obtain regional freeway system.
regional totals by weighting the average travel time results for
each category by the number of trips contained within each
category.
3.3.3 Sample Size Requirements for
Another strategy would be to group the zones into super-
Estimating Mean Delay or Travel Time
districts. Three zones would then be randomly selected from
each super-district and the travel times measured for the Travel time varies randomly from hour to hour, day to day,
selected zone pairs. The results can be aggregated weighting and week to week throughout the year. It is never adequate to
the average travel times according to the number of trips measure travel time only once. The analyst must measure the
represented by each super-district. travel time between two points several times and compute the
average travel time from the data.
This section describes how to estimate the minimum num-
3.3.2 Sampling Strategies
ber of travel-time observations that would be required. The
for System Monitoring
minimum number of observations is determined by preci-
If it is desired to develop travel-time information for the re- sion desired by the analyst. If the analyst needs to know the
gional freeway system (or surface street system), collection of mean travel time very precisely, a large number of observa-
travel time for 100 percent of the road system will probably be tions will be required.
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Agency Comments
State DOTs On freeways within major urban areas the state DOT may have continuous
count stations with counts and point speeds available every half mile of
freeway and most ramps. In some states (e.g., Washington and California) the
data may be available on a real-time basis over the Internet.1
Floating car measurements of mean segment speed may be gathered on an
annual basis for certain freeways in major urban areas as part of a congestion
monitoring program.
For freeways outside of major urban areas (and conventional state highways
everywhere in the State), the state DOT may have a couple of weeks of hourly
count data collected quarterly at scattered count stations. Speed, travel time,
and delay data are not typically gathered at count stations outside of major
urban areas.
Counts, speed, and other data are often collected on an "as-needed" basis for
upcoming highway improvement projects.
Traffic Management Centers TMCs gather real-time speed and volume data for freeway segments at
intervals that typically range from one-third to one mile. Data in some cases
stored for longer than 24 hours. Detector reliability can be low depending on
maintenance budget. A few TMCs (Los Angeles ATSAC for example) gather
real-time volume data for city streets. TMC speed data for urban streets are
generally considered less reliable.
MPOs MPOs conduct travel behavior surveys every 5 to 10 years in which they ask
travel-time information. MPOs involved in congestion management may
commission annual surveys of peak-period speeds and travel times on specific
road segments.
Local Agencies Counties and cities gather traffic count data generally as part of specific
studies for improvement projects. Speed data on road segments may be
measured every few years in support of enforcement efforts (radar spot speed
surveys).
Private Company Several private companies collect travel time or speed data to disseminate as real-
time traffic information. Other companies offer vehicle fleet monitoring
services for real-time fleet management and dispatching, and may save
"anonymized" vehicle position data that could be used to calculate travel
time-based measures. A key consideration for this type of data is the
negotiation of data rights such that the privately owned data can be used as
needed by public agencies.
American Community Survey The ACS is the annual replacement for the decennial census travel data. Some
commuting measures are available if a region has invested in additional
surveys to ensure statistical reliability at the local level.
National Household Travel As states have taken a more active role in measuring and forecasting travel
Survey demand, the NHTS is becoming more important as a source of state-level
indicators for transportation planning and performance measurement.
Products, such as the state profiles, freight data and statistics, seasonality
statistics, etc., provide agencies with improved ability to apply national travel
behavior data to local, regional, and state performance measurement and
forecasting.
1
The California Department of Transportation (Caltrans) has teamed with Partnership for Advanced Technology on Highways
(PATH) at the University of California, Berkeley, to store traffic data and make it available on-line. Access to this data, known as
the Freeway Performance Measurement System (PeMS), can be requested at http://pems.eecs.berkeley.edu/public/index.phtml.
The Minnesota Department of Transportation (Mn/DOT) has a data collection and storage center at its Twin Cities office that
integrates traffic, weather, and traffic incident data. Mn/DOT's Regional Transportation Management Center (RTMC) can be
reached at www.dit.state.mn.us/tmc/index.html. Interested parties may visit their office and download desired data onto a storage
device. The State of Washington's DOT, the first to archive real-time traffic data in the United States, will download requested
information onto a suitable storage device such as a CD (see http://www.wsdot.wa.gov/traffic/seattle/traveltimes).
