Splash and Spray Measurement and Control:
Recent Progress in Quebec
G. Dumas and J. Lemay
Department of mechanical engineering, Laval University, Quebec City, Canada
Summary. This paper presents results of a series of road tests measuring the spray
clouds generated by a truck/trailer traveling on a watered roadway with and without specifically-configured splash guards covering all the wheels. The tests were
conducted with a carefully-arranged set of laser transmissometers, and data show
significant reductions in spray density at some fixed positions from the truck-trailer
and the roadway. Data is also given showing the effect of adding a drag-reducing
air shield on the truck. Emphasis is put on the full-scale test procedures and on the
reliability/repeatability of the measurements.
1 Introduction
Every motorist driving regularly on highways has experienced situations of
significantly reduced visibility in rainy conditions while following, crossing or
passing a heavy truck. There is no doubt that such encounters can increase
the anxiety level of the drivers (cars as well as trucks) and may represent a
serious road safety hazard.
Although one usually refers to the “splash and spray” as the generic phenomenon responsible for this adverse effect on visibility, it should be pointed
out that it is more the spray clouds surrounding the heavy vehicle than the
splash itself that represents the main perturbation and inconvenience. Indeed,
the splash being the part associated with the large droplets of water raised
by the tires, it tends to follow ballistic trajectory and to stay relatively close
to the ground on smooth road surfaces. Interference with motorist’s visibility
is thus minimal. On the other hand, the spray which consists of very small
droplets of water can remain airborne for a long time and be transported
along in the turbulent air flow. It typically produces fog clouds on each side of
the vehicle and behind it (Fig. 1). According to previous studies such as the
extensive work of Weir et al. in the 1970’s [1], the spray is formed when some
water is being atomized after impacting a hard surface under the vehicle. If
there is a sufficiently large air flowrate in that area, the mist being produced
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G. Dumas and J. Lemay
Fig. 1. A mild case of reduced visibility due to the splash and spray of a typical
heavy truck.
is evacuated away before it gets a chance to reform large droplets that would
quickly fall back to the ground.
It should be emphasized here that the formation mechanism of spray and
its later dispersion involves quite complex physics and aerodynamics as well
as a large variety of parameters which can be classified as “truck-centered” or
“situational” [2]. For example, in the former category, one would include the
tires treads, the speed and load of the truck, its general shape and underbody
details, while in the latter category, one would list the pavement texture, the
thickness of the water film on the road, and the magnitude and direction of
the ambient wind.
Strangely, the important progress made in the 1970’s and 1980’s on several
of these aspects has not brought us much closer to practical, real life solutions
of the splash and spray problem in the 1990’s and up to now. In our view,
the main reason for that is twofold: first, no system or devices tested so far
seem to provide the desired overall level of effectiveness at a minimum cost
and with minimal adverse effects (on the drag, the brakes, the maintenance,
etc.), and second, perhaps more importantly, the lack of recent development
turns out to be fundamentally linked to the difficulties associated with the
measurement of the phenomenon itself.
Indeed, virtually all large scale efforts in this area of research were abandoned when in 1988, the National Highway Traffic and Safety Administration
(NHTSA) announced [3] that it was terminating its pending rulemaking (ordered in 1982) to require splash and spray suppression devices on all new
truck tractors, trailers and semitrailers because it determined that no available technology had been demonstrated to
“... significantly reduce splash and spray from truck tractors, semitrailers and trailers, and significantly improve visibility of drivers, as demonstrated during testing
on highways, at test facilities, and in laboratories to take into account possible
wind and rain conditions.” [3]
The major problem for the NHTSA was a lack of consistency and too much
variability in the full-scale road test data that had been produced to establish
the effectiveness of a wide variety of splash and spray suppression devices and
Splash and Spray Measurement and Control
535
concepts. NHTSA’s position has remained unchanged since then as reported
in updates to Congress in 1994 [4] and 2000 [5].
All the same, the splash and spray problem has continued to bother highway users despite the very few actual crashes that have been officially linked
to it [4]. The general public interest has nonetheless remained high as well
as the interest of the transport industry. Several national and local governments in America and in Europe have thus proposed, or have been considering
proposing, some form of legislation on the question [5]. In that spirit, the Department of Transportation of the province of Québec (Canada) in 1997 gave
the present authors the mandate to develop a local expertise on the splash and
spray issue that could be used to carry out rigorous, repeatable comparisons
between existing and future anti-spray systems or devices.
