In depth - Dirección General de Tráfico

In depth
26
MINISTERIO
DEL INTERIOR
from the Observatory
Second quarter 2011
1. Introduction
The impact of traffic speed on safety is the focus of intense
debate between scientists, road users and policy-makers. The
goal of this brief report is to summarise the most important scientific literature in this field of research.
Increasing traffic speed may have several positive effects, the
most important one being the reduction in travel times. The enormous technical advances achieved in the past decades in the
design of roads, vehicles and traffic management, along with the
improvement in the behaviour of users, have made it possible to
increase traffic speeds while, at the same time, reducing the risk
of accident and injury. The decrease in travel times has important
benefits to productivity and provides users with more spare time
for other activities.
Speed has also important negative consequences, such as
energy consumption, environmental impact and road accidents
and injuries. This brief report focuses solely on the relationship
between speed and safety.
There are several reasons why speed affects safety. Many of
them are of a physical nature: the distance required for fully stopping a vehicle increases with speed; therefore, the probability of
avoiding a collision with another vehicle or obstacle in an emergency situation decreases with speed. On the other hand, injuries and property damage in a crash increase with impact speed,
which, at the same time, increases with the speeds of vehicles
before the collision.
As will be summarised in section 3, empirical research provides clear evidence of the negative impact of speed: greater
speed increases the risk of accidents and injuries, both at the
individual level —relationship between the speed of a given driver
and his risk— and at the aggregated level —relationship between
the average speed of traffic flow and the total number of accidents
and injuries—.
Reports from national and international road safety organisations concur that speed is, together with alcohol consumption and
failure to wear seat belt, the main risk factor of accident and injury
[Ref. 1]. According to the European Road Safety Observatory’s reports, speed is an essential contributory factor in around 10% of
all accidents and 30% of fatal accidents [Ref. 2]. Similar figures
are cited in the World Health Organization’s world report [Ref. 3].
In Spain, speed, whether excessive or inappropriate, was cited as
a contributory factor in 13% of the injury accidents registered by
traffic police officers in 2009; this percentage rose to 31% in fatal
accidents [Ref. 4].
Speed management plays a key role in road safety strategies
based on the so-called Safety System approach, such as the
Swedish Vision Zero or the Dutch Sustainable Safety [Ref. 5]. One
of the fundamental principles of this approach is that the traffic
system should be able to tolerate human errors and limitations,
without them resulting in deaths or serious injuries. In order to
achieve this goal, it is necessary to manage crash energy, so that
no user is exposed to forces greater than those determined by
National Road Safety
Observatory
www.dgt.es
physical vulnerability. Thus, the concept of safe speed emerges,
defined as the value of traffic speed that can ensure the protection
of users. Safe speed depends on the characteristics of road infrastructure and traffic flow; for example, it is lower on rural roads
than on motorways, and it is also lower on pedestrian areas than
on wide avenues where flows of pedestrians are segregated from
motor vehicles.
This brief report also includes a discussion about the impact
of speed limits, as the basic tool to manage speed (section 4).
2.
Factors affected by speed
The precise relationship between speed and the number of
accidents and victims is affected by many factors related to the
road, the vehicles and the drivers. This affirmation is easy to check
when one compares the performance of modern motorways with
that of rural two-lane, two-way roads. On motorways, average
speeds are far higher, but the number of fatalities, for the same
amount of distance travelled, is about three times lower. One
should not conclude from this observation that higher speeds
contribute to reducing accidents, but rather that there are many
other factors —in our example, mainly related to road design—
that affect the precise number of accidents and victims that is
expected at a given value of speed.
Active safety systems in vehicles, such as anti-lock braking
system (ABS) and electronic stability control (ESC), also affect the
relationship between speed and safety. Assuming that a driver’s
behaviour remains the same —in particular, that his choice of
speed is independent from the characteristics and safety systems
of his car—, these devices reduce the risk of being involved in a
crash.
In order to study the impact of speed, independently from the
influence of other factors, we must suppose that a given driver,
driving a fixed car through a fixed road segment, increases his
speed. What changes should we expect then?
The most important changes have to do with vehicle dynamics: [Ref. 6]. Firstly, the stopping distance increases with speed,
due to the increase of both the distance travelled during the time
of perception and reaction, and the distance travelled during
braking. Secondly, as speed increases, the gap between travelling
speed and the maximum speed determined by tyre-road friction
is narrowed, thus increasing the risk of veering off road on a bend
and the risk of hydroplaning in rain conditions.
