In This Issue
Technologies for an Aging Population
March 1, 2009 Volume 39 Issue 1

Designing In-Vehicle Technologies for Older Drivers

Monday, March 16, 2009

Author: Joachim Meyer

New in-vehicle systems must be designed for users who receive no training in how to use them and whose cognitive and sensory abilities vary.

Seventy years ago people were already concerned about older drivers having to adjust to changes in cars. In an article on traffic accidents and age, written in 1938, we read “. . . drivers who were trained on 30-mile per hour cars will have to be retrained to drive their improved vehicles safely at the higher rates of speed prevailing on our highways” (De Silva, 1938). The rapid development of technology since then and the aging of the population have greatly increased those concerns.

Today, new in-vehicle systems must be adapted to their prospective users, who receive no specific training on how to use them and whose cognitive and sensory abilities vary. The design of these devices will determine whether or not users accept them and will, therefore, have major business consequences for the companies that market them. In this article I outline some of the challenges facing the designers of in-vehicle devices for an older population and suggest how these devices can be designed and introduced in ways that encourage their success.

The Aging Driver Population
The population in most developed countries, including the United States, is rapidly aging. As longevity increases, the number of people over the age of 65 in the United States is also increasing. In addition, as birth rates decline, older people make up a larger proportion of the general population.

But old age is not what it used to be (and there is little reason to be nostalgic about this). In the past, old age was often associated with disease and disability, but older people today are more active and healthier than ever before. Even though more people are diagnosed as suffering from chronic diseases, such as hypertension and diabetes, the adequate management of these conditions enables them to function without serious disabilities (e.g., Manton et al., 1998). In addition, older people today are better educated than previous generations and more likely to strive to maintain their independence and mobility. These trends are expected to continue in the future.

Older people are also driving more than ever before. This is the first generation in which almost everybody earned a driver’s license during adolescence and has been driving ever since. Not surprisingly, therefore, in the U.S. National Household Travel Survey, 89 percent of older Americans (age 65+) reported using personally driven vehicles as their means of transportation (Collia et al., 2003). The percentage of the population over 65 with driver’s licenses increased from 62.7 percent in 1982 to almost 80 percent in 2003, and it is likely to increase somewhat more in the future. Therefore, the number of older drivers and their percentage in the total driver population is increasing rapidly (see Figure 1).

Figure 1

Figure 1 Number and percentage of drivers 65 years of age or older in the U.S. driver population. Source: Federal Highway Administration statistics and predictions (

Special Needs of Older Drivers
There is no specific age at which a person becomes an older driver. According to De Silva, in 1938, more than a quarter of the U.S. population was over 40 years old, and “persons beyond their forties can not expect to continue to drive at the same rate as they did in their younger days.” Indeed, visual abilities do decline from age 40 on (or even earlier), and the decline becomes steeper as we age. Other cognitive and sensory abilities usually change only when a person reaches 60 or 70, and some abilities, such as language skills, may change very little. There are also large individual differences in the onset and extent of these changes (see Meyer, 2004, for an analysis of aging and driving). Most statistics on older drivers set the cutoff age around the age of retirement (60 or 65), but empirical data show gradual changes with age and no clear transition from a middle-aged to an older driver.

A number of these changes are particularly important for driving and the use of in-vehicle devices. Among them are age-related changes in night vision, contrast sensitivity, recovery from glare, and a decrease in the useful field of view (UFOV) (i.e., the width of the visual field over which information can be acquired in a quick glance). Aging is also accompanied by general slowing in processing speed. The initiation of responses and their execution become slower, especially for unex-pected events (Olson and Sivak, 1986).

It seems logical that age-related changes in drivers’ abilities would make them more accident-prone, but older drivers are by and large safe drivers. After age 60, the number of traffic fatalities per billion kilo-meters driven increases steadily (Evans, 2004), but this increase is mainly due to older people’s fragility rather than their greater involvement in accidents (Li et al., 2003). Older drivers are likely to be fatally injured in an accident from which a younger person may walk away almost unharmed. Only after age 80 does the involvement of older drivers in accidents exceed the involvement of 20 to 29 year olds. Thus older drivers seem to be able to compensate effectively for age-related changes, for instance, by limiting themselves to daytime driving, using familiar routes, and avoiding difficult traffic situations (see Chapter 7 in Shinar, 2007, for a description of the driving characteristics of older drivers). Of course, Alzheimer’s disease and other cognitive and sensory disorders may impair a person’s ability to drive safely (e.g., Dubinsky et al., 2000), and people suffering from such diseases should cease driving.