Since then, two campaigns of full-scale road tests [6][7] have been realized
by the authors to develop a proper measuring technique and to compare a
few basic spray suppression devices. A third experimental campaign was also
undertaken in a small-scale wind tunnel to investigate the laboratory modeling of spray clouds and to contribute towards a better understanding of the
aerodynamic aspects of the problem [8]. This last campaign is not discussed in
this paper so as to emphasize the test procedures put forward in our two road
campaigns, and the lessons that have been learned for better, future tests.
2 Road Test Measurements
The challenges associated with the quantitative measurement of the spray
clouds characteristics in typical highway situations are not conceptual or theoretical issues. They are rather of a very basic, practical/economical and technical nature. Repeatable conditions of crosswind and water film for instance
may be quite demanding to provide, even on a dedicated test track. So are
the parameters of speed and precise positioning of the test vehicle on the wet
track. Many passages of the test vehicle may thus be required to reduce uncertainty in the mean data, but testing budget and track schedule are often
quite restrictive. Some compromises and optimization of the procedure have
to be devised and validated.
A valiant effort to do so and to propose a rigorous road test protocol was
initiated in the early 1990’s by Johnson and Weir under the auspices of the
Society of Automotive Engineers. It yielded in 1994 the SAE Recommended
Practice J2245 for splash and spray evaluation [9] which synthesized almost
two decades of R&D in the United States. To the authors’ knowledge, however,
there was no report available in 1997 of its formal application in an actual
road test campaign, nor has there been since then. Some key aspects of the
recommended procedure are briefly reviewed below.
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G. Dumas and J. Lemay
2.1 SAE Recommended Practice J2245
In the SAE recommended procedure [9], two types of approach are proposed.
Both of them involves stationary test setups, meaning that the test-truck is
driven through a wet test section with the measuring instruments installed
on both sides of the track. An alternative setup attached to the truck has
been proposed in Europe [10], but it seems more appropriate for local splash
measurements than for global spray clouds characterization that is of interest
here.
The first technique recommended in the SAE standard is called the “video
digitizing method”, and it uses large checkerboards (see Fig. 2a) and image
processing techniques to measure the loss of contrast when the spray cloud
happens to be between the camera and the target board. Although interesting
in principle in terms of providing some discrete spatial information over entire
planes, this approach was not selected here due to the post-processing delays
involved and the significant crosswind sensitivity expected.
The second, and more attractive method in our opinion, is called the
“laser transmissometers method” and it measures the loss of light transmission through the mist, i.e., the opacity of the spray cloud. According to the
standard, two lasers are used on each side of the track (see Fig. 2) and are set
at a height above the road corresponding to a typical car driver’s line of sight.
The four corresponding photometers are positioned in front of the lasers at
least 15 m (50 ft) away. The signal from each of the photocell is continuously
recorded during the passage of the test vehicle.
Assuming here the “SAE low crosswind scenario”, i.e., crosswind component less than 5 km/hr (3 mph) during the run of a given test truck configuration on the wet track, the procedure J2245 defines the “measurement for
that run” as being the arithmetic average of the four photocell values. Each
of the sensor measurement is expressed as a percentage of light transmittance
reduction (% obscured) called “Figure of Merit” (FOM) which is calculated
as
#
"
Vmin − V0
F OM = 100 × 1 −
(1)
Vmax − V0
1.68 m
Midpoint of Test Section
60.96 m (200 ft) to end (type)
Laser
Photocell
15.24 m (50 ft) min
VEHICLE PATH
1.14 m
(a)
0.61 m
1.83 m
1.52 m
Slope = 1%
(b)
3.66 m (12 ft)
Anemometer
Fig. 2. SAE’s recommended practice J2245. (a) View from behind showing the 4
lasers and the checkerboards; (b) Plan view of the test section. Adapted from [9].
