Does
building freeways only lead to more congestion? Can investments in
transit, particularly rail transit, help relieve congestion?
Since the early 1980s, the Annual Urban
Mobility Report published by the Texas Transportation Institute
(TTI)--a part of the engineering department at Texas A&M
University--has helped to answer these questions by estimating
traffic congestion in more than 70 urbanized areas. By September 2003, TTI
had compiled 20 years of highway, driving, and congestion data for
75 urban areas in the United States.
Of
course, not everyone agrees on the interpretation of these data.
Publication of TTI's annual report is usually greeted with a flurry
of press releases, reports, and counter-reports by advocates of
transit subsidies, highways, and other interests. But TTI's data,
while not always perfect, remained an objective and independent
standard against which the claims of various groups could be
tested.
TTI's first congestion study was funded by
the U.S. Department of Transportation. Many of the annual updates
were co-sponsored by various state transportation departments.
These sponsors did not have a particular axe to grind, and no one
questioned the source of TTI's funds. In 2003, however, the
transfer of sponsorship to several new financial sponsors with
specific public policy agendas undermined that independence,
particularly after those sponsors misrepresented TTI's 2003
findings to support their own objectives.
In
contrast to past practices, TTI's 2003 report was co-sponsored by
the American Public Transportation Association (APTA), which
represents transit agencies and transit vendors, including rail
transit builders, and the American Road and Transportation Builders
Association, whose members build both highways and rail transit. An
APTA press release, timed to coincide with the release of TTI's
2003 Annual Urban Mobility Report, claimed that the congestion report
proved that "more public transportation is needed to relieve
traffic congestion." In fact, the Urban Mobility Report said no
such thing.
The
2003 report did ask the hypothetical question of what effect
eliminating public transit would have on urban congestion. While
such a question might have some academic interest, TTI's answer was
used to exaggerate the effects of transit on congestion.
Even
accepting TTI's answer, the report did not specifically ask whether
more investments in transit would relieve traffic congestion and
offered no estimates of what such investments would accomplish. In
an attempt to fill that gap, this paper will attempt to answer that
question as accurately as possible.
Problems with the 2003 Report
To
begin, however, several things about the 2003 report seem more
accommodating to the interests of the new funders than is justified
by the facts. Specifically:
- The report exaggerates the effect of
transit on congestion by assuming that all transit riders would
drive if publicly funded transit did not exist. (Many would be in
carpools, for example, since 70 percent of transit riders do not
have either a car or a drivers license.)
- Without any supporting evidence, the
report erroneously indicates that transit has increased its share
of urban travel in the past two decades, when in fact that share
has declined.
- In response to the question, "How should
we address the mobility problem?" the first answer provided is
"more travel options"--a euphemism among transit advocates for more
government transit subsidies--even though the report provides no
evidence that non-highway options can attract significant numbers
of people out of their cars or that they can even be provided
outside the dense urban core.
- While in previous years the report was
released earlier in the year, the 2003 report was not released
until September 30, the day that congressional authorization for
federal transportation funding expired, giving transit lobbyists an
opportunity to promote the findings at a crucial moment in
Congress's debate over future transportation funding.
Relying on data from the Texas
Transportation Institute, the U.S. Department of Transportation,
and the Census Bureau, this paper shows that transit is not a
solution to congestion. Transit plays an important role in America,
but attempting to use transit to relieve congestion only diminishes
its principal role, which is to provide mobility for those who do
not have a car available.
How TTI Measures Urban Congestion
The
Texas Transportation Institute's congestion calculations rely on
data gathered by state transportation agencies and published by the
Federal Highway Administration in its annual Highway Statistics
reports. Based on these data, TTI uses a computer model that it
developed to calculate various measures of congestion for each
urban area. These measures include:
- The Travel Time Index,
which estimates the time that a trip takes at rush hour relative to
the time required in uncongested conditions. An index of 1.50, for
example, means that a trip that would normally take an hour takes
90 minutes at rush hour
(90 minutes divided by 60 minutes = 1.50).
- The number of hours of delay per person
per year and the grand total for each urban area.