New Technologies in Cars
Although cars and driving are changing faster today than at almost any other time in the last century, driving a car manufactured in the 1950s is very similar to driving a one produced in 2000—the speed is regulated by pressing the accelerator and the brake pedal, and direction is controlled by turning the steering wheel. The information for driving is mainly collected by looking through the windows, both in normal driving and when backing up and maneuvering.

Today, however, new technologies are being introduced into the car that alter the way the driver controls the vehicle (for a description of many of these systems, see Ashley, 2008). Typical examples are adaptive cruise control (ACC), which allows a driver to maintain a constant speed, but also a constant distance from vehicles traveling in the same lane. Thus speed is no longer solely controlled by changing the pressure on the accelerator or brake pedal. The car automatically accelerates and decelerates within preset limits.

The information available for driving is also changing. Various types of warnings are now installed in cars, including forward-collision warnings, backup warnings, and lane-departure warnings. Night-vision systems and various cameras provide drivers with visual information. These and other enhanced vision systems are becoming additional sources of information for controlling the vehicle. They give drivers a better understanding of the driving situation and make it more likely that they will detect obstacles and hazards.

Cars are also increasingly equipped with devices that support tactical aspects of driving. These include navigation systems that help a driver find a route toward a destination by providing turn-by-turn directions or by showing the route on a map display. They may also provide traffic advice, informing a driver about congestion, accidents, or road work, and can help a driver choose a route with minimal delays.

Finally, systems to entertain the driver and passengers are also rapidly changing. Such systems have been in cars, in the form of car radios, since the early 1930s, but they have greatly evolved. Today systems with combined advanced communication and computing capabilities provide not only entertainment, but also access to information. In addition, they can communicate with people outside the car. The use of these devices is usually unrelated to the driving task itself. Examples of such systems are car entertainment systems, cellular phones, text message systems, and in-vehicle e-mail and web access.

Many cars today use the same computer system to interact with all three types of devices. For instance, a computer display may show the view from a rear-facing camera when the car moves backward. The same computer may also show route information for navigation and provide access to the entertainment system or a screen for reading text messages. Although these devices can have great benefits for a driver, they can also interfere with safe driving.

Older Drivers and New In-Vehicle Systems
New in-vehicle systems create particular challenges for older drivers. Paradoxically, even though older drivers may find it more difficult to use these devices, they are likely to be the first to encounter them, because innovations are often initially introduced into high-end cars, which are usually bought by more affluent (and usually older) costumers. Thus the more mature driver population is often the first to encounter still immature systems.

Older drivers can, of course, benefit from new systems. When well designed, technology can limit the effects of age-related changes. For instance, a major problem for many older people is decreased flexibility. In a survey of older drivers in the United Kingdom, more than half of the respondents mentioned difficulties with turning their heads and looking out the rear windows (Herriotts, 2005). The reduced motility of the neck and head, combined with a narrower useful field of view, may increase the likelihood that an older driver will collide with an object behind the car when backing up. When changing lanes, older drivers may also be less likely to see a vehicle coming from behind in a parallel lane.

Alerts and visual aids, such as rear-view camera systems, can help alleviate these problems. But for older drivers to benefit from them, their designers must consider the users’ abilities and characteristics. For example, interfaces should be as simple and intelligible as possible. Almost everyone over the age of 60 has trouble focusing sharply on nearby objects, a condition called presbyopia, and most people require corrective lenses to view close objects (Weale, 2003). While driving, drivers will not put on reading glasses to use a system, and they may find driving with bi- or multifocal glasses unpleasant. Therefore, in-vehicle displays and devices should be designed so that drivers with presbyopia can still use them. Some evidence has shown that older drivers particularly benefit from multi-modality displays that combine visual and auditory information (Liu, 2000). However, hearing loss is also fairly common among older adults. Thus designers must also take this into account in designing auditory displays.

The design of intelligent interfaces that predict and support drivers’ actions can also help alleviate age-related problems. For instance, in a recent study in our laboratory, we examined the performance of older and younger drivers while using an in-vehicle telematic system (Lavie and Meyer, 2008). We compared performance with various levels of adaptivity in the telematic system. A system with the highest level of adaptivity could predict a driver’s actions and perform them automatically. At lower levels of adaptivity, the driver chose from a suggested list of possible actions. In the fully adaptive mode, the performance of older and younger drivers and their use of the system were almost the same, as long as the system correctly predicted the driver’s intentions. Thus intelligent, adaptive software may make these devices safe and acceptable for older drivers. However, the systems must be very reliable. In our study, an incorrect prediction of a driver’s intention had a much more adverse effect on older drivers than on younger ones.

