Speeds on Rural Interstate Highways Relative to Posting the 40
mph Minimum Speed Limit
VICTOR MUCHURUZA1*
RENATUS
N. MUSSA2
ABSTRACT
The relevance of posting the 40 mile per hour (mph) minimum speed
limit on the Interstate Highway System has been increasingly called
into question since the National Highway System Designation Act of
1995 repealed the federally sanctioned maximum speed limit. In this
study, data were collected on major interstate highways in Florida
to evaluate speed distribution relative to the 40 mph posted minimum
speed limit. The data revealed that the 15th percentile speed at all
sites was 60 mph or above on both four-lane and six-lane highway
sections. The analysis showed that the average speed at all sites
was approximately 5 standard deviations above the 40 mph minimum.
The coefficient of variation ranged from 7% to 11%, while the
trimmed variance analysis showed that vehicles traveling below 55
mph contributed insignificantly to the variation in traffic speeds.
A comparison of data collected before the speed limit rose from 65
mph to 70 mph showed that the average speed increased by 5 mph,
while the variances did not change significantly. The coefficients
of variation, however, increased significantly. The results reported
here suggest that speed variability at the lower end of the
distribution is not a significant factor in traffic operating
characteristics on Florida rural interstate highways.
KEYWORDS: Speed limit, speed variation, highways.
BACKGROUND
The decades-old practice of posting minimum speed limits on rural
interstates and other limited access highways is predicated on the
desire to reduce vehicle conflicts caused by speed variability in a
traffic stream. The relevance of the 40 mile per hour (mph) posted
minimum speed limit found on the Interstate Highway System is
increasingly being called into question in light of the National
Highway System Designation Act of 1995, which repealed the federally
sanctioned maximum speed limit of 65 mph on rural highways. Most
states, including Florida, then raised the maximum speed limits, and
by the end of 1997, most parts of Interstates 4, 10, 75, and 95 in
Florida posted 70 mph, which is the maximum speed allowed by the
Florida state statutes. While the maximum speed limit fluctuated
over time, the minimum did not and, in Florida, the 40 mph limit was
in effect and posted across many sections of rural interstate
highways, even when the U.S. Congress required states to lower the
speed limit to 55 mph in 1974.
With such a wide (30 mph) gap between maximum and minimum speed
limits, it is logical to question the relevance of the 40 mph posted
minimum. If the review of the current speed distribution shows that
the 15th percentile speed is much higher than the 40 mph posted
minimum, perhaps the minimum speed needs to be increased or
rescinded. Also, it is important to know if the continued posting of
the 40 mph minimum speed limit results in the increase in speed
variability on rural interstate highways. A review of traffic
operations on sections of Florida highways may provide answers to
these questions.
HISTORICAL PERSPECTIVE
The promise behind the posting of minimum speed limits on
interstate highways was to reduce interactions between fast and slow
moving vehicles. Many states based their minimum speed limits on the
Uniform Vehicle Code (UVC) published by the National Committee of
Uniform Traffic Laws and Ordinances (National Committee 1954). The
UVC stipulated that minimum speed limits be established on highways
whenever traffic and engineering investigations concluded that
slow-moving vehicles consistently impeded the normal flow of traffic
on the highways.
Studies showed that, by 1962, many states had adopted slow speed
laws in their statutes in compliance with the UVC (National
Committee 1964). Florida was among the states adopting slow-speed
provision, making 40 mph the minimum on the four-lane interstate
system, the Turnpike, and defense highways. Basically, the Florida
statutes made it illegal to drive at a slow speed that impedes the
normal and reasonable flow of traffic on rural highways.
The literature reveals that, in the early 1960s, 41 states and
the District of Columbia instituted slow-speed laws in verbatim or
significantly conforming with the UVC, while the remaining 9 states
did not add minimum speed regulations in their codes. Like Florida,
Georgia and South Dakota statutes explicitly stated that the minimum
speed limit was 40 mph, while Michigan and North Carolina maintained
a 45 mph minimum speed rule on their interstate highways.