Speed also influences accident severity, i.e. the probability that
someone involved in a collision will be injured. At the moment of the
collision, the amount of energy to be dissipated depends on the
squares of the impact velocities of the vehicles involved (kinectic
energy). An increase in this energy leads to an increase in the probability of injuries among the people involved in the accident —as vehicle occupants or pedestrians—. The relationship between impact
speed and injury risk has been amply proven in scientific literature
(see e.g. [Ref. 7]).
In depth l 26
One of the most controversial effects of speed has to do
with drivers’ behaviour. Many drivers claim that driving slowly
becomes monotonous and that, as they increase their driving
speed, their level of attention rises, with a net improvement
in safety. However, it should be borne in mind that at higher
speeds, the rate at which the driver must process information about the highway and its environment increases directly,
demanding an extra effort that may cause fatigue. As the researcher Shinar points out [Ref. 8], «the act of paying attention
is an effort» (p. 233), so the increase in the level of attention with
increasing speed, if any, would occur in any case at the expense
of an increase in the fatigue caused by driving.
To our knowledge, the only research carried out so far on
the relationship between speed and the level of driver’s attention was an experiment conducted in Sweden in the 1990s
[Ref. 9]. Twenty-four drivers participated in the experiment,
each of whom did 200km of motorway driving three times at
speeds of 70km/h, 90km/h and 110km/h, respectively. The
level of attention was measured through the reaction time.
Despite the large differences between the three speeds tested, the changes observed in the reaction times were small: a
40km/h increase in speed was found to produce a reduction
of 4% in the reaction time. The author concluded that «the
present findings indicate that the possibility of counteracting
these consequences [the increase in stopping distance due
to higher speeds] by being somewhat more alert at higher
speeds are not great» (p. 441).
3.
Relationship between driving speed and the number
and seriousness of the accidents
Introduction
3.1.
We have already discussed that the precise relationship
between speed and the number of accidents and victims is
affected by many factors. Most past research has not sought
to determine relationships between exact values of speed and
accidents, but between variations of speed and variations of accidents. Let us consider a particular kind of road, through which
vehicles and drivers of known characteristics drive. At present, it
is not possible for us to estimate the expected number of accidents at different given values of speed: 60, 80, 100, 120 km/h.
However, research evidence does allow us to estimate the percent variation of accidents that should be expected when speed
increases from, say, 60 to 80 km/h, or 100 to 120 km/h, while
the remaining factors of influence remain constant.
There is another usual way to describe and analyse the speed
problem, consisting in determining the proportion of accidents
in which excessive speed (speed over the maximum permitted
speed) or inappropriate speed (unsuitable for the prevailing conditions) appear as the main cause or a contributory factor. The
main drawback of this approach is that it cannot be used to
estimate the variation of accidents that should be expected from
an increase or decrease in speed. Let us assume that excessive
speed has been identified as the main cause of 10% of accidents. This does not imply that perfect compliance with speed
limits would reduce accidents only by 10%. Even when the main
cause of an accident is different from speed (for example, veering into oncoming traffic due to a distraction), speed still influences the probability of the accident occurring and of it resulting
in injuries.
Individual and collective risk
3.2.
Once established our goal of estimating relationships between variations of average speed and variations of accidents,
two basic approaches are possible:
•
[Approach 1] To analyse the relationship between the driving speed of a given driver and his risk of accident involvement.
•
[Approach 2] To analyse the relationship between the
average speed of the vehicles as a whole and the total
number of accidents occurring on a stretch of road, road
or road network.
These approaches are discussed in sections 3.3 and 3.4
respectively.
3.3.
Relationship between speed and individual risk
In order to obtain representative relationships between the
speed of a driver and his accident risk, we should ideally be
able to count the number of accidents in which a given driver is
involved when travelling at different speeds. By doing so, driver’s
characteristics would remain constant, and thus have no influence on the results. However, this method is not feasible, due to
practical difficulties and also to the fact that accidents are rare
events in most drivers’ lives.
The practical solution consists in comparing the speeds of
two different populations of drivers: the population of drivers involved in accidents and a sample of the population of drivers
travelling on the road network at a certain moment. If drivers
involved in accidents travelled, on average, at higher speeds
than those of drivers not involved in accidents, we would conclude that speed significantly increase the risk of accident. If the
speeds of both populations of drivers are the same, we would
conclude that it does not affect risk.