- The gallons of fuel per year wasted due to
congestion.
- The cost per year of fuel and time wasted
due to congestion.
- The Roadway Congestion
Index (RCI), which measures the volume of traffic compared
to highway capacity.
An urban area roadway operating at capacity has an RCI of 1.00. A
roadway averaging 25 percent more than capacity has an RCI of
1.25.

The
principal purpose of the Urban Mobility Report is to assess
peak-hour traffic congestion. It focuses on peak periods because
most traffic congestion occurs during peak periods.
Further, work trips are particularly
important because they are concentrated in peak periods. If work
trips, which represent less than one-third of peak-period travel,
were evenly spread out through the day, traffic congestion would be
considerably less. Congestion during peak periods would be little
more than what occurs during the rest of the day.
Transit has the greatest potential to
reduce traffic congestion during peak periods, when most congestion
occurs. Further, transit ridership is disproportionately
work-oriented. Surveys indicate that approximately one-half of all
transit trips are to or from work, compared to 23 percent for all
modes combined.
In
addition to calculating its traditional congestion measures, TTI's
2003 report also includes several new features:
- The report estimates the effect of
"existing" public transit systems on congestion.
- It calculates the effects of operational
solutions such as ramp metering, traffic signal coordination, and
incident management.
- It calculates the effect of high-occupancy
vehicle (HOV) lanes on congestion.
The
report also estimates the benefits of extending ramp metering,
traffic signal coordination, and incident management to all roads
in all 75 urban areas. However, it does not estimate any benefits
of expanding transit systems or HOV lanes.
Problems with TTI's Public Transit
Calculations
By
including its new calculation of transit's impact, the TTI study
got more than the usual publicity as transit subsidy advocates used
the findings to support their case for more government subsidies.
But a look behind those numbers shows that transit claims are
without foundation and are not supported by the report.
TTI's approach to transit is to ask, "What
if transit riders were in the general traffic flow?" In other words, what
would happen to congestion if public transit systems
disappeared?
While this might be an interesting
academic question, it is irrelevant, as no one has proposed to
eliminate public transit systems. Even if they did, private systems
would emerge to take their place. The answer to this question does
not provide any information that contributes to the policy debates,
which are centered more on the appropriate response to current
congestion problems, including how to structure public transit
systems and whether capital-intensive investments in rail and other
fixed-guideway transit are worthwhile.
To
calculate the effect of public transit on congestion, TTI assumed
that the sole alternative to public transit would be automobiles
and that all public transit riders would, in the absence of public
transit, drive on all trips that now use transit. This assumption
is unrealistic, particularly since two-thirds of transit riders use
transit precisely because they are unable to drive because of age,
income, or disabilities. In fact, most people ride transit because
they have no choice, not because they choose it.
Beyond this, the alternative to public
transit is not "no transit," but private transit. Before public
transit, every urban area in the TTI study had a privately operated
transit system, and if the public system were to disappear
tomorrow, the private sector would quickly move in to satisfy the
demand.
TTI
made another unrealistic assumption regarding transit riders: that
the value of their time is zero, or that they are indifferent as to
how long it takes them to get from one place to another on transit.
In calculating the effect of eliminating public transit, TTI added
all the people who now ride transit to the highway system and
recalculated the Travel Time Index and other congestion measures
for each urban area. This increased the travel time for people who
currently drive, but it would decrease the travel time for people
currently riding transit because most transit is much slower than
auto travel. People
who switch from transit to cars usually do so in part because
automobiles are faster.
Conventional bus service averages around
15 miles per hour. Light rail (trolleys or streetcars) averages
around 20 miles per hour. Heavy rail (fully grade-separated
subways, elevateds, or metros) averages around 30 miles per hour,
while commuter rail (conventional trains operating on tracks shared
with freight trains) averages around 35 miles per hour. By
comparison, TTI assumed that auto travel in uncongested conditions
would average 60 miles per hour on freeways and 35 miles per hour
on other roads. Even with congestion, for most transit travelers,
switching to automobiles would increase their speeds. This
time-savings would offset some of the time lost to other travelers
if public transit were eliminated.
