Select Committee on Transport, Local Government and the Regions Appendices to the Minutes of Evidence

Memorandum by Transport Research Institute, Napier University (RTS 45)


  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 drivers.

1.  The role of illegal speed in crash severity and frequency.

  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 trajectories.

  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)




Driver Age17-24 years olds fastest, then 25-58, then 58 years plus
SexMales faster than Females
Social ClassA/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.
DomicileLiving out of town, faster
Experience1-3 years driving experience, faster
Engine SizeDrivers of cars with engines 1.6 litre and above, faster
Age of carDrivers of cars 1-7 years old, faster
Annual MileageAbove 10,000 miles per annum fastest, then 5,000-10,000, then below 5,000
Company CarCompany car drivers, faster
Drive as workDriving 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 literature.

  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 route:

    —  age;

    —  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 style—a central component of the model of crash involvement of Figure 2—through 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 behaviour.

    (c)  Changing the culture of the roads by changing the capability of the equipment. Here's a not untypical manufacturer's press release:

    "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 1999, p29).

  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

  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. Oxford: Pergamon.

Professor Stephen Stradling

Transport Research Institute

Napier University

January 2002

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