The initial speeds of the vehicles involved in accidents can
only be obtained by means of reconstruction procedures, which
are expensive and may be prone to error. Another drawback of
the method is that, since we are observing two different populations of drivers, there may be characteristics of the drivers, other
than speed, which may vary between both populations and bias
the estimates of risks. For instance, age and sex are two factors that influence accident risk and that, at the same time, may
determine speed. Under these conditions, if it is found that the
vehicles moving faster than the others are involved in more accidents, it is not clear to what extent the result can be due to the
fact that such vehicles are typically driven by younger drivers,
who have a higher risk at any speed.
The first studies of the relationship between speed and individual risk were published in the U.S. in the 1960s. Among them,
the best known and most frequently cited is certainly Solomon’s
study [Ref. 10], in which a U-shaped curve was obtained, according to which the risk was minimal for drivers who travelled at
a speed slightly above the average speed of the traffic flow, and
it increased both for faster and slower drivers.
According to various authors (see e.g. [Ref. 11]), Solomon’s
study has methodological inadequacies that could significantly
bias its risk estimations. On the other hand, the most recent
studies have not replicated the U-shaped curve. The latest available study was conducted by the University of Adelaide [Ref.
12][Ref. 13] and researched the relationship between a vehicle’s
speed and the likelihood of involvement in an accident with at
least one person hospitalised. According to a review published
by researchers Aarts and Van Schagen [Ref. 14], the results of
the Adelaide study “for now […] best describe the relationship
between individual vehicle speed and crash rate” (page 222).
These results are shown in Figure 1; as can be seen, both risk
curves —for urban and interurban roads— are monotonically increasing in the whole speed range.
Figure 1.
Relationship between speed and risk of involvement in an
accident with at least a person hospitalised.
35
30
Relative risk
(average speed=1)
25
20
15
10
5
The power model stems from the observation of the effects produced by the different speed limit changes that took
place in Sweden in the late 1960s and at the beginning of
the following decade. A detailed discussion of the model is
outside the scope of this report. The main issue here is the
validity of its predictions. Two key validations have been carried out so far:
•
The validation by Rune Elvik et al [Ref. 20] [Ref. 21]
[Ref. 22].
•
The validation by Hauer and Boneson [Ref. 23], for
the American association AASHTO’s Highway Safety
Manual [Ref. 25].
0
-15
-10
-5
0
5
10
15
20
25
Difference with respect to average speed (km/h)
Urban roads (limit 60km/h)
Source:
Interurban roads (limit 80-120 km/h)
[Ref. 12] [Ref. 13].
Relationship between average speed and accident
frequency on a stretch of road or road network
3.4.
The input data are the same in both cases: the collection of 526 speed-accident estimates obtained by Elvik et al
from 115 scientific studies. Each of these 526 estimates is
expressed in terms of the percentage change in accidents or
casualties of a certain severity produced by a certain speed
change.
The conclusions of the above two validations of the power
model can be summarised as follows.
•
The vast majority of scientific evidence available relates to
the relationship between the total number of accidents and
casualties and the average speed on a stretch of road, road or
road network. Among all the models proposed in the scientific
literature, the most popular one is certainly the so-called ‘power model’, proposed by the Swedish researcher Göran Nilsson [Ref. 15]. This model has been cited as scientific evidence
by, inter alia, the European Road Safety Observatory [Ref. 16],
the OECD [Ref. 17], the European Transport Safety Council
[Ref. 18] and the World Health Organisation [Ref. 19].
On interurban roads, the validations in general provide
consistent results with the power model. Table 1 presents an overview of the predictions of the power model
and the two validations for two initial average speeds (80
km/h and 120 km/h), and different changes in speed.
The validation by Elvik et al leads to values very close to
those of the power model in all cases, while the validation by Hauer and Boneson is in line with it for an initial
speed of 120 km/h, and predicts larger effects when the
initial speed is 80 km/h. As can be seen in the table,
even very small increases in speed may lead to significant changes in fatal accidents; thus, a change from 120
to 121 km/h is expected to increase the number of fatal
accidents by 3-4%.
En Profundidad l 26
In its complete formulation, the power model comprises
six equations that relate variations in the number of accidents
and in the number of road users killed or injured, to variations
in the average speed of traffic. If we focus on the three accident equations, the model can be summarised as follows:
an increase of 1% in the average speed, all other influencing
factors (including traffic flow) being kept constant, results in,
approximately:
•
An increase of 4% in fatal accidents.
•
An increase of 3% in fatal and serious accidents.