Transit "riders understand that [transit]
travel might be slower" than auto travel, says TTI. Since they
choose to use transit anyway, TTI apparently reasons they must not
care about the value of their time. So TTI did not count the
time-savings to transit passengers from switching to automobiles;
it counted only the time lost to auto drivers if transit passengers
were added to the highway flow. Not only is this assumption
unrealistic, but it also presumes that the chief reason for getting
more people onto transit is to make the commute more convenient for
those who remain in their cars. This is demeaning to transit
passengers.
By
the same token, automobile drivers understand that travel during
rush hour will be slower than during other times. Yet TTI does not
apply the same logic to automobile users and, unlike its treatment
of transit passengers, acknowledges the delay to auto travelers
caused by rush-hour congestion.
To
make matters worse, TTI counted the delay to former transit
passengers who, in the absence of public transit, would drive in
congestion and have to spend more time than if they could drive in
uncongested traffic. So TTI assumes that time is valuable to
transit riders only if they are driving, not if they are riding
transit.
For
example, a hypothetical transit rider's commute ordinarily takes an
hour on light rail but only 30 minutes by automobile in uncongested
conditions or 40 minutes in congestion. In counting the cost of
eliminating transit, TTI includes the 10 minutes (40 minus 30)
spent by the former transit rider in congested traffic but ignores
the 20 minutes (60 minus 40) saved by switching to an auto. It
appears that close to a fifth of the savings claimed for transit
may really be this congestion hypothetically experienced by transit
riders. It is simply not reasonable to suggest that a person
driving a car for 40 minutes experiences more travel delay that a
person who makes the same trip in 60 minutes by transit.
In
fact, by shifting people from faster-moving cars to slower-moving
transit, overall commute time lengthens because any time-savings
that are achieved by lessening congestion are more than offset by
lengthening the commute of those who switch from cars to transit.
For example, if the transit work trip share in Portland, Oregon,
were doubled, the average work trip time for all would rise from
24.4 minutes to 26.7 minutes as some motorists shifted from faster
automobiles to slower transit.
Results Skewed by a Few Major
Urbanized Areas
Aside from these incredible assumptions, TTI's
calculations fundamentally do not make sense. TTI estimates that
transit reduces travel delay during peak periods by approximately
30 percent. This is simply not reasonable given that transit
represents only 3.8 percent of work trips nationwide and less than
1.9 percent of other trips, and that as many as 70 percent of
transit passengers do not have access to a car for their trip.
One
reason why TTI's numbers are so skewed is that its data and
subsequent calculations are heavily weighted by the
disproportionately large impact of the New York urbanized area on
any measure of national transit trends. Transit clearly plays a
critical role in moving people in and to Manhattan. Without
transit, Manhattan could not exist. So it is not surprising that
New York accounts for 36 percent of the time-savings that TTI
attributes to transit. Transit also plays a role, though less
important, in the inner cities of Chicago, San Francisco, Boston,
Washington, and Philadelphia. These five regions make up another 29
percent of the calculated time-savings. The remaining 35 percent is
divided among the other 69 urban areas, where transit is relatively
unimportant, even by TTI's dubiously generous calculations.
The
2003 report also asked how much transit would have to expand to
keep congestion at current levels. It concluded that transit
ridership would have to increase by 20 percent per year in urban
areas of 3 million people or more, by 60 percent per year in urban
areas of 1 million to 3 million people, and by 80 percent to 100
percent per year in smaller urban areas. The report does not ask
what kind of investments would be needed to produce these ridership
gains or whether the necessary number of commuters would
voluntarily give up their cars for a most likely slower and less
convenient trip to work.
Indeed, because of transit's decades-long
decline in market share, it is difficult to estimate what it would
take to reverse this trend and increase transit's share of urban
travel. Furthermore, the continuing loss in transit market share is
not unique to the United States. Data for the 1980s and early 1990s
show that transit's market share has declined in 24 of 30 urban
areas in Western Europe, Canada, Asia, and Australia by an average
change of 17 percent over 10 years.