A 2003 survey of minimum speed practices in different states
conducted for the Florida Department of Transportation showed that,
following the 1995 National Highway System Designation Act, 43
states raised the maximum speed limit on their Interstate Highway
System roads (Mussa 2003). However, the posted minimum speed on
these systems did not change. In fact, the survey showed that 14
states still use 40 mph minimum speed limit signs, 10 states use 45
mph, and 1 state uses 55 mph. Furthermore, the survey showed that 25
states do not post minimum speed limit signs. Some respondents in
states that do not post minimum speed limit signs indicated that
slow driving is not a big problem on their highways and if a need
arose for enforcement, various rules in their state statutes, such
as "impeding traffic flow," can be used to warn or cite slow
drivers.
UNDESIRABLE EFFECTS OF SPEED VARIABILITY
Posting a minimum speed limit was and still is motivated by the
desire to reduce speed variability in a traffic stream and its
attendant consequences in efficiency and safety of traffic
operations. Numerous studies have documented the negative effects of
speed variability.
In determining the extent to which the 55 mph federally
sanctioned maximum speed limit affected safety, a Transportation
Research Board (TRB) study found that the probability of crashes
occurring increases as the speed variance rises. The study showed
that speed variation causes significant lane changing and passing
maneuvers, which are known to be potential sources of conflicts and
crashes (TRB 1984). The significance of speed variance was observed
by developing a fatality model that included highway safety
characteristics such as traffic density, percentage of vehicles
exceeding 65 mph, percentage of teenagers, and enforcement activity,
as well as speed variance and average speeds. The TRB model revealed
that speed variance had a statistically significant effect on
fatality rates-states with wider variances in vehicle speed on the
highway tended to have higher fatality rates. The study further
found that the mean speed only affected the severity of crashes.
Holding the effect of speed variance constant in the model presented
no statistically significant relationship between the fatality rate
and any other speed variables. The study concluded that controlling
speed variance could be an effective tool in improving highway
safety.
Another study of 36 crashes that occurred on Indiana highway 37
indicated that the crash involvement rates per million vehicle-miles
of travel were higher for vehicles whose speeds were below and above
the mean speed (West and Dunn 1971). After removing data on all
crashes related to turning maneuvers, the authors found that the
crash risk associated with vehicles traveling faster or slower was
more than six times the involvement rates at the mean speed. The
West and Dunn findings were supported by Hauer (1971) who developed
a mathematical model to correlate accident involvement rates and
vehicle travel speeds. Hauer found that the imposition of a minimum
speed limit on highways was two to three times as effective as an
equivalent maximum speed limit in reducing the frequency of
overtaking and thereby crash involvement rates. Hauer suggested that
the relationship between vehicle speed deviations and crashes might
be due to a higher incidence of passing maneuvers from which the
vehicle passes or is passed by another vehicle-a situation caused by
the presence of slower vehicles impeding fast vehicles in the
traffic stream.
Lave (1985) found that the major highway safety benefits obtained
after the enactment of the 1974 National Maximum Speed Limit
Act-which reduced the maximum speed limit on interstate highways to
55 mph-were due to the reduction of speed variance rather than
average speed. The author argued that a reduction in speed variance
was realized because speed differences between slow and fast moving
vehicles were reduced enough to cause a uniform flow of traffic on
interstate highways. Thus, with small speed variances there are
fewer passing and overtaking maneuvers, eventually leading to the
reduction in the potential for conflicts and crashes. Lave concluded
that slow drivers are just as dangerous as fast drivers and thus
posting minimum speed limits is desirable so as to reduce speed
variance in a traffic stream.
RESEARCH AGENDA FOR A MINIMUM SPEED LIMIT
The posting of higher maximum speed limits on rural interstate
highways necessitates an evaluation of the relevance of posted
minimum speed limit signs that existed prior to raising the maximum
speed. Some studies (e.g., West and Dunn 1971; Hauer 1971; and Lave
1985) documented that posting the minimum speed limit has the
beneficial effect of smoothening traffic flow by removing
perturbations caused by speed differences.