Splash and Spray Measurement and Control
537
where Vmax is the voltage before the passage of the vehicle (unimpeded beam),
Vmin is the minimum voltage recorded during the run, and V0 is the “zero
voltage” (offset) measured when the beam is occluded. A 100% means total opacity of the spray cloud while 0% means total transmittance, i.e., no
visibility impairment.
In the present work, the authors have preferred to use the terminology
“Opacity Index” (OI) in place of Figure of Merit to facilitate interpretation
and to emphasize the difference put forward with respect to Vmin as is discussed further. However, one should note for the moment that the SAE’s FOM
will correspond to the maximum instantaneous value (peak value) of the OI
proposed in this work.
The overall FOM of a test truck configuration, equipped or not with an
anti-spray device or system, is finally obtained according to the SAE’s standard by ensemble averaging over a minimum of 8 different runs at a given
wind condition such as, for example, low head wind or low left crosswind [9].
The lower the score, the better the given configuration is classified in terms
of visibility impairment and safety hazard.
2.2 First Road Test Campaign
For our first road test campaign in 1997, an original technique inspired of
the SAE’s laser method was conceived with a particular aim to provide a
richer information about the lateral distribution of opacity through the spray
cloud. Monotonic decay of cloud opacity with respect to lateral distance from
the truck seemed to be taken for granted in previous works [2] leading to the
SAE’s standard. It was believed by the present authors that, for the purpose of
comparing or developing spray suppression devices, more detailed data about
the spatial distribution of the mist was important. Information closer to the
side of the vehicle (sensors are at 1.22 and 2.13 m in SAE’s J2245; Fig. 2)
was also desired since it represents a crucial visibility region for a following
motorist in the process of deciding or not to overtake the heavy vehicle in
front of him on a two-way road.
Oscillating
mirror (1.2 Hz)
Photocells
(a)
Stepping
motor
Laser
(He-Ne 10 mW)
(b)
Fig. 3. First road campaign in 1997. (a) Ramp of 15 sensors within their protective
tubes inside the photometers housing; (b) Laser and oscillating mirror.
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G. Dumas and J. Lemay
The approach that was developed and successfully implemented involved
a 4 m ramp of 15 sensors distributed along its length (Fig. 3) yielding final
sensors positions from 0.76 to 4.78 m. A single laser with an oscillating mirror
was used to produce a sweeping laser beam that illuminated at least 3 times
each photocell while the test vehicle was moving through the central 30 m of
the 61 m test section (200 ft between laser and sensors) at a nominal speed
of 77 km/hr. A general view and sketch of this setup are provided in Fig. 4.
Note that for the purpose of this paper, most details are omitted here. For all
the information concerning these tests and the results of some comparisons
carried out between a few spray suppression approaches, the reader is referred
to the original technical report [6].
Typical raw signal for a given sensor is shown in Fig. 5. An “analyzing
window” is defined so that only the part of the signals measured while the
truck is passing in the central region of the test section, away from the perturbation of the two protective housings, is considered to calculate the Opacity
Index denoted here OI I . In that central region, it is assumed that the spray
cloud carried by the test vehicle is, statistically, in its stationary state. One
thus defines the OI I measured by each of the 15 photocells as
(a)
(b)
Fig. 4. Test track of the first road campaign in Blainville, Québec. (a) General view
of the site prior to the tests; (b) Sketch of the setup about the wet track.
Splash and Spray Measurement and Control
V-V0
539
Original signal (sensor #4)
1
0
0
2
4
6
t1
x0
8
t2
t3
No mist signal
1
0
0.01
0.02
0.03
0.04
0.05
Vwm-V0
0.06
0.07
Time (s)
With mist signal
1
0
12
Time (s)
Extracted signals
Vnm-V0
0
10
x61
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
Time (s)
Fig. 5. Typical sensor signal among 15 recorded during a run. The time interval
between t2 and t3 is the data analyzing window which corresponds to the truck
entering and exiting the central 30 m between laser and sensors. The non-vanishing
signals in the unimpeded portion and in the analyzing window (clean and perturbed
gaussian responses of the swept-by sensor) are then regrouped for processing.
