Memorandum by Transport Research Institute,
Napier University (RTS 45)
ROAD TRAFFIC SPEED
I am replying to your Press Notice No 15 of
Session 2001-02 dated 19 November 2001.
I wish to make four points based upon research
work conducted by ourselves and others concerning speeding car
1. The role of illegal speed in crash severity
Speed kills by increasing crash severity. The
laws of physics inexorably dictate that the higher the speed at
impact, the more energy must be absorbed by hard metal, soft flesh
and brittle bones. Speed at impact will be a function of pre-incident
speed and of the time and distance available to take avoiding
action (braking and steering). Reducing speeds (and increasing
separation eg, headway or following distance to the vehicle in
front) will allow more time for the avoidance of intersecting
Illegal speed elevates crash frequency. Drivers
who break the speed limits, violate other rules of the road, and
who seek thrill when driving pose greater risks to themselves
and to other road users. Drivers who report having been penalised
for speeding in the previous three years are more likely to report
also having been accident-involved during that period. In the
US, drivers with more speed citations were found to have been
involved in more crashes and in crashes involving excess speed
(Stradling et al, 2000; Cooper, 1997). Thus, the kinds
of drivers who speed are "crash magnets".
Speed reduction may be achieved by modifying
roads or vehicles to reduce the opportunities for speeding, or
modifying drivers and their trip agendas to reduce the inclinations
and presses to speed.
2. Who speeds?
Who are the "crash magnets"? Person
factors that make a difference to drivers' reported speed choice
are summarised in Table 1. (Stradling & Meadows, 2000)
DEMOGRAPHIC, VEHICLE AND VEHICLE USE CHARACTERISTICS
OF CAR DRIVERS REPORTING HIGHER SPEEDS
WHO REPORTS HIGHER SPEEDS?
|Driver Age||17-24 years olds fastest, then 25-58, then 58 years plus
|Sex||Males faster than Females
|Social Class||A/B fastest, then C1, C2, then D/E and Retired
|Household Income||£30,000 per annum fastest, then £20,000-£30,000 per annum, then below £20,000 per annum.
|Domicile||Living out of town, faster
|Experience||1-3 years driving experience, faster
|Engine Size||Drivers of cars with engines 1.6 litre and above, faster
|Age of car||Drivers of cars 1-7 years old, faster
|Annual Mileage||Above 10,000 miles per annum fastest, then 5,000-10,000, then below 5,000
|Company Car||Company car drivers, faster
|Drive as work||Driving as part of work, faster
Those driving at higher speeds are more likely to be young,
more likely to be male, from higher social classes and higher
household income groups, to live out of town, to be inexperienced
drivers, to drive larger cars (60 per cent of those in our study
who had been penalised for speeding drove cars of 1.8 litres or
above), to drive newer cars, to drive a high annual mileage, to
drive a company car and to drive as part of their work.
This pattern of results resolves into two main groups: young,
inexperienced drivers and those who live outside town centres
and drive large cars large distances as part of their work.
Amongst the youngest group of drivers young female drivers
are fast catching up with young male drivers. Fortunately, as
Figure 1 shows, plotting the reported speeds for both sexes by
age group, relative to the average reported for the sample as
a whole (zero on the y-axis), they grow out of it quicker. Young
females (17-20) report normal speeds as fast as young males, but
males then report faster normal speeds than age-equivalent females
up until age group 50-59 when speed choices again converge.
3. Causes of crashes
Figure 2 shows a descriptive model of the person and system
influences on frequency of crash-involvement. The model posits
a "violation route" and an "error route" to
a crash, though there will undoubtedly be interactions between
the two converging paths in the model which will influence how
successful the driver is at collision avoidance.
In the model peripheral factors influence more proximal factors.
For example, age and gender make documented differences to the
factors below them. Age, gender and all the factors below them
have links to crash involvement which are documented in the research
The model suggests that violations directly influence safety
margins and that driving with reduced safety margins makes the
driver vulnerable to error by any of the parties in a road traffic
situation as a result of which trajectories may intersect unless
remedial action (braking, steering) is taken. Recent work from
the Netherlands also suggests we may now begin unpacking the ways
in which the ever increasing demands of a traffic system grinding
towards gridlock increase time and mental load stress and thus
driver mental workload, in turn increasing the likelihood of error.
The core of our formulation is that:
Violations (eg, speeding, close following, running
red lights, aggressive driving, drink-driving, etc) are a part
of the expressive component of driving.