•
An increase of 2% in accidents with casualties of any
severity.
The following discussion will be primarily focused on the
effect of speed on the number of fatal accidents. Figure 2
shows the prediction of the model for this kind of accident.
80%
60%
40%
(%)
Change in the number of fatal accidents
Figure 2. Change in the number of fatal accidents (%) as
a result of changes in average speed (km/h), according
to the initial average speed.
20%
80km/h
90km/h
0%
-15
-10
-5
0
5
-20%
-40%
-60%
Change in average speed (km/h)
Source:
Power Model [Ref. 15].
10
100km/h
15
120km/h
•
There are fewer studies in urban areas. Elvik et al have
found a smaller effect in these cases: a 1% increase in
the average speed would result in an increase of approximately 2.6% in fatal accidents, instead of 4% as
predicted by the power model.
•
Another interesting finding of both validations is that
the effects of speed seem not to depend on the country where the study was conducted. In this sense, Elvik et al point out that “there is no support for the
idea of de-veloping separate versions of the model for
each country. This shows that the effects of speed on
road safety are likely to be universal and not strongly
influenced by conditions that are specific to a certain
country” ([Ref. 21], page 23). The validation by Hauer
and Boneson, on the other hand, concluded that “the
speed-versus-crash relationship in the foreign studies was similar to that in the U.S. studies” ([Ref. 24],
page 26).
To conclude this discussion, it is important to note that the
average speed is not the only parameter of the speed distribution that influences safety. In particular, there is consensus
that the dispersion of speeds between vehicles is a risk factor, although there are no reliable estimates of this effect. The
European Road Safety Observatory summarises it as follows:
“If on a particular road, the speed variance is high, this will
result in less predictability, more encounters, more overtaking
ma-neuvres, etc. Therefore, when the speed differences increase, the accident risk increases as well. […] But no reliable
quantified relationship has been established for this linkage”.
([Ref. 2], page 6).
Table 1.
Predictions of the effect of variations in average speed on the number of fatal accidents, according to initial average speed.
The number of fatal accidents varies…
If the initial average
speed is…
80 km/h
120 km/h
According to the
power model
According to the
validation
by Elvik et al
According to the
validation by Hauer
and Boneson for the
Highway Safety Manual
Increases by 8 km/h
+46%
+48%
+58%
Increases by 4 km/h
+22%
+22%
+28%
Increases by 1 km/h
+5%
+5%
+7%
Decreases by 1 km/h
-5%
-5%
-7%
Decreases by 4 km/h
-19%
-19%
-26%
Decreases by 8 km/h
-34%
-35%
-52%
Increases by 8 km/h
+29%
+30%
+32%
Increases by 4 km/h
+14%
+14%
+15%
Increases by 1 km/h
+3%
+3%
+4%
Decreases by 1 km/h
-3%
-3%
-4%
Decreases by 4 km/h
-13%
-13%
-15%
Decreases by 8 km/h
-24%
-25%
-29%
And the average
speed…
Methodology for drawing up the table:
Power model: the equation (5.2) on page 56 of [Ref. 15] has been used.
Validation by Elvik et al: a power model with exponent 4.13 is used, according to table 10 of [Ref. 21] and table 7 of [Ref. 22].
Validation by Hauer and Boneson: table 3E-2 on page 3-57 of [Ref. 25] is used, converting mph to km/h and using linear interpolation when the value
ranges diverse from those in table 2 in this report.
4.
Influence of speed limits
The speed limit is certainly the most important of all the
speed management tools. A speed limit change will influence
safety to the extent that it leads to a change in actual driving
speeds. The causal sequence would be the following: an increase (or decrease) in the speed limit leads to an increase (or
decrease) in the mean speed of traffic, which in turn leads to an
increase (or decrease) in the number of accidents and casualties. If we have empirical relationships between the speed limit
change and the change in the mean speed, we may apply the
power model - or the validations presented in the previous section - to estimate the expected impact on accidents.
Evidence show that a speed limit change leads to a change
in the same direction in the actual driving speed. For example:
•
The researchers Elvik, R. et al concluded that “on the
average, the change in the mean speed of traffic induced
by a change in speed limit appears to be around 25%
of the change in speed limit” ([Ref. 20], page 93); i.e.
a change in the speed limit of, for example, ±10km/h
produces on the average a change in the mean speed of
traffic of ±2.5km/h.
•
The OECD mentiones in its report on speed management
that “meta-analyses show that lowering the speed limit by
10 km/h leads to a decrease in speed of 3-4 km/h. A similar effect can be expected from an increase in the speed
limit” ([Ref. 17], page 100).