OI I = 100 ×
Vnm − Vwm
Vnm − V0
(2)
where Vnm is the maximum voltage recorded with “no mist” before the passage
of the test vehicle, Vwm is the maximum voltage “with mist” in the analyzing
window (Fig. 5), and V0 is the regularly measured offset voltage. Therefore,
similarly to the SAE’s F OM , a 100% value of OI I means total opacity while
a 0% value implies that there is no visibility impairment whatsoever.
(a)
(b)
Fig. 6. Two of the truck configurations tested in the first campaign. (a) The
“base configuration” (Base) of the 5-axle tractor-trailer test vehicle with its standard European-type fenders; (b) The “reddaway configuration” (RW) of the truck
equipped with some homemade Reddaway-type of fenders [1][2].
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G. Dumas and J. Lemay
OI I (%)
100
RW
Base
80
60
40
SAE Laser #1
20
SAE Laser #2
0
0
1
2
3
4
5
Position (m)
Fig. 7. Example of results from the first campaign: Lateral distribution of opacity
index OI I (y) at a height of 1.14 m for the base and reddaway configurations. The
lateral position y is defined from the side of the truck’s trailer. The curves plotted
here represent ensemble averages over 8 runs in each case, all under SAE’s condition
of low wind.
Plotting the opacity index data of all sensors on the ramp against the
lateral position yi of each sensor – measured with respect to the actual position of the test vehicle on the track for that particular run –, one obtains
the “Lateral Distribution of Opacity” OI I (y) for that given run and truck
configuration. The distributions obtained during this first campaign for the
case of the “base truck” and for the “reddaway” configuration (Fig. 6) are
shown on Fig. 7.
These results clearly suggest that simple systems such as reddaway fenders
can have measurable and positive impact on spray clouds in terms of both,
their peak opacity and their spatial extent. From previous studies [1][2], one
can infer that opacity levels of 70% and above are perceived by human eyes as
“very bad” (no useful visibility). One would therefore require that an efficient
anti-spray device yields much lower levels (still to be determined) across the
whole width of the cloud, and in particular in the first 2 m from the side of the
truck. It is also noted from Fig. 7 (and other results of this campaign) that indeed opacity distributions appear to be reasonably monotonic and decreasing
functions, except perhaps very close to the vehicle.
Repeatability of the results provided by full-scale road tests being at the
heart of the problem in splash and spray research, dispersion in the raw data
and statistical convergence of the final results have to be considered. First, it
was noted that the dispersion in the OI I data was larger than expected: for
the base configuration, about ±12 for the inner part of the cloud (first 2 m)
Splash and Spray Measurement and Control
541
and up to ±20 in the outer part (last 2 m). Large external flow intermittence
may explain in part the difference between the two regions, but it is most
likely attributable to what has been termed the “triangle effect”, and that is
described on the sketch of Fig. 8. The phenomenon tends to add more noise
to the calculated indices in the outer portion of the cloud which makes it
more challenging to reach good statistical convergence, and is therefore an
undesirable weakness of this approach.
In any case, significant dispersion in the OI I data calculated by (2) is to
be expected due to intrinsic aerodynamics unsteady effects (air turbulence
and large-scale eddies) to which one must add the effects of varying winds
(intensity and direction) between runs. Even for “low wind” conditions (UW <
5 km/hr) considered here, important impact of the wind is expected as will
be addressed further. Furthermore, non-repeatability and non-uniformity in
the water film are important issues to be minimized, which was not rigorously
the case in this first campaign where watering was provided by distributed
sprinklers along the track.
Most importantly, one must realize that in this approach as well as in the
SAE’s recommended procedure, the only way to improve statistical convergence of the final results, and thus repeatability, is by doing more runs in
the same – as much as possible – conditions. Indeed, the only averaging used
is ensemble averaging which, according to us, requires many more than the
8 runs (per truck configuration) recommended and that were realized here.
Four times as many runs would reduce uncertainty of the mean distributions
by a factor of two which may be viewed as a minimum. Considering different
wind conditions – as many as 8 according to the SAE’s classification – as well
as different speeds of the test vehicle and different depths of the water film,
would add up quickly to prohibitive proportions in terms of both time and
testing cost.
Fig. 8. Exaggerated sketch showing the “triangle effect” that contributes to add
noise in the readings of the sensors which are not directly in front of the laser
source. While the truck moves through the central part of the test section (analyzing
window, 31 m), and considering a given photocell on the ramp, this effect yields
varying optical paths of the laser beam with respect to the cloud.
