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For 2002, the percent of freeway mileage covered ranged from 9% to 99 ... A Tale of Traffic in Two Cities: Austin, Texas vs. Los Angeles, California ... – PowerPoint PPT presentation
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Title: P1251947088URoQk
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FHWAs Mobility Monitoring Program Monitoring
Mobility and Reliability Using Archived Traffic
Operations Data Shawn Turner (shawn-turner_at_tamu.e
du) and Tim Lomax (t-lomax_at_tamu.edu), Texas
Transportation Institute Rich Margiotta
(ram_at_camsys.com), Cambridge Systematics,
Inc. Dale Thompson (dale.thompson_at_fhwa.dot.gov),
Office of Operations, Federal Highway
Administration
EXECUTIVE SUMMARY
PROGRAM DESCRIPTION
- WHAT WE DO
- Monitor freeway performance and analyze trends in
mobility and reliability using archived traffic
operations data. - Provide proof of concept and technical
assistance to foster local/regional performance
monitoring programs and the supporting data
collection and archives. - SOME MORE DETAILS ON WHAT WE DO
- Gather archived data from traffic management
centers (for 2002 data, 23 cities participated by
providing archived data). - Perform quality checks and create standard
datasets (5-minute traffic volume and speed by
lane, with processing metadata). - Calculate travel time-based mobility and
reliability measures. - Use a variety of graphics and tables to
illustrate mobility and reliability trends, as
well as underlying data quality - Share and discuss the results with FHWA, state,
and local agencies. - Buy more data storage and return to Step 1
above. - WHAT WE HAVE LEARNED IN THE PAST 3 YEARS
- Data Quality Affecting Applications Data quality
varies widely and may be limiting the credibility
and application of results in some cities.
Several cities have acceptable data quality and
are integrating the archived data and performance
measures into key decision-making processes. In
some cities, limited roadway coverage precludes
certain analyses. In other cities, incomplete or
inaccurate data limits its credibility and
hampers use of the data for decisions. - Agencies Are Implementing Program Elements
Various elements of the Mobility Monitoring
Program are being locally implemented. For
example, several agencies are using the quality
checks for their data archives. Other agencies
have adopted some of the analysis techniques
and/or performance measures.
- Mobility Measures
- Travel Time Index ratio of average peak travel
time to an off-peak (free-flow) standard, in this
case 60 mph for freeways. For example, a value of
1.20 means that average peak travel times are 20
longer than off-peak travel times. - Percent of Congested Travel the congested
vehicle/person-miles of travel divided by total
VMT/PMT. A relative measure of the amount of
travel affected by congestion. - Reliability Measures
- Buffer Time Index the extra time (buffer) needed
to ensure on-time arrival for most trips. For
example, a value of 40 means that a traveler
should budget an additional 8 minute buffer for a
20-minute average peak trip time to ensure 95
on-time arrival. - Planning Time Index Statistically defined as the
95th percentile Travel Time Index, this measure
also represents the extra time most travelers
include when planning peak period trips. For
example, a value of 1.60 means that travelers
plan for an additional 60 travel time above the
off-peak travel times to ensure 95 on-time
arrival. - Archived Operations Data Source
- Uses archived freeway data from traffic
operations centers - Level of source data varies from 20-second by
lane to 15-minute by direction - For 2002 data (23 cities) 7 billion total data
records, 500 GB (uncompressed) - Developed quality control processes and data
quality measures - See the charts below for information on data
quality
- Data Completeness
- Completeness of data varies within cities and
from year to year. - For 2002, the percent of compete data ranged
from 9 to 94. - Data completeness may affect results for
particular routes and may hamper use of data for
decisions.
- Freeway System Coverage
- For 2002, the percent of freeway mileage covered
ranged from 9 to 99. - The archived data is often collected from the
most congested freeways. Because of this
non-random sample bias, the areawide mobility and
reliability measures should not be used to
compare one city to another.
2
Participating Cities and Agencies (2002 data)
Research Conducted By
Research Sponsored By
Cambridge Systematics, Inc.
Office of Operations, Federal Highway
Administration
- A Tale of Traffic in Two Cities Austin, Texas
vs. Los Angeles, California - The chart below contrasts the congestion levels
in Austin, Texas with those in Los Angeles,
California. The time-of-day chart clearly shows
the morning and evening peak periods in both
cities. The intensity of congestion (magnitude of
the travel time index) and the duration of
congestion (width of the hump) is also
apparent. The morning peak period in Los Angeles
is nearly as severe as the evening peak, but
Austins morning peak is only half as severe as
their evening peak. - Relationships between Mobility and Reliability
SELECTED FINDINGS
- Each year, the Mobility Monitoring Program
prepares a performance report for each city
represented in the Program. The city reports are
about 10 to 12 pages in length, and include a
variety of charts and tables that describe the
mobility and reliability trends for that specific
city, both at the areawide level as well as for
each directional route that is monitored.
Selected graphics from these city reports are
shown below to illustrate key findings. - Ramp Metering Operations in Minneapolis-St. Paul
- The trends chart below reflects the changes to
ramp metering in Minneapolis-St. Paul from 2000
through 2002. The freeway ramp metering system
was disabled in late 2000 as part of an
experiment mandated by the state legislature.
After the experiment, freeway ramp metering was
continued in early 2001, but in a less aggressive
manner that took ramp and surface street delay
into greater consideration. The trends chart
indicates that freeway mobility and reliability
has not returned to the levels experienced prior
to the ramp meter experiment.
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