Thus the mean speed of traffic increases to a lesser extent
than the increase in the speed limit. But this does not mean
that the effect on accidents will be small. For example, the
power model states that an increase from 120 to 122.5 km/h
in the mean speed would lead to a 9% increase in fatal accidents.
Most of the experiences in raising the speed limit confirm the
negative impact on accidents. We will cite only a few relevant
cases. More case studies can be found in [Ref. 19].
In Denmark, the speed limit was raised on half of the motorway network from 110km/h to 130km/h on 30 April 2004.
On the other half, the speed limit was maintained at 110km/h.
The Danish Road Directorate carried out an assessment of its
impact during the 16 months after the entry into force of the
change [Ref. 26]. In August 2005 the Danish Government introduced the point system for driving licences; as from that
date it is not possible to separate the effect of both measures.
On motorways where the speed limit was maintained at 110
km/h, the average speed decreased from 118.9 to 116.0km/h
(by approximately 2.4%). This reduction was presumably the
consequence of the measures that follow the increase in speed
limit, such as: increased traffic surveillance, stricter penalties, awareness campaigns and speed limit signposting at the
110km/h motorways. To the contrary, on roads where the speed
limit was raised, speed increased from 120.4 to 121.2km/h (by
approximately 0.7%). The changes observed in the number of
casualties were as follows: on motorways where the speed limit
was raised: increase of 9%; on motorways where the speed
limit was not changed, decrease of 40%; on all other interurban
roads: decrease of 18%. According to the regression model adjusted by the authors of the report, a change in mean speed of
+/-1km/h results in about 10% increase/decrease in personal
injuries. This relation is much more pronounced than the one
predicted by Nilsson’s power model.
A speed limit change can have overall effects that go beyond
the impact on the roads affected. It has sometimes been argued
that an increase in the speed limit on high-capacity roads could
indeed lead to an increase in the number of casualties on these
roads, but at the same time, to a shift of journeys from rural roads
- more dangerous roads - so that the system-wide net balance
is positive. This argument comes mainly from some studies conducted in the U.S., such as [Ref. 27]. However, the latest research
has not found these effects. Grabowski and Morrisey [Ref. 28]
examined the overall impacts of the two speed limit changes in
the U.S. in 1987 and 1995; the following effects were found:
•
•
Increase in the speed limit from 55 mph to 65mph (year
1987): 16-17% increase in the number of fatalities on the
roads affected; non-significant effect on the interurban
roads that were not affected.
Increase in the speed limit to 70-75 mph or higher (year
1995): 36-37% increase in the number of fatalities on the
roads affected; 7-11% increase on the interurban roads that
were not affected.
Therefore, the authors did not find a reduction of fatalities in
those roads where the speed limit was not changed. In fact, the
second result above shows an increase in fatalities, a result that
may be linked to the speed spillover or generalization theory, according to which the changes in average speeds on certain roads
may extend their effect to other parts of the road network.
5.
Driving speeds in Spain
Drivers’ behaviour towards speed is usually studied in freeflow situations, where the prevailing conditions are such that the
driver can choose any speed: lack of roadside checks, low traffic density, favourable road design, road surface in good condition and good weather conditions. The available data in Spain
show that, under free-flow conditions, between 38% and 59%
of the drivers travel above the maximum speed limit; in between
17% and 37% of the cases, the scale of the offence is more than
10km/h.
Table 3.
Average speeds of light vehicles in Spain under free-flow
conditions. 2010.
Table 2.
ROAD TYPE
Average
speed
(km/h)
% over the
limit
% more
than
10km/h
over the
limit
Motorway
117.7
52%
27%
Dual carriageway
113.9
38%
17%
Trunk road.
Speed limit 90
km/h
96.3
51%
32%
Trunk road.
Speed limit 100
km/h
98.4
59%
37%
Source: National Road Safety Observatory, study carried out by The University Institute for Automobile Research (INSIA) [Ref. 29].
The recent evolution has been clearly positive. Free-flow indicators are currently only available for the years 2009 and 2010.
To carry out a time analysis, we must use other two indicators concerning all traffic conditions, and not just traffic-calmed
situations under favourable conditions. For instance, the Ministry
of Public Works performs measurements of average speeds at a
sample of locations in the road network of its ownership. These
measurements show that the percentage of light vehicles travelling over 120 km/h on motorways has fallen from 27.99% in 2003
to 17.08% in 2010. On trunk roads, the percentage of vehicles
travelling over 100 km/h has fallen from 17.35% to 12.30% over
the same period.