While evidence obtained from past research shows that vehicle
speed variability contributes to crashes, it is a big and
unsubstantiated leap to say that posting 40 mph minimum speed limit
signs on a highway with a 70 mph maximum speed limit, as is the case
on the Florida rural Interstate Highway System, contributes to large
differences in vehicle speeds. The effect of the 40(min)/70(max)
seeming mismatch can be evaluated through a carefully designed field
study in which driver characteristics and the resulting operating
speeds are observed over a long period of time on highway sections
with similar geometrics and traffic characteristics but with some
having the 40 mph minimum posted and others not having the minimum
posted. Furthermore, knowing whether the minimum speed limit should
be increased above 40 mph and by how much, given that the maximum
speed limit has been raised from 65 mph to 70 mph, would also be
useful. To obtain this information, a study would require
experimental highway sections with the desired minimum speed limit
signs posted.
This study aimed at evaluating operating speed characteristics on
the Florida Interstate Highway System where 40 mph minimum speed
limit signs are posted. It would have been desirable to conduct a
study designed as described above but control sites with no minimum
speed limit signs were not available. An experimental site with 40
mph minimum speed signs removed or covered can be created for
conducting a longitudinal study where both operational and traffic
crash data are collected and later compared with the current
conditions. However, creating such sites has legal implications that
are difficult to resolve at this time. Thus, this study was limited
to the following: determining how speed characteristics deviate from
the 40 mph limit, and determining the speed variability that
resulted before and after the limit was raised.
Note that the relevance of the 40 mph minimum speed limit is
analyzed in this paper from the operational standpoint only.
Certainly, law enforcement personnel would prefer to have these
signs erected to provide support for warning or citing slow moving
drivers; the "impeding traffic flow" criterion may be less useful
for enforcement purposes.
STUDY SITES
There are four interstate highways in Florida, Interstates 4 and
10, oriented in the east-west direction, and Interstates 75 and 95,
which go in a north-south direction. In addition, the Florida
Turnpike is a tollway from central to south Florida oriented in the
north-south direction.
Site selection targeted rural sections of these roads where
minimum speed limit signs are posted. The established site selection
criteria required choosing sites where the geometric characteristics
produced the highest free-flow speed possible, that is, sites devoid
of horizontal and vertical curves, sustained grades, or other
geometric constraints. Another criterion used was to select sections
with telemetered traffic monitoring stations that collect traffic
flow data on volume, occupancy, and individual vehicle speeds on a
24-hour basis throughout the year. The Florida Department of
Transportation operates and maintains these sites. We could not
select a site on Interstate 4 because the Tampa-Orlando-Daytona
Beach corridor, through which this highway runs, is heavily
congested throughout the week with few periods in which free-flow
speeds are attainable. Table
1 shows the study sites selected based on the established
criteria discussed above.
DATA COLLECTION
As part of the data collection strategy, the project team drove
through the entire Interstate Highway System to observe geometrics
and traffic operating conditions. In addition, the project team
evaluated over 320 telemetered traffic monitoring sites to determine
their locational suitability in relation to the research objective
of evaluating speed characteristics. The field review resulted in
choosing sites described in table 1. The elements of the
data-collection plan including the data quality checks are explained
below.
Individual Vehicle Records
Telemetered traffic monitoring stations use loop detectors that
provide individual vehicle records composed of the exact time of
passage of a vehicle, its speed, the lane of passage, the number of
axles and axle spacing, vehicle length, and, in some stations, an
individual vehicle's axle weight. A cursory review of the speed
characteristics at most sites indicated that there were minor
differences between weekend and weekday traffic speed distribution.
Thus, data from all sites were collected on weekdays in good weather
conditions and dry pavement. The integrity of the data was verified
by checking for errors.
Data Error Checks
Logic checks on the recorded data elements were applied to the
raw data files downloaded from the count stations. Typical data
errors included improper recording of speeds and loop failures on
some lanes. We set an initial criterion that if more than 5% of the
data were bad, the dataset for the whole day was discarded and
another day's data were downloaded. The accuracy of individual
vehicle speeds was checked by relating vehicle length and its
corresponding recorded speed. When the length of the vehicle was
missing, it was assumed that the vehicle did not cross both loops in
the speed trap thus suggesting that the recorded individual vehicle
speed was erroneous. The number of records with missing speed or
length was used to check the percentage of usable counts with
respect to raw data elements and finally to decide whether the data
for that particular day was within acceptable limits needed for
further analysis.