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G. Dumas and J. Lemay
A procedure that could offer faster statistical convergence was imposing
itself as a necessity to achieve dependable and repeatable full-scale road test
results. Including some temporal averaging in the process, in addition to the
existing ensemble averaging, appeared as the only practical option available to
increase convergence, and thus repeatability of the results while maintaining
the number of runs at a reasonable level. This idea as well as some significant
improvement as far as the water film is concerned were implemented in the
procedure developed for our second road test campaign.
2.3 Second Road Test Campaign
For our second campaign in 1999 (see [7] for a detailed report), we used a
small test track in the region of Quebec City. The track had a fairly uniform
1% slope across the pavement which allowed us to produce a quite uniform
and repeatable film of water (Fig. 9a), 1.5 mm thick, over the entire 61 m
(200 ft) of the test section. A 4-inch perforated pipe running along the track
(a)
Downstream trigger
Lasers
Perforated pipe
Wet pavement
Upstream trigger
Photocells
61 m (200 ft)
(b)
Fig. 9. Second road campaign. (a) Upstream view of the test track and of the
continuously fed water film; (b) Sketch of the setup about the wet track.
Splash and Spray Measurement and Control
(a)
543
(b)
Fig. 10. Second road campaign setup at run time. (a) Upstream view showing the
3 lasers at the forefront; (b) Downstream view with the 3 photocells at the forefront.
and fed by a regulated fire hydrant was used to that end. For all practical
purposes, contribution of the water film to the final dispersion of the data
was reduced to negligible proportion.
In this campaign, in order to eliminate the undesirable “triangle effect”
and to provide for some temporal averaging of the signals, each photocell
used had to have its own dedicated laser aligned with it, in much the same
way as in the SAE’s recommended practice J2245 discussed previously. The
continuous signal recorded for each sensor while the test vehicle is passing
through the “analyzing window” would permit the temporal averaging needed,
which departs in a fundamental way from the standard J2245. Based on the
results of the first campaign – relatively monotonic decay of lateral opacity
distributions – it appeared that three sensors (Fig. 9b) would be sufficient
to properly characterize the opacity distribution. The positions retained were
selected as: 0.61, 1.22 and 2.44 m (2, 4 and 8 ft; nominal values w/r to the
side of the vehicle’s trailer). This reduced number of photocells allowed to get
rid of the large and perturbing protecting housings of the first campaign as
can be seen on the pictures of Fig. 10.
Typical signals recorded at run time by the three photocells are shown
on Fig. 11. Note that sensor #1 is the inner one, closest to the truck, while
#3 is the outer one at 2.44 m (8 ft) which would correspond to the middle
of the neighbor lane next to the truck’s lane. The data indicates that the
outer part of the spray cloud takes about just under 59 m (193 ft) to build
up from zero and stabilizes. Of course, wetting of the track upstream of the
test section would easily fix this problem. This is unfortunate in the spirit of
the present method since it severely limits the time window over which one
can average the signals (assuming a common window for the 3 sensors). The
last 0.10 second (last 2 m) before the vehicle started exiting the test section
has usually been selected in this campaign.
Nonetheless, this modest temporal averaging, combined with the usual
ensemble averaging, can significantly improve convergence of the mean results,
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G. Dumas and J. Lemay
V
Sensor # 1
0.5
0
Sensor # 2
1
Entering
0.5
Exiting
0
Sensor # 3
0.5
0
4
61 m = 3 seconds
2
0
0
1
2
Trigger
3
4
5
Time (s)
Fig. 11. Signals recorded for each of the 3 sensors and the triggers during a typical
run of the second road campaign.
even though dispersion itself may still remain important, as can be seen in
Fig. 12. In this campaign, one now defines the OI measured by each of the 3
photocells in a given run as
OI = 100 ×
V be − V ss
V be − V0
(3)
where V be is the mean voltage recorded “before entering” the wet test section (with no mist), and V ss is the mean voltage in the “stationary signal”
zone (averaging time window; see Fig. 11). The results obtained for the base
truck configuration (same tractor and similar trailer as in campaign one) are
presented in Fig. 12.