Violations reduce safety margins, thereby increasing
the likelihood of both active and passive crash involvement.
Excessive mental workload demands promote errors
which may take advantage of reduced safety margins, such that.
Violation + Error = Crash.
Young drivers typically figure higher on factors on the violation
personality factors such as risk-taking;
lifestyle factors such as night driving;
general attitude factors such as fearlessness
and compliance with peer pressure;
(in)experience (which also promotes error proneness);
unsafe driving beliefs and attitudes;
high violating driving style;
all of which may lead to driving with reduced safety margins (which
magnifies error impact).
Those who drive a car as part of their work tend to figure
high on both the violation and error route, suffering high mileage
and time pressure leading to violation, and traffic system congestion
and work load stress leading to error.
The model thus accommodates these two high risk groups. It
also has implications for road safety countermeasures, suggesting
that the effectiveness of interventions will depend on bringing
about reliable and sustainable changes to the proximal causes
of crash involvement at the heart of the model: safety margins;
errors and those elements of the traffic system that promote them;
violations and those underlying attitudes to which they give expression.
4. Three modest proposals
(a) The most effective way to change people's behaviour
and bring about sustainable change integrated into their behavioural
repertoire is to make it as easy as possible for them to change.
To conform to the local speed limit requires that the driver knows
the answer to two core questions: "How fast am I going?"
and "What's the speed limit round here?" Obtaining the
answers to these questions, without substantial distraction from
the driving task in order to scrutinise the speedometer and visually
search the roadside, is more difficult than it need be.
The bulk of daily driving in the United Kingdom is done on
urban roads with a 30 mph limit and motorways with a 70 mph limit.
Few car speedometers clearly show either "30" or "70"
on the dials. DTLR tell us that the difference in outcome between
hitting a pedestrian at 30 mph or 35 mph is critical, yet discerning
the difference on the typical speedometer is not easy.
Too many signs at the transition from one speed limit zone
to another are small, grubby, obscured, ill lit and not repeated.
Many drivers are unsure as to what the "national speed limit
applies" sign means, especially on inter-urban single carriageways.
This situation could be readily remedied, with repeater signs
and road paint.
Modifying speedometer design and speed limit signage would
remove common excuses for speeding ("I didn't know how fast
I was going"; "I didn't know what the speed limit was
there"). Legislation to require them would signal a desire
to facilitate rather than coerce compliance by making it as easy
as possible for drivers to observe speed limits.
(b) Driver retraining, unlike engineering and other enforcement
measures, offers the opportunity to substantially modify driving
stylea central component of the model of crash involvement
of Figure 2through practical demonstration and on-road
instruction with fast feedback. Signs and speed tickets say "Slow
Down"; a programme of re-education says "Here's how".
The Institute for Transport Studies at Leeds University are currently
conducting for DTLR an evaluation of the current Driver Improvement
Scheme programme in England and Wales, and may suggest ways in
which this programme could be made even more efficacious. Figures
from the forthcoming RAC Report on Motoring 2002 will show a surprisingly
large proportion of the motoring public in favour of driver retraining
at five or 10 year intervals (I cannot reveal to you actual figures
as they are embargoed until the Report launch on 22 January!).
Modifying the driver in this way rather than by monetary or other
penalty is likely to make a more sustainable change to driver
(c) Changing the culture of the roads by changing the
capability of the equipment. Here's a not untypical manufacturer's
"FAST Ford fans, which would appear to mean half the
adult male population of the country, are in for a millennium
treat when the market leader resurrects the hot Fiesta with a
new 130 mph pocket rocket". (from The Scotsman, 8 September
The problem of speeding could be solved at a stroke of the
Ministerial pen: no more cars capable, as in this case, of an
86 per cent "mark-up" on the maximum legally permitted
on-road velocity in this country. Why do manufacturers make these
cars? And why does the government let them?
Cooper P. (1997). The relationship between speeding behaviour
(as measured by violation convictions) and crash involvement.
Journal of Safety Research, 28 (2), 85-95.
Stradling SG and Meadows ML (2000). Highway Code and Aggressive
Violations in UK Drivers. Global Web Conference on Aggressive
Driving Issues at www.drivers.com.
Stradling SG, Meadows ML and Beatty S (2000: forthcoming).
Characteristics of speeding, violating and thrill-seeking drivers.
In JA Rothengatter, RD Hugenin (Eds) Traffic and Transport Psychology.
Professor Stephen Stradling
Transport Research Institute