Next, outliers were removed prior to performing the statistical
analyses. All outliers, defined as data points that were
inconsistent with the general trend of the data elements, were
eliminated by a computer program developed for this purpose. The
computer program discarded data points showing zero speed or speed
greater than 120 mph (the maximum speed value the equipment can
record). The time slots in which data were discarded were coded as
missing data. In all datasets used for further analysis, the
percentages of data coded as missing were less than one. All
individual vehicle records were then summarized per hour and per
lane and the required volume, speed, and headway statistics were
calculated. Analyses proceeded only after assuring the data quality
through these error checks.
VOLUME ANALYSIS
Under low to moderate traffic congestion, as demand on travel
lanes increases so does the need of fast moving vehicles to pass
slow moving vehicles. The combination of passive and active passing
maneuvers creates the potential for conflicts in the traffic stream.
Higher operating speeds are generally attainable at level of service
(LOS) A1
and continually decrease as the speed-volume relationship moves
toward congested flow conditions. An hour-by-hour volume analysis of
the 24-hour dataset was conducted at all eight sites to determine
the volume distribution across the travel lanes, the percentage of
trucks on each lane, and the minimum and maximum volumes and their
hour of occurrence. The traffic volumes were expressed on a per-lane
basis, because, in general, volume varies by lane. The average
annual daily traffic, which is the gross indicator of traffic
activity, usage, and need, was estimated by multiplying the 24-hour
recorded volume with the adjustment factors developed by the Florida
Department of Transportation Statistics Office. Table
2 shows the results of the volume analysis.
Table 2 presents the results categorized by the number of lanes
on the highway (i.e., four or six lanes) and by direction of travel.
Examination of the hourly variation at each site showed that the
demand volumes were at their lowest from midnight to dawn hours,
while the peak-hour demand occurred in the afternoon, typically from
3 p.m. to 5 p.m. with a few exceptions. The lane distribution
analysis for the six-lane highway sections showed that flow rates in
the middle lane were typically higher than on shoulder and median
lanes. On four-lane sections, the flow rates on the shoulder lanes
were higher than on the median lanes.
We also analyzed the distribution of trucks in each lane.
Vehicles traveling at the low end of the speed distribution tended
to be trucks, recreational vehicles, and vehicles towing trailers.
Table 2 shows that truck percentages are higher on the shoulder
lanes in both four-lane and six-lane sections. Note that on Sites
320 and 9904 on Interstate 75 in north Florida trucks are not
allowed to travel on the median lane of three-lane (in
one-direction) sections (i.e., they can only use the two outermost
lanes).
A comparison of the peak-hour and 24-hour truck percentages
suggests that more trucks travel during the offpeak hours. The need
to change lanes and to pass some slow moving vehicles-typically
trucks and RVs-is high during offpeak hours. The LOS in most of the
sections was B or better during these time, thus operating speeds
tend to be high due to fewer traffic interactions. With trucks and
RVs typically among the slower moving vehicles, changing lanes and
passing, resulting from the speed variances, might be a concern.
SPEED ANALYSIS
The analysis of speed is presented in two parts. The first part
of the analysis details the central tendency of the speed data while
the second part looks at the speed variability in the traffic
stream. The analysis of both measures of center and dispersion takes
into account the demand volume, lane of travel, and the type of
vehicles-passenger cars or trucks-in the traffic stream.
Central Tendency Analysis
Figure
1 shows the 24-hour mean speed of all vehicles categorized by
facility type (i.e., four-lane or six-lane highway). Examination of
the graphs in figure 1 reveals that average speeds of vehicles vary
from shoulder to median lanes with median lanes experiencing higher
average speeds. At four-lane sites, the average speeds ranged from
66 mph to 74 mph in shoulder lanes and 67 mph to 85 mph in median
lanes. At six-lane sites, the average speeds of the vehicles on the
shoulder, middle, and median lanes ranged from 67 mph to 70 mph, 72
mph to 75 mph, and 75 mph to 81 mph, respectively.
Pairwise comparisons of the average speeds using a t-test
showed that, on four-lane sections, average speeds differed
significantly between shoulder and median lanes (p = 0.0002).