Other Data Difficulties
In other sections of the TTI report, the data trends
presented are not consistent with data provided by the Department
of Transportation or other data presented in the report itself.
According to the introduction, for example, "From 1982 to 2001 in
the 75 urban areas studied, passenger-miles of travel increased
over 91 percent on the freeways and major streets and about 100
percent on the transit systems." This makes it appear that transit
ridership is growing faster than auto travel. However, neither of
these numbers is supported later in the report, and both are
wrong.
According to data in the report, daily
miles of vehicle travel on freeways and other major arterials in
the 75 urban areas grew by 77.7 percent from 1982 to 2001. This is
well short of the 91 percent claimed earlier. But growth in
passenger miles of travel was even less. According to the
Department of Transportation, vehicle occupancies during that time
declined from 1.76 to 1.63. This means that passenger miles of
travel grew by only 65.5 percent.
The
report exaggerates the increase in transit even more. From 1982 to
2001, total U.S. transit passenger miles grew by just 32.2
percent--one-third of the amount suggested by TTI. Since the 75 urban
areas in the TTI study account for 95 percent of the 2001 (and
historical) transit passenger miles tracked by the Federal Transit
Administration, the figure for these areas can be little different
from 32 percent.
Although TTI overestimated both auto and
transit growth, the correction reveals a crucial fact: Automobile
travel grew twice as fast as transit use. This is important because
it helps to dispel the dream that transit can someday replace a
significant portion of auto trips.
Transit's Potential to Reduce Traffic
Congestion
As
noted above, TTI's questionable estimates of the extent to which
existing transit system use reduces highway delay during peak hours
may be an interesting academic question, but it is irrelevant to
public policy since no one seriously proposes canceling all transit
service. The less fanciful question that should be asked, and the
one that this paper attempts to answer, is the extent to which
future expansion of transit might reduce travel delay.
More
precisely, this paper seeks to estimate the answers to two
questions:
1. What would be the traffic impact of a
large increase in transit's peak-hour market share?
2. How much would providing the new transit services cost?
The
Transit Market Share Increase Scenario--the principal scenario
analyzed--assumes that transit increases its share of urban travel
during peak period by 50 percent in five years. (See Chart 1.) It
also assumes that during these five years, both the Travel Time
Index and the peak-period travel delay per capita for each urban
area will continue to change at the same rate as in the past five
years (1996-2001). A peak-period work trip transit market share was
estimated, using transit's work trip market share and the overall
share of travel by transit in each urban area.
It
is, in fact, highly unlikely that transit could increase its
peak-period market share by 50 percent in five years or even over a
much longer period. Experience indicates just the opposite.
Transit's share of work trips has declined in every decade since the
U.S. Census Bureau began collecting the data in 1960. In 2000,
transit carried 4.57 percent of work trips, down from 5.12 percent
in 1990, so a 50
percent increase would mean that transit's market share would rise
to 6.85 percent of
work trips.

Overall Results
Using the methodology and estimation
process described in detail in the Appendix, it is apparent that a
50 percent increase in transit's market share--if it could even be
accomplished--would have little effect on congestion or travel
times. Using TTI's Travel Time Index for 2001 as the benchmark--the 75
urban areas registered a 1.249 index that year--projections of
transit's peak market share in five years reveal that:
- Without a 50 percent
increase in transit's peak-hour market share, the average
Travel Time Index would grow to 1.305, an increase of 0.056 over
the 2001 Travel Time Index.
- With the 50 percent
increase in transit's market share, the average Travel
Time Index would be 1.285, an increase of 0.036. The 50 percent
increase in transit's peak-period market share would thus result in
an improvement of 0.019 in the Travel Time Index.
In
2001, the average delay per capita was 17.9 hours per year in the
75 urban areas. In five years, it is projected that:
- With no increase in transit's
peak-hour market share, the average annual delay per
capita would be 23.8 hours, an increase of 5.9 hours over
2001.