The uncertainty bars shown in Fig. 12 suggest an accuracy of about ±5
points on the mean opacity indices which is already a significant improvement
with respect to our first campaign, and previous works in general in this field.
Only 14 runs have been necessary to achieve this level of confidence thanks
mainly to the temporal averaging added to the process here – admittedly
quite modest in this instance. Longer time windows exhibiting statistically
stationary signals (Fig. 11) would allow for better temporal means which
would tend to reduce even more the dispersion in the OI data, thus improving
further the confidence level of the final values. Of course, complete elimination
of dispersion in the OI from run to run is not possible due mainly to the wind’s
effects. Note finally that by eliminating the “triangle effect” present in the first
campaign, the level of dispersion in the data is now much more uniform across
the width of the cloud.
Splash and Spray Measurement and Control
OI (%)
545
100
OI Eq. (3)
Mean OI
80
60
40
20
0
0
1
2
3
Position (m)
Fig. 12. Raw results of the Opacity Index OI according to (3) for the base truck
configuration in the second road campaign (“low crosswind” runs). The 95% confidence bands of the three mean values are also shown. The line connecting these
values is only suggestive of the actual distribution of opacity.
Our second road campaign also provided the opportunity to test the effect
of a simple drag shield installed on the tractor cab. As expected, such air
shield tends to keep the mist closer to the truck thus increasing opacity in
that area. However, combined with conventional anti-spray systems such as
reddaway fenders, it tends to improve their performances in the mid and outer
portion of the cloud as can be inferred from the results presented in Fig. 13.
(b)
(a)
Fig. 13. (a) Mean opacity results from the second campaign for the RW (reddaway)
versus the AS-RW (air shield + RW) configuration – low wind condition, V = 70
km/hr; (b) Test vehicle equipped with a basic air shield on the tractor cab and
reddaway-type of fenders on the trailer.
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G. Dumas and J. Lemay
3 Recommendations for Future Road Test Campaigns
The experience gained from our two road campaigns can be summarized by
the following recommendations:
1. The general guidelines provided in the SAE Recommended Practice J2245
[9] should be followed, granted the modifications outlined below.
2. Three laser transmissometers should be used on each side of the track with
2 of them within the first 1.2 m (4 ft) from the side of the test vehicle (see
Fig. 14).
3. The distance between lasers and sensors (test section) should be of about
3 truck lengths, 61m (200 ft) in this case, to allow for proper temporal
averaging of the signals.
4. An extra 60 m or so of wet pavement should be provided upstream of the
test section to assure that statistically stationary conditions (stationary
clouds) are reached at the entrance of the test section.
Assuming, conservatively, a total span of the clouds of about 2 truck
lengths, as suggested on Fig. 14, the above recommendations would allow
for temporal averaging of the signals for at least one full “truck time scale”
(T = L/V ), i.e., over the last truck length of the test section. This translates in this case as about 1 second of time-averaging window – ten times
as much as was permitted in the second road campaign of this work. It is
expected that such an approach, coupled with ensemble averaging over about
15 “similar runs” (in terms of wind conditions, truck speed and water depth),
should yield spray measurements confidence within a few percent, and thus
circumvent the basic criticism raised by the NHTSA since 1988.
Fig. 14. Sketches of approximate spray cloud envelopes under no wind condition
(left), and under some “low crosswind” condition, e.g., UW " 4 km/hr (right).
There remains the challenge of how to properly take into account the effect
of crosswinds in the overall evaluation of spray suppression devices. It seems
to these authors that a finer grading system than the one proposed in the
SAE’s procedure is required. As suggested in Fig. 14b, it takes very little
crosswind to significantly alter the distribution of spray around the vehicle.
This represents a critical issue which still needs to be addressed.
Splash and Spray Measurement and Control
547
Acknowledgement
The authors would like to acknowledge the financial support of the Ministère des Transports du Québec, contracts MTQ/1220-97-RG01 and 122098-RG02. Help and encouragement from the project manager at DoT, M.
Mario Bussières, is also gratefully acknowledged. Special thanks to the welcoming and professional staff of the CFTC (Centre de Formation en Transport
de Charlesbourg; www.cftc.qc.ca) where our second road campaign was realized.
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