Further analysis showed that the average speeds were significantly
different between shoulder-middle lanes and middle-median lanes on
six-lane sections (p ≤ 0.0001 and p ≤ 0.0001). These
results confirm that slow-moving vehicles generally use the shoulder
lanes while fast moving vehicles use the median lanes. At the
prevailing LOS, it seems that the influence of traffic intensity was
not a significant factor, because at six-lane sites the middle lanes
carried higher volumes than shoulder lanes yet they had higher
average speeds. To further understand the profile of speeds at these
highway sections, table
3 presents the overall 24-hour mean speeds by lane and vehicle
type. Table 3 also shows the harmonic mean speeds weighted by lane
volumes and by vehicle type. The harmonic mean speeds were
calculated as follows:
 (1)
where
 = the harmonic mean speed weighted by the 24-hour
lane volume in lane i,
 = the harmonic mean speed weighted by 24-hour
vehicle type j volume,
 = the 24-hour mean speed of all vehicles in lane i,
 = the total 24-hour volume in lane i,
 = the 24-hour mean speed of all vehicles of type
j, and
 = the total 24-hour volume of vehicle type j.
Table 3 also includes the straightforward average speeds of all
vehicles and the trimmed mean speeds. The trimmed mean speeds were
calculated by discarding the lowest 15% and the highest 15% of
vehicle speeds. We statistically analyzed the significance of the
difference between the speed types displayed in this table. Pairwise
comparisons of and showed no and slightly significant differences (p
= 0.7 and p = 0.08) between lane-based and vehicle
type-based mean speeds on both six-lane and four-lane highway
sections, respectively. Statistical comparisons between trimmed mean
speed and average speeds in each lane indicated lack of a
discernible difference in both six- and four-lane sections (p
= 0.57 and p = 0.40). The non-existence of the difference
between trimmed speed and mean speed shows that the presence of fast
and slow moving vehicles in the speed distribution has no
significant effect on the average speeds on these facilities. The
average speed of the bottom 15th percentile of the vehicles was 62
mph on both facility types, while in the upper 15th percentile, the
average speed of vehicles was 81 mph and 83 mph on six-lane and
four-lane sections, respectively.
Speed Dispersion Analysis
The dispersion of speeds was analyzed by lane and vehicle type
using the standard deviation, coefficient of variation, and 10-mph
pace, which is the 10 mph speed range with the highest number of
observations of vehicles in the speed distribution. In addition, as
is the case in most traffic engineering design and operational
analyses, the 85th and 15th percentile speeds were also calculated.
The results follow.
Facility Type Speed Distribution
We computed the standard deviations of vehicle speeds and the
corresponding coefficient of variation. The results showed that
their values varied depending on facility type. On six-lane
sections, the standard deviation of speeds ranged between 4 mph and
6 mph, while on four-lane sections the standard deviations were as
high as 10 mph. Specifically, Sites 351 and 9919 showed high values
of standard deviations-9 mph and 10 mph on the median lanes,
respectively. The field review revealed that these two sites are on
highway stretches that are longitudinally straight for at least 10
miles.
The coefficient of variation, which measures relative dispersions
of vehicle speeds from the average speed, was also calculated by
lane for each site. This statistic was necessary to compare speed
variations by examining the magnitudes of deviation relative to the
magnitude of the mean given that there were different mean speeds
grouped by lane. The analysis of the coefficients of variation in
each lane showed that they ranged from 5% to 14%. When coefficients
of variation for adjacent lanes on each site were compared, the
results showed that the differences were less than 2%. These results
suggest that the scatters of the vehicle speeds from the average
speed are small. Therefore, the traffic speeds are very closely
clustered about the mean speeds in all sections analyzed.
Speed Distribution by Vehicle Type
On average, the results of the speed distribution analysis by
vehicle type showed that passenger car speeds were higher than truck
speeds by at least 1 mph on both six-lane and four-lane sections.
The results further showed that the coefficients of variation did
not differ significantly between passenger cars and truck speeds for
six-lane highway sections but were significant on four-lane sections
(p = 0.027). Figure
2 displays the results of the speed distribution analysis at the
lower end of distribution.
With respect to the vehicles traveling at the lower end of speed
distribution (i.e., less than 60 mph), we found that more trucks on
four-lane sections traveled below 60 mph than passenger vehicles at
Sites 9901, 9919, and 9928, while more passenger cars traveled below
60 mph at Sites 351 and 9932. The results were also mixed on
six-lane highway sections. At Sites 320 and 9904, which are on the
same stretch and approximately 70 miles apart, different patterns of
vehicles traveling below 60 mph were observed. While at Site 9904
more passenger cars traveled at speeds below 60 mph, at Site 320
more trucks traveled below 60 mph. At Site 9905, more passenger cars
than trucks had speeds below 60 mph in all lanes.