- With a 50 percent increase in
transit's market share, the average annual delay per
capita would be 23.4 hours, an increase of 5.5 hours. Compared to
the estimated trend increase of 5.9 hours, a transit market share
increase of 50 percent would save only 0.4 hours (24 minutes) of
delay per capita per year compared to the present trend.
The
impact of the two scenarios on the daily lives of people can be
estimated by reviewing the impacts on average one-way work trip
travel times. The average one-way work trip in the 75 urban areas
took an estimated 23.5 minutes in 2001. It is projected that in five
years:
- With no change in transit's market
share, the average work trip travel time would rise to
24.6 minutes, an increase of 1.2 minutes (70 seconds).
- With the 50 percent increase in
transit's market share, the average work trip would rise
to 24.3 minutes, an increase of 0.8 minutes (48 seconds) from 2001.
Overall, the 50 percent increase in transit market share would
reduce one-way work trip times by just 0.4 minutes (22 seconds)
compared to the present trend.
Overall, these are modest impacts; yet to
achieve them would require an almost unprecedented and improbable
increase in transit's market share at a staggering cost.
Travel Time
Index
As insignificant as these estimated travel time improvements would
be, they would not be distributed evenly among the metropolitan
areas. In fact, most benefits would accrue to residents of large
urbanized areas.
Transit has far more impact in the largest
urban areas. It is therefore not surprising that the most
significant results occur in what TTI classifies as very large
urban areas. The 50 percent increase in transit market share would
reduce the Travel Time Index (see Chart 2):
- By 0.058 in very large urban areas
(population over 3,000,000).
- By 0.017 in large urban areas (population
of 1,000,000 to 3,000,000).
- By 0.011 in medium-sized urban areas
(population of 500,000 to 1,000,000).
- By 0.009 in small urban areas (population
under 500,000).

Of
the 75 urban areas, New York was projected to have the greatest
impact from the 50 percent increase in transit market share. This
is to be expected, since transit in the New York urbanized area has
more than double the market share of any other urban area and four
to five times the national average. In New York, the Travel Time
Index would be reduced 0.164.
However, in addition to the overall
unlikelihood that transit market share could be increased 50
percent, it could be even more difficult in New York. Much of New
York's peak-period transit ridership is in or to Manhattan, where
transit's work trip market share is approximately 75 percent--a
figure that cannot be increased 50 percent.
Delay per
Capita
As Chart 3 reveals, the most significant improvements would occur
in the largest urban areas. Except for the very large urbanized
areas, the delay reduction stemming from a 50 percent increase in
transit's market share would be inconsequential.

New
York was projected to have the greatest reduction (3.8 hours
annually) in delay hours per capita from the 50 percent increase in
transit market share. However, transit's market share is so high in
the core of New York that increasing its market share by 50 percent
could be impossible.
Journey to Work
As with the Travel Time Index and annual delay hours per
capita, the most significant work trip travel time results occur
among the largest urban areas. (See Chart 4.)

What Would it Cost, and Could it be
Done?
For
decades, transit spending has increased at a much greater rate than
inflation and even faster than ridership, as illustrated by trends
over the past 10 years. Between 1990 and 2000, annual spending on
public transit by all levels of government increased by an
inflation-adjusted 28.8 percent in the United States. Over the same
period, transit's work trip market share declined by 10.7 percent.
In relation to work trip travel--the most critical element of any
transit strategy to reduce traffic congestion--transit productivity
fell 30 percent over the past decade.
Based upon the historical trend that shows
market share declines and expenditure increases, it is difficult to
imagine any prospective policy scenario--short of some form of
coercion--that would increase transit's market share, much less a
50 percent increase.
The
few transit share gains that have been achieved have come at great
cost. According to Census data, 11 large metropolitan areas were
able to increase their transit work trip market shares from 1990 to
2000. Over that
same period, transit expenditures increased by an
inflation-adjusted $3.5 billion in those 11 areas. Assuming that
non-work travel on transit increased by the same percentage, the cost per new
peak-hour traveler was $14,357 annually, or nearly $1,200 per
month. This is more than the monthly lease for most cars, including
luxury cars such as the Lexus 430 or the Lincoln Town Car.