Evolution of speeds in points of measurement of the Ministry of Public Works. Period 2003-2010.
Indicator
2003
2004
2005
2006
2007
2008
2009
2010
% Light vehicles travelling over 120km/h
on dual carriageways
27.99%
25.16%
26.17%
19.68%
20.60%
18.92%
15.71%
17.08%
% Light vehicles travelling over 100km/h
on trunk roads
17.35%
15.25%
16.73%
12.00%
12.45%
9.54%
12.23%
12.30%
Source:
Ministry of Public Works [Ref. 30].
Another available indicator is the average speed on sections
controlled by fixed speed cameras, in which, according to the
information collected by the National Road Safety Observatory,
the percentage of vehicles travelling over the speed limit fell from
28-29% in 2006 to 9-13% in 2010, with a very similar evolution on
dual carriageways and trunk roads.
The two types of data above —speeds on a sample of sections of the network and speeds on sections controlled by speed
cameras— suggest the following two conclusions: firstly, the
policies of recent years, such as the point system for driving licences and the plan for installation of speed cameras, have been
successful in reducing speeds; secondly, this reduction seems
to have taken place across the entire network, and not just in
controlled sections.
Although a precise assessment has not yet been made, it is
plausible to assume, on the basis of all the scientific pieces of evi-
dence cited in previous sections, that the fall of the driving speed
which has occurred over the last few years must have played a very
significant role in the reduction of the accident rate in Spain since
2003 (down by 54% for road accident fatalities over 2003-2010).
6.
Conclusions
This report has presented a general overview of the current
knowledge about the relationship between speed and safety. The
following is a summary of the main conclusions:
•
The relationship between speed and safety can be analysed
from the perspective of the individual risk —relationship between the speed of a driver and his risk— or of the collective risk —relationship between the average speed of the
vehicles as a whole and the total number of accidents—.
National Road Safety Observatory
Josefa Valcárcel, 28
28071 Madrid
www.dgt.es
MINISTERIO
DEL INTERIOR
Nipo: 128-11-027-3
Nacional Road
Safety Observatory
•
With regard to the individual risk, the most comprehensive study is the one conducted by the University of
Adelaide, which shows that the risk of involvement in
a serious crash increases steadily with speed, both on
urban and interurban roads.
a 1% increase in average speed leads to an increase of
approximately 4% in the number of fatal accidents can be
accepted. On urban roads, evidence suggests that the impact of speed could be lower than the one predicted by
the power model, but it is in any case significant.
•
From the perspective of the collective risk, Göran Nilsson’s
power model is the most commonly used model. The power
model is based on the following qualitative principles:
Evidence showed, moreover, that the relationship between
speed and accidents does not significantly depend on the
country or region concerned.
•
A change in speed leads to a change in the same direction in crash/casualties frequency.
•
The greater the change in speed, the greater the
change in crash/casualties frequency.
The available evidence confirms the aforementioned principles. It has been found that the relationship between
speed and safety is very consistent: if average speed increases (or decreases), the number of fatal accidents almost always increases (or decreases). From a quantitative
point of view, the validations carried out have confirmed
that, on interurban roads, the predictions of the power
model are valid; in this way, the rule according to which
•
With regard to the impact of the speed limit, most evidence
indicates that the mean speed of traffic changes in the same
direction as the speed limit, however, the magnitude of the
change is smaller (around 25%). The available evidence
shows that an increase in the speed limit leads to an increase
in accidents and casualties.
•
Spain has seen significant decreases in speed across the
entire interurban road network and not just in controlled sections. Taking into account all scientific evidence available, it
is plausible to assume that this decline in speed must have
made a major contribution to the recent reduction in the
number of accidents.
References
• (Ref. 1) European Transport Safety Council (2010) Tackling the three
main killers on the roads. A priority for the forthcoming EU Road Safety
Action Programme. PIN Flash N.16. Brussels.
• (Ref. 2) European Road Safety Observatory (2006) Speeding. Retrieved January 20, 2007 from www.erso.eu.
• (Ref. 3) World Health Organization (2004) Informe mundial sobre prevención de los traumatismos causados por el tránsito.
• (Ref. 4) Dirección General de Tráfico, Observatorio Nacional de Seguridad Vial (2010) Las principales cifras de la siniestralidad vial. Spain 2009.
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