The results further showed that on both four-lane and six-lane
sections the percentage of vehicles at each site traveling below 40
mph (the posted minimum speed limit) was approximately zero. In
fact, the results showed that at all sites only 1% of the vehicles
traveled below 55 mph. Both passenger cars and trucks averaged
speeds below 60 mph but above 55 mph on six-lane sections. On
four-lane sections, the speed of vehicles traveling below 60 mph
averaged above 54 mph.
Percentile and Pace Characteristics
Table
4 displays the 15th and 85th percentile speeds in each lane, 10
mph pace speeds, and the percentages of vehicles within the pace.
Analysis of percentile speeds showed that, in four-lane and six-lane
sections, the 85th percentile speeds ranged from 71 mph to 94 mph
and 73 mph to 86 mph, respectively, while the 15th percentile speeds
ranged from 60 mph to 77 mph and 62 mph to 76 mph, respectively,
depending on the lane of travel (i.e., median lanes had higher
percentile speeds than shoulder lanes). Of significant interest was
the 15th to 85th percentile range, because it represents the
proportion of vehicles traveling close to the mean speed. At the
six-lane sites, the percentile speeds ranged from 7 mph to 10 mph, 8
mph to 10 mph, and 10 mph to 12 mph on the median, middle, and
shoulder lanes, respectively. The ranges for four-lane sites were 7
mph to 11 mph and 11 mph to 12 mph on the median and shoulder lanes,
respectively.
Note that the results from Sites 351 and 9919 do not particularly
follow the trend of other sites because of the somewhat large
differences between percentile speeds at the two sites-14 mph and 19
mph, respectively. These differences could result from the
straightness of the segments as well as a low volume of traffic that
induces high-speed travel by some drivers. Furthermore, these two
sites also showed the highest values of standard deviations. Table 4
further details that the paces ranged from the mid-60s to the
mid-80s on both facility types with shoulder lanes experiencing
lower pace speeds. The results in table 4 show that there is no
direct relationship between the number of lanes on a highway and
pace speeds.
Trimmed Variance Analysis
A trimmed variance analysis determined the contribution of slow-
and fast-moving vehicles on overall speed variation. Using five
different scenarios, vehicles traveling slower than 40 mph, 45 mph,
50 mph, 55 mph, and 60 mph were removed from the dataset when
calculating the variance. The resulting speed variances from these
trimming processes were then compared. At all sites, the 15th
percentile speed was about 65 mph, 25 mph above the posted minimum
speed of 40 mph.
The results showed no discernable contribution to speed variance
for vehicles with a speed of less than 55 mph, primarily because
very few vehicles at each site traveled at speeds less than 55 mph.
In fact, at each site vehicles with speeds under 55 mph made up 1%
of those recorded, while the percentage of vehicles with speeds of
less than 40 mph was negligible (i.e., 0.15%). Although the
contribution to the standard deviation of vehicles with speeds less
than 55 mph is very minor, the safety implications of the presence
of vehicles with very low speeds cannot be ignored. Even though only
a few vehicles cause speed differential conflicts, these vehicles
could be a contributory factor in crashes.
PLATOON ANALYSIS
Highway travel is generally composed of free-flowing and
platooned vehicles. In free-flowing traffic, drivers can choose
their speeds as they desire as long as conditions are such that
slow-moving vehicles do not impede their ability to change lanes at
will. Platooned vehicles travel close to each other mostly because
of lack of passing opportunities, thus causing other vehicles to be
trapped behind the lead vehicle. No definition exists in the
literature of a headway value below which vehicles are considered to
be moving in a platoon. Thus, in this study, four definitions were
considered-less or equal to 1, 2, 3, and 4 seconds.