If
the success of these metropolitan areas could be replicated across
the nation, the annual additional cost to increase transit's
peak-period market share 50 percent would be $85 billion per year,
the equivalent of a more than $0.40 increase in the federal
gasoline tax.
Low-Cost Ways to Relieve Congestion
What Does Work?
Fortunately, there are a number of low-cost ways to
relieve congestion, some of which were identified by the Texas
Transportation Institute in its 2003 Annual Urban Mobility Report.
These include freeway ramp metering, traffic signal coordination,
and incident management.
Freeway ramp metering,
which puts traffic signals at on-ramps, seems annoying, but it can
save motorists' time by smoothing out freeway flows. According to
the mobility report, metering currently saves motorists 73 million
hours a year. However, many freeways do not yet have ramp metering.
TTI estimates that adding it to congested freeways that do not now
have it could increase time-savings by nearly 200 million more
hours.
Where ramp metering saves time on
freeways, traffic signal coordination aims to save
people time on arterial roads. Coordinated signals allow motorists
to drive at a steady rate of speed without stopping at each signal.
TTI calls this "one of the most cost-effective tools to increase
mobility" on signaled roads. Yet only about 59 percent of
signalized intersections in the areas studied in the mobility
report are coordinated. TTI estimates that coordinating the rest
could save motorists an added 17.2 million hours a year.
The
mobility report estimates that half of all congestion is due to
accidents, stalled cars, and similar incidents. Incident
management uses video cameras and other means to detect
such obstructions, combined with patrols ready to move these
obstructions quickly out of traffic. About half of all urban areas
had incident management programs in 2001, and the mobility report
says these programs saved motorists more than 100 million hours.
Implementing it in the remaining urban areas could save motorists
another 100 million hours a year.
One
technique that did not seem to work as well is
high-occupancy vehicle lanes. Initially, planners
hoped that such lanes would encourage people to carpool more, but
carpooling has declined steadily in tandem with shrinking family
sizes. Except in rare instances, such as the San Francisco-Oakland
Bay Bridge, carpool lanes have not promoted carpooling or
ridesharing.
Nevertheless, carpool lanes can be most
effective tools if they end up moving more people, due to higher
occupancies, than general-purpose lanes. A lane with two-thirds as
many cars as adjacent lanes does more work if those cars have twice
as many people as the other lanes. Regrettably, many of the carpool
lanes in America's urbanized areas do not carry enough traffic to
be worthwhile.
A
better way to use HOV lanes is to turn them into
high-occupancy/toll (HOT) lanes, as recommended by
Robert Poole and Ken Orski in a report published in February
2003.
High-occupancy vehicles would still use these lanes for free, but
low-occupancy vehicles could also use them by paying an electronic
toll. This would get more use out of the lanes and give drivers a
choice between taking the congested lanes for free or paying a
little more and getting home quicker.
HOT
lanes will help solve another problem that simply increasing
gasoline taxes or using sales or other taxes to pay for
transportation improvements would not address. It costs much more
to provide roads capable of handling peak demand than it does to
provide roads sufficient to meet average demand. Yet gas taxes are
the same whether people drive during rush hour or at midnight.
HOT
lanes can resolve this problem if they use value pricing, meaning
that they charge more during congested periods than during other
times of the day. This will help encourage people to take advantage
of flextime or otherwise drive during less congested times of the
day. Since well over half of all traffic on the road during rush
hour is not work-related, value pricing can help to relieve
congestion by encouraging non-work-related travel to shift to other
times of the day.
The
revenues from HOT lanes should be dedicated exclusively to
expanding a region's HOT-lane network. One way to accomplish this
is to create regional toll road authorities. Such authorities could
sell bonds, buy land, take over unused state or local rights of
way, and build new lanes and roads to relieve congestion.
If
these ideas can relieve congestion, why are they not used
everywhere? One answer is that the leaders of many urban areas have
decided not to solve the congestion problem. Instead, they seek to
increase congestion out of a perverse hope that increased
congestion will somehow reduce congestion by convincing some people
to use transit instead of driving.