A number of factors may make the introduction of new in-vehicle devices problematic for older drivers. The main advantage of older drivers is probably their long experience with driving, which makes them, overall, very safe drivers. However, the need to learn new skills, related to new devices, may render their previous experience obsolete. Although people are often able to perform familiar tasks and skills up to a very advanced age, learning new skills and changing familiar routines becomes more difficult with age (Craik and Jacoby, 1996).

Even apparently simple systems, such as rear-view cameras, require learning new skills. Common driving situations, like backing out of a garage, involve a coordinated set of complex actions related to the collection of information (by turning the head, etc.), decelerating and accelerating, and turning the steering wheel. When using a rear-view camera, the driver must look at the screen in front of her, and not turn the head, and use the information from the screen to control the steering of the car. Thus the driver must change well established routines, which may be more difficult for older drivers.

Distraction is another issue that may affect the adoption and safe use of new technologies by older drivers. With age, the ability to focus and divide attention tends to decrease (e.g., Greenwood and Parasuraman, 1997). In-vehicle devices often require that a driver divide attention between driving and using the device. Some evidence of these difficulties was apparent in the survey of older drivers in the United Kingdom (Herriotts, 2005). Many of them said they had problems with their car radios; others said they did not have problems because they simply never used their radios when driving. If an older driver is distracted when using in-vehicle systems, he or she may compensate by driving slower and leaving more space between the vehicle and the car ahead (Merat et al., 2005).

If an older driver learns to use a new system, there is a real danger of what has been called “automation bias,” or “complacency” (Parasuraman and Riley, 1997). If a driver comes to rely entirely on the new system, for example, a backup warning system, a lane-departure warning, or an intelligent cruise control system that maintains spacing between cars, he or she may eventually begin to initiate a lane-change maneuver without bothering to look, assuming that the warning system will issue a cue if the lane is occupied. However, these systems are considered convenience systems and are not designed to be safety systems. They are, therefore, not sufficiently reliable to be the main source of information for initiating a maneuver.

Also, drivers may not understand the limitations of new technologies. In a survey of the use of in-vehicle technology by young and older drivers, many respondents indicated that they expected these systems to be useful even in situations for which they were not designed (Jenness et al., 2008). For example, more than half of the respondents said they expected a backing aid system (which sounds an alarm when the car approaches an obstacle while backing up) to issue a warning when backing out of a driveway into the street and into the path of an oncoming car. The rate of misperception of the conditions in which the system might be useful was the same for older and younger drivers. However, if older drivers eventually learn to rely on the system to compensate for age-related changes, their misperceptions could have more severe consequences.

Technology should be designed for people, which includes considering aging drivers. We must design cars (and technology in general) so that older people can use them, and, more important, so that new devices make life more comfortable, safer, healthier, and better overall for older people. This is not purely altruistic—designing for older people is likely to benefit everyone. Older people do not need different systems, but they are less able to compensate for a bad design.

A technically well designed system may provide major benefits for older drivers, but it may also turn out to be useless or even to cause harm. To make the success of a system as likely as possible, its design must be based on an understanding of older drivers’ characteristics and needs. Thus this is an instance in which “user-centered design” is particularly important (e.g., Owens et al., 1993). The designer should take into consideration theories, research, and recommendations from human-computer interaction (HCI or CHI), cognitive engineering, ergonomics, and human-factors engineering (e.g., Helander et al., 1997; Shneiderman and Plaisant, 2004; Wickens and Hollands, 1999).

At the same time, although extensive research has been done in all of these fields, there are still large gaps in our knowledge of how to design in-vehicle devices, especially if they will be used by older drivers. A major research effort will be necessary to fill these gaps. We should strive for the development of advanced engineering models of users in general, and older users in particular, specifying their characteristics and predicting their responses to different system designs. We are still very far from having such models. Most of the time we are grappling with different design suggestions and comparing them without the aid of such a model.

Conducting the research and developing models of technology use, particularly by older people, is one of the major intellectual, scientific, and engineering challenges of the 21st century. Meeting that challenge will require the collaboration of engineers, psychologists, physicians, researchers, and practitioners in many other disciplines.