Exhibit 3.2. Potential sources of travel time, delay, and reliability data.
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Accuracy for
General Purpose
Vehicle Travel
Method Time Variability Geographic Time of Day Modes Comments
Floating Cars Excellent. Limited ability to Best for single Best for limited Not practical for Floating cars are cost inefficient for gathering travel
GPS collect variability facilities. Very peak periods. gathering bike time and delay, but the technology is commonly
DMI data. costly to acquire Too costly for data. available and easy to apply.
data for extensive obtaining 24-hour Too costly to collect data over broad arterial network or
geographic area. data. in nonpeak periods. Not practical for OD travel times.
Feasible, but very costly to collect data for transit and
freight modes.
Transit Schedules Fair. Does not provide Full coverage of No data outside Transit only. Average transit travel times can be approximated with
data on variance. region is service hours. transit schedules if transit agency has good schedule
inexpensive. compliance.
Not uniformly reliable for individual routes; may
supplement with on-time performance statistics.
Not reliable for systems that do not routinely monitor
on-time performance.
Retrospective Limited because Limited ability to Full geographic Unlikely to obtain No Freight. Retrospective surveys which rely on travelers'
survey of respondents' collect variability area coverage good travel-time memories are generally less precise than prospective
Home memories and data due to possible; costs data for light surveys.
Telephone tendency to rounding of vary. travel periods of Good for obtaining OD trip times, although times not
Employer round travel reported times. day (overnight). likely to be more accurate than to nearest 5 to
times. 10 minutes.
Piggyback on
Other Efforts Costs decrease as tolerance for bias increases (sampling
can be less rigorous (e.g., using employee surveys or
web surveys)).
Other variations on sampling possible.
Many MPOs currently conduct commuter surveys; may
be possible to piggyback on those current surveys.
Prospective Fair to Good. Fair. Full coverage Unlikely to obtain No Freight. Prospective survey where the traveler is contacted in
Home Survey costly. good travel-time advance and asked to record all trip making the next
(Manual Trip data for light day are generally more precise than retrospective
Diary) travel periods of surveys.
day (overnight). Good for obtaining OD trip times.
Most expensive and most accurate traveler survey
method.
GPS diaries have excellent accuracy but increase costs
and require a long-term implementation timeframe.
Exhibit 3.3. Travel-time data collection methods requiring little or no technology investment.
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Method Accuracy Variability Geographic Time of Day Modes Observations
Freight Tracking Excellent. Yes, but limited Coverage All Only Freight. Reliance on carriers to provide data likely impractical
by sample size. dependent on due to imposition on carrier.
Logs
participants.
Loaner GPS units costly but provide incentive for
GPS
carrier participation and increase accuracy.
TMC Roadside Excellent (for spot Excellent Full coverage All Best for freeways. Loop infrastructure unreliable without significant
Sensors speeds, assuming costly. maintenance commitment.
adequate
Loops/RTMS Possible to extrapolate travel time from speed data,
maintenance).
(spot speeds) depending on accuracy need.
Vehicle signature matching, under development; may
generate travel-time data in the long term.
ETC Passive Excellent. Excellent. Full coverage All All, bike possible. ETC tags cheap, but roadside readers costly; therefore
Probes costly. costly to get broad coverage, especially on arterials
and therefore on transit.
Deployed successfully for other purposes.
Vehicle type identification nontrivial to implement.
Areawide Passive Excellent. Good. Full coverage All No bike. GPS units currently expensive and complicated to
Probes (GPS) inexpensive. install (by operators); costs may decrease, but this is a
risk factor.
Collecting data from GPS units is costly, and likely
inconvenient.
The only nonsurvey method that can collect door-to-
door travel time.
Transit Good. Yes, but limited Depends on All Transit; may be Transit agencies are using a variety of tracking
Monitoring by sample size. routes and roads used to estimate systems to provide on-time data to their patrons. This
Systems covered. general purpose data can be synthesized for use in general-purpose
travel as well. traffic monitoring.
License Plate Excellent. Excellent. Full coverage All No bike. Manual matching possible in short-term, but cost
Matching with costly. prohibitive without (long term) advances in OCR.
OCR
Video equipment also expensive, especially to cover
broad arterial network; therefore limited transit
coverage.
Exhibit 3.4. Travel-time data collection methods requiring major technology investment.