What Does Not Work
Many urbanized areas have reduced traffic signal
coordination; changed one-way streets to two-way (effectively
eliminating signal coordination); placed barriers in roads
(euphemistically called traffic calming but more
accurately titled congestion building ); and spent
transportation funds that could be used to reduce congestion on
unrelated activities. Supporters of these steps include a
congestion coalition of planners, urban
environmentalists, transit agencies, and transit builders who hope
to gain when people agree to build rail transit out of
desperation.
Portland, Oregon, is a leader in this
movement. Local officials have put speed bumps in collector streets
and eliminated lanes from minor arterials. The regional
transportation plan for the Portland area calls for turning many
arterials into boulevards --the planners' term for
fewer lanes and wider sidewalks--with the aim of increasing walking
and bicycling at the expense of driving. The region's
transportation planning models predict that these actions will
increase walking and cycling from 5 percent of the region's trips
all the way to 6 percent.
Portland is also obsessed with rail
transit at the expense of auto driving. A major bottleneck in the
region is located on Interstate 5, which runs north and south from
Washington, through Oregon and into California. A crucial segment
of the highway runs through the city of Portland but has only two
lanes each way and is heavily congested. For 50 miles to the north
and south of this segment, Interstate 5 is at least a six-lane
highway, much of it in rural areas.
Highway planners estimate that adding a
new lane to this section would cost around $10 million, but the
region has instead spent well over $10 million on planning just
this section of road. In April 1998, Chairman Henry Hewitt of the
Oregon Transportation Commission testified before an interim
legislative committee that Portland planners had asked the state
not to relieve this bottleneck until a light-rail line is built
between Vancouver and Portland. Vancouver has refused to pay the
hundreds of millions of dollars required for its share of this
light-rail line, and Portland planners are literally holding the
cure for this bottleneck hostage until Vancouver funds light
rail.
In
other words, relieving congestion is less of a technical problem
than it is a political problem. Unless the people who are most
affected by congestion work together to challenge the congestion
coalition, urban congestion will continue to worsen no matter how
much money people vote to spend on transportation improvements,
because that money will likely be spent on things that will not
reduce congestion.
In
the long run, it is likely that congestion will be solved, or at
least greatly reduced, through the use of intelligent
highways on major busy roads. Such highways would include
sensors that detect and control cars, with computers that
automatically steer, accelerate, and slow cars in tandem. This
would allow much higher traffic flows per lane than are currently
seen, perhaps quadrupling the capacities of a given highway
space.
Many
automobiles today have cruise control, and some newer models sense
when a car ahead slows down and automatically slow in response. The
Toyota 2004 Prius will self-steer. All that will be needed is to
connect self-accelerating, self-braking, self-steering cars to an
intelligent highway network.
Hybrid-electric cars such as the Prius
also virtually eliminate air emissions and greatly reduce energy
consumption. Thus, most of the reasons cited for heavy investments
in rail transit--saving energy, reducing air pollution, and solving
congestion--are being taken care of at a much lower cost without
attempting to force people who can drive to use less efficient mass
transit.
Conclusion
The
evidence cited in this study shows that an increase of at least 200
percent in transit spending would be needed to increase transit's
market share of peak-hour commuters by 50 percent. Yet this would
save urban commuters no more than an average of 22 seconds each way
to work (44 seconds per day). Moreover, in most urban areas, total
driving and per capita driving continue to grow so fast that within
a few months, at most, all of that savings would be consumed by new
traffic.
In
recent decades, much federal, state, and regional transportation
policy has been based on the assumption that transit can help
relieve highway congestion, which has led many urban areas to write
plans that spend well over half of their transportation budgets on
transit systems that carry well under 5 percent of passenger
travel, not to mention virtually no freight.
For
example, Atlanta's metropolitan planning organization adopted a
25-year plan committing 56 percent of future funding to transit,
which carries approximately 1.5 percent of travel demand. This
funding/demand discrepancy is repeated in all other metropolitan
regions that propose to build rail transit. One report indicates
that the nation's 19 largest urban areas plan to spend half of
their transportation funds on transit, while the average transit
market share in those areas is less than 3 percent.