The insights gained from such efforts will have implications for almost all domains of life, not just vehicle design. Technologies designed with an eye to older users will not only provide an important service for older drivers and society as a whole by increasing mobility and making driving safer, but are also likely to be a major business opportunity in the 21st century.

I would like to thank Hilla Burstein for her help in preparing this article.

Ashley, S. 2008. Driving towards crashless cars. Scientific American 299(6): 58–65.

Collia, D.V., J. Sharp, and L. Giesbrecht. 2003. The 2001 National Household Travel Survey: a look into the travel patterns of older Americans. Journal of Safety Research 34(4): 461–470.

Craik, F.I.M., and L.L. Jacoby. 1996. Aging and Memory: Implications for Skilled Performance. Pp. 113–137 in Aging and Skilled Performance: Advances in Theory and Applications, edited by W.A. Rogers, A.D. Fisk, and N. Walker. Mahwah, N.J.: Erlbaum.

De Silva, H.R. 1938. Age and highway accidents. Scientific Monthly 47(6): 536–545.

Dubinsky, R.M., A.C. Stein, and K. Lyons. 2000. Practice parameter: risk of driving and Alzheimer’s disease (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 54(12): 2205–2211.

Evans, L. 2004. Traffic Safety. Bloomfield Hills, Mich.: Science Serving Society.

Greenwood, P.M., and R. Parasuraman. 1997. Attention in Aging and Alzheimer’s Disease: Behavior and Neural Systems. Pp. 288–317 in Attention, Development, and Psychopathology, edited by J.A. Burack and J.T. Enns. New York, N.Y.: Guilford Press.

Helander, M.G., T.K. Landauer, and P.V. Prabhu. 1997. Handbook of Human-Computer Interaction, 2nd ed. Amsterdam: North Holland.

Herriotts, P. 2005. Identification of vehicle design requirements for older drivers. Applied Ergonomics 36(3): 255–262.

Jenness, J.W., N.D. Lerner, S. Mazor, J.S. Osberg, and B.C. Tefft. 2008. Use of Advanced In-Vehicle Technology by Young and Older Early Adopters: Selected Results from Five Technology Surveys. NHTSA Report DOT HS 811 004, September 2008. Springfield, Va.: National Technical Information Service.

Lavie, T., and J. Meyer. 2008. Benefits and costs of adaptive user interfaces. Manuscript, submitted for publication.

Li, G., E.R. Braver, and L.-H. Chen. 2003. Fragility versus excessive crash involvement as determinants of high death rates per vehicle-mile of travel among older drivers. Accident Analysis and Prevention 35(2): 227–235.

Liu, Y. 2000. Effect of advanced traveler information system displays on younger and older drivers’ performance. Displays 21(4): 161–168.

Manton, K.G., E. Stallard, and L. Corder. 1998. The dynamics of dimensions of age-related disability 1982 to 1994 in the U.S. elderly population. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 53(1): B59–B70.

Merat, N., V. Anttila, and J. Luoma. 2005. Comparing the driving performance of average and older drivers: the effect of surrogate in-vehicle information systems. Transportation Research Part F: Traffic Psychology and Behavior 8(2): 147–166.

Meyer, J. 2004. Personal Vehicle Transportation. Pp. 253–281 in Technology for Adaptive Aging, edited by Richard Pew and Susan Van Hemel. Washington, D.C.: The National Academies Press.

Olson, P.L., and M. Sivak. 1986. Perception-response time to unexpected roadway hazards. Human Factors 28(1): 91–96.

Owens, A., G. Helmers, and M. Sivak. 1993. Intelligent vehicle highway systems: a call for user-centered design. Ergonomics 36(4): 363–369.

Parasuraman, R., and V.A. Riley. 1997. Humans and automation: use, misuse, disuse, abuse. Human Factors 39(2): 230–253.

Shinar, D. 2007. Traffic Safety and Human Behavior. Oxford, U.K.: Elsevier.

Shneiderman, B., and C. Plaisant. 2004.  Designing the User Interface: Strategies for Effective Human-Computer Interaction, 4th ed. New York: Addison Wesley.

Weale, R.A. 2003. Epidemiology of refractive errors and presbyopia. Survey of Ophthalmology 48(5): 515–543.

Wickens, C.D., and J.G. Hollands. 1999. Engineering Psychology and Human Performance, 3rd ed. Upper Saddle River, N.J.: Prentice Hall.


About the Author:Joachim Meyer is associate professor, Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beer Sheva, Israel.