The analysis showed that six-lane highway sections carried larger
proportions of platooned vehicles than four-lane sections. Further,
the middle lanes of six-lane sections carried more platoons than the
shoulder and median lanes. To study the effect of platooned vehicles
on the distribution of speed, the mean speeds of platooned vehicles
were compared with the mean speeds of nonplatooned (or free-flowing)
vehicles. The statistical analysis here uses a t-test in
which platooned and nonplatooned vehicles were paired by site and by
lane of travel. The results showed that the difference between the
speeds of platooned and nonplatooned vehicles were insignificant for
both four- and six-lane highway sections regardless of whether the
cut-off point was 1, 2, 3, or 4 seconds of time headway. These
results indicate that platooned vehicles are not slow moving and
thus do not create a need for free-flowing vehicles catching up
behind them to pass. However, it should again be noted that the
highway sections analyzed were relatively uncongested, operating at
levels of service B or better for a majority of the hours in a
year.
BEFORE AND AFTER COMPARISON
To understand the change in speed characteristics following the
increase in the speed limit, table
5 presents a comparison of before-and-after data. In 1996, the
speed limit was 65 mph at all the sites indicated in the table.
Data-collection sites for both 1996 and 2002 were physically very
close, and the field review of the sites indicated that for all
practical purposes the geometric characteristics prevailing at these
sites would produce similar driver behavior.
The results in table 5 show that the average speeds across all
sites increased by 5 mph to 72 mph. The 15th percentile speed also
showed a significant increase of 3 mph when averaged across all
sites (p ≤ 0.0001). A statistical F-test comparison of
the variances indicated no significant difference between the 1996
and 2002 data (p = 0.50). However, significant differences
were found in the variances on four-lane sections (p =
0.0003). Further analysis indicated that in 1996, the average speed
on six-lane sections was 4.75 standard deviations above the 40 mph
minimum posted speed limit. In 2002, it was 5 standard deviations
above the 40 mph minimum. In four-lane sections, the results show
that the average speeds were 6 and 5 standard deviations above 40
mph in 1996 and 2002, respectively. Examination of the coefficients
of variation between the two datasets indicated that 2002 data show
significant large variations compared with 1996. However, the
coefficients of variation are still below 10%, indicating a
reasonable equity in travel speeds.
DISCUSSION OF RESULTS
This paper presents a review of traffic operating characteristics
on rural interstate highways in Florida. Using various analytical
techniques, we determined speed characteristics in relation to the
posted minimum speed limit of 40 mph. Our intent was to examine the
relevance of the 40 mph minimum speed limit in light of the increase
in the maximum speed from 65 mph to 70 mph.
It is clear from the analysis that raising the speed limit
increased average speeds on rural interstate highways. The
comparison of 1996 data with 2002 data showed that average speeds
rose by 5 mph, which is the same amount of the speed limit increase.
The comparison further showed a slight increase in the coefficient
of variation after the maximum speed went up; however, the increase
is statistically insignificant and under 10%, a threshold that can
be considered to indicate uniform operations. In addition, the 15th
percentile speed showed an increase of 3 mph when averaged across
all sites. In relation to the 40 mph posted minimum speed, the 2002
average speed on all sections was 5 standard deviations above this
minimum speed, compared with 5.4 standard deviations for the 1996
data.
In light of the above data and analyses, from a traffic
operations standpoint, several questions arise: Is the practice of
posting the 40 mph minimum speed irrelevant or is it successful in
ensuring that vehicles do not travel below 40 mph? Should the 40 mph
posted minimum speed limit be scrapped or should it be raised to a
higher value? What should that value be? These are important
questions that could not be adequately answered through the research
paradigm reported here. However, the data reveal a few pointers.
First, the 40 mph posted minimum speed limit probably does not
have a significant influence on driver behavior given that the
number of vehicles traveling below 55 mph at all sites was
negligible (i.e., 1%). If these signs influenced drivers, we would
expect a higher percentage of vehicles to travel at speeds in the 40
mph to 50 mph range, as is the case on the higher side of the speed
distribution where a large percentage of drivers maintain speeds
between 70 mph and 80 mph.
It has been suggested in the past (e.g., McShane et al. 1998)
that the 15th percentile speed may be used as a measure of the
minimum reasonable speed for the traffic stream. (This suggestion
mirrors the attempt to use the 85th percentile speed as a measure
for setting the maximum speed limit). The data reported here
indicate that, in all sections studied, the 15th percentile speeds
on the aggregate ranged from 60 mph to 70 mph, which is 20 mph to 30
mph above the posted minimum speed limit value. Does this mean that
the minimum speed limit should be set at 60 mph? There are number of
concerns that would need to be addressed before a change like this
could be made. First, Florida statutes (Florida Statutes 2002) state
that "no school bus shall exceed the posted speed limit or 55 mph."