There is no indication that this
additional money for transit will produce a material shift from
cars to transit. Virtually all of the nation's metropolitan
planning organizations project that almost all new travel growth
will be by automobile rather than transit.
Some
transportation planners actually applaud rail transit's inability
to reduce congestion. Their goal is to increase congestion. They
believe that the residents of their urbanized areas are better
served by wasting time in cars that burn fuel and pollute the air
in stop-and-go traffic out of a forlorn hope that a few of those
drivers will give up in frustration and ride transit. Yet their own
transportation planning models show that very few drivers will stop
driving because of congestion, principally because
automobile-competitive transit service is provided to few
destinations other than downtown.
Urban leaders who seriously want to reduce
congestion should demand that transportation planners calculate the
dollar cost per hour of delay that is reduced by proposed highway,
transit, and other transportation improvements. This consistent
test can easily be calculated for almost any transportation capital
improvement using urban transport models. There may be other
measures by which proposed projects should be judged, but as far as
congestion goes, this is the primary if not the only valid
measure.
Applying such a measure to highway,
transit, and other projects will reveal that many projects are not
economically justified, at least on congestion-reduction grounds.
Yet many projects can easily save hours of delay at a fairly low
cost. These include freeway ramp metering, incident management, and
traffic signal coordination. Many low-cost highway expansions and
bus improvements will also produce high returns. Rail transit will
rarely make the grade.
High-occupancy/toll lanes are a special
case. They should require no subsidies, so the only question is
whether a particular road can pay for itself. The best way to
answer this question is to create an independent toll roads
authority that has the power to build roads, charge for them, and
fund itself exclusively out of its receipts.
Public transit is important for people who
cannot drive, but it is not a solution to congestion. Efforts to
build expensive rail transit lines in the hope of reducing
congestion are doomed to failure and often detract from transit
agencies' ability to carry out their primary mission of providing
mobility for people who have no access to cars.
Wendell Cox, Principal of the Wendell Cox
Consultancy in metropolitan St. Louis, is a Visiting Fellow at The
Heritage Foundation and a visiting professor at the Conservatoire
National des Arts et Metiers in Paris. Randal O'Toole is Senior
Economist at the Thoreau Institute.
Appendix: Notes on Methodology
The
following method was used to project the impacts of a 50 percent
increase in transit peak-period market share in urban areas over a
five-year period, with peak periods defined as 6:00 a.m. to 9:00
a.m. and 4:00 p.m. to 7:00 p.m.
"Trend Scenario" Assumptions
- Public transit's peak-period market share
would be the same in five years as it was in 2001.
- The Travel Time Index would increase over
the next five years at the same rate as between 1996 and 2001 in
each urbanized area.
- Annual delay hours per capita would
increase over the next five years at the same rate as between 1996
and 2001 in each urbanized area.
- An average journey-to-work time estimate
(in minutes) was developed by adjusting the 2000 Census figure for
each urbanized area by the change in the Travel Time Index from
2000 to 2001 and by the projected change for five years.
"Transit Market Share Increase
Scenario" Assumptions
- Transit market share would increase by 50
percent over trend.
- Transit's peak-period market share was
estimated, assuming that transit and auto users would have the same
propensity to carpool. According to the National Household Travel
Survey, 29 percent of peak-period travel is to or from work. Each urbanized area's
journey-to-work market share from the 2000 U.S. Census was used for
this portion of transit travel. The other 71 percent of peak-hour
travel was assumed to have a transit market share equal to the
overall transit market share for each urbanized area (adjusted to
1.25 average automobile occupancy). These weighted figures were
combined to establish an estimated peak-period market share for
transit. The estimated peak-period transit market share was
increased by 50 percent.
- The Travel Time Index and the average
annual delay per capita from the "Trend" scenario were reduced by a
percentage equal to the transit peak-period market share.
- Average journey-to-work time was estimated
by adjusting the "Trend" scenario figure by the difference in the
Travel Time Index between the "Trend" scenario and the
"Transit