You want to make the roads safer? Try enforcement. Make it a felony to kill someone with your car. Drivers will learn very quickly how to drive safely.
Can technology improve driver competency?
By: John Svensson
Date: Monday, 31. August 2009
John Svensson is President of TRIADD: the Training and Research Institute of Advanced Driver Development.
This article originally appeared in Vol. 3, Number 4 of Driver/Education, in December 1993.
Two methods of improving the competency of the driving population are: to improve the selection process so that bad drivers are screened out; and/or to improve the training process by producing more "skilled" drivers.
However, for either of these processes to have any measure of success, we must first be able to establish a correlation between the selection or training criteria, and driver performance.
The research community has been hard pressed to establish which measurable tasks or performance criteria best correlate with predicting future collision involvement. Certainly, the specific nature of the relationship between these elements is not, as yet, clearly defined.
Do we only test for what we can measure? Are crashes the best yardstick by which to measure the success of the screening or training process? No doubt, the driver training and screening processes will continue to be complex and controversial issues, with the stringency with which they are applied remaining dependent upon the real or perceived risks drivers pose to the well-being of society.
Technologies aimed at improving driver performance fall into two categories: those which actively seek to improve driver performance (such as training programs), and those which passively seek lower driver variability in the safety equation (such as antilock braking systems).
In the case of the latter we can draw on an example from the aviation industry. Because too many of the tasks traditionally performed by pilots were computerized and automated, boredom became the new enemy in the cockpit. Furthermore, automation occurred to such an extent that successful intervention by the pilot became almost impossible in the event of an automated systems failure. Lessons learned from this aviation experience warn that implementing a technology before ascertaining whether it's necessary or desirable may be ill-advised.
In driving, the introduction of a technology such as an onboard navigation system may have the potential to help the driver avoid traffic tie-ups and improve trip efficiency. It may also act as a distraction that could, in certain circumstances, cause a crash.
A major problem here is that we don't know enough about the driving task, and about how drivers perform it, to be able to adequately evaluate technologies. There is not, as yet, a "base line" performance against which the driver's abilities and the effects of the technology on performance can be measured. In fact, we don't really know what level of performance it takes to make a driver acceptably safe in modern traffic.
So how do we implement technological change? What are the potential problems? What criteria do we use?
Before we tackle these questions let's take a look at the range of technologies we're dealing with. There are three categories: range tools; training room tools; and in-vehicle tools.
Range tools include such devices as skid cars, the slide car, tire blowout simulation devices, lane blockers, and the emergency reaction trainer (a device which allows trainers to set up avoidance maneuvers and measure driver reaction).
Training room devices include simulators, interactive videodiscs, computer based text and video (as used in testing, for example), videos and films, vision measuring devices, and attention-measuring devices.
In the vehicle we have radios, car phones, the G-Analyst, onboard computers, antilock braking systems, and a variety of navigation systems. Most of these technologies have not been validated. There is no concrete evidence that they improve driver performance in terms of safety or efficiency.
Perhaps a key factor in this deficiency is that, so far, we have defined our objectives for screening and training in very broad strokes. We've accepted that a driver's licence means that a driver is competent; we've agreed to ensure that drivers meet a general minimum standard of performance by testing them; our objectives have been very general (be safe, collision-free). Before we can make effective decisions about the use of technologies, we must be much more focused in our objectives. We need to know more about human behavior and what makes for a safer driver. We need to be clearer about our training objectives and desired learning outcomes, and we need to define training needs more sharply.
The research community is now hard at work attempting to establish what current tasks or measures of performance will correlate best with ensuring that a driver's future performance will be acceptable.
What today's and tomorrow's technologies can do is provide reliable and consistent stimuli or scenarios that can be applied to specific situations. In training, this means meeting specific needs of an individual rather than trying to apply technologies, in a broad way, to populations.
Technological interventions might be applied on a discovery, or guided discovery basis and perhaps in modular or prescriptive form rather than in a fixed curriculum. We can say that technology can improve driver competency but it will be aspect by aspect. It will not provide a panacea solution to problems. We will have to target specific behaviors, for specific populations, under specific conditions.
Decisions related to equipment purchase must take human factors into account, and changes in equipment must be viewed, not in isolation, but in a broader context of how they integrate into the total job function.
It will be critically important for trainers to keep abreast of the latest research findings and the implications of these for the use of new technologies. Trainers will also need to implement effective data collection systems as a prerequisite for validating the technology and validating decisions made about training.
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Al Cinamon,