Second, as a tourist state, some Florida visitors drive recreational
vehicles (sometimes towing a trailer) or motor homes, and field
review indicated that these are the vehicles that tend to make up
the lowest 15% of the speed distribution at all sites. Third, a
safety analysis would be needed to fully justify any change in the
minimum highway speed.
Instead of increasing the minimum speed, should it be eliminated?
After all, the results of a survey conducted as part of this
research showed that 25 states do not post minimum speeds on
interstate highways. Currently, Florida statutes state that: "The
minimum speed limit on interstate and Defense Highways, with at
least 4 lanes, is 40 mph." The Florida Highway Patrol in the context
of this research study indicated that such a statute is required to
enable law officers to issue citations. A question was raised that
in the absence of the minimum speed rule, can the law officers use
another Florida statute that states "No person shall drive a motor
vehicle at such a slow speed as to impede or block the normal and
reasonable movement of traffic" to warn or issue citations to slow
moving vehicles? One police officer pointed out that if a vehicle is
alone on the highway traveling at, say 25 mph, what traffic is the
driver impeding?
RECOMMENDATIONS
Further research is needed to ascertain the effect of the current
posted minimum speed limit on driver behavior. While the data seem
to indicate that the 40 mph minimum speed might not be that relevant
based on prevailing operating speed distributions, it is not clear
what the effect would be if the signs were removed from rural
interstate highways. The answer to most of the questions raised
above requires field evaluation, as simulation analysis would not
appropriately depict driver behavior on roadways with and without
posted minimum speed limit signs.
Additional research that is planned includes collecting data on
interstate highway sections in states that do not have minimum speed
limits posted but have similar geometric and driver characteristics.
A comparison of multistate data might shed some light on the
relevance of posting minimum speed limit signs. Multistate data
would also be of interest to traffic engineers who want to compare
safety characteristics on sites with and without posted minimum
speed limits.
REFERENCES
2002 Florida Statutes. Title XXIII, Chapter
316, section 183(3).
Hauer, E. 1971. Accidents, Overtaking, and Speed
Control. Accident Analysis and Prevention 3:1-13.
Lave, C. 1985. Speeding, Coordination, and the 55 mph
Limit. American Economic Review 75:1159-1164.
McShane, W.R., R.P. Roess, and E.S. Prassas. 1998. Traffic Engineering. Upper Saddle
River, NJ: Prentice-Hall.
Mussa, R. 2003. Nationwide Survey of the Practice of
Posting Minimum Speed Limit Signs on Interstate Highways,
manuscript.
National Committee on Uniform Traffic Laws and
Ordinances. 1954. Uniform Vehicle
Code. Washington, DC.
______. 1964. A Comparative Survey Based on the
Uniform Vehicle Code. Traffic Laws Annual 1.
Transportation Research Board (TRB). 1984. Special
Report 204: 55: A Decade of Experience. Washington, DC: National
Research Council.
U.S. Department of Transportation (USDOT), Federal
Highway Administration. 2000. Highway Capacity Manual.
Washington, DC.
West, L.B. and J.W. Dunn. 1971. Accidents, Speed
Deviation and Speed Limits. Traffic Engineering 41:52-55.
END NOTES
1LOS classifies the quality
of operation provided by the roadway from A through F, with "A"
representing the most favorable driving conditions and "F" the
worst, measured at the peak hour period of the day (USDOT 2000).
ADDRESSES FOR CORRESPONDENCE
1 Corresponding author: V. Muchuruza, Department of Civil Engineering and Environmental Engineering, Florida A&M University-Florida State University, 2525 Pottsdamer Street, Tallahassee, FL 32310. E-mail: vmuchuruza@eng.fsu.edu
2 R. Mussa, Department of Civil
Engineering and Environmental Engineering, Florida A&M
University-Florida State University, 2525 Pottsdamer Street,
Tallahassee, FL 32310. E-mail: mailto:mussa@eng.fsu.edu
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