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Technology for Adaptive Aging 10 Personal Vehicle Transportation Joachim Meyer The face of aging is rapidly changing. Although older age in the past was mainly considered as a transient period in which abilities and activities decline, today more and more older people hope to spend their later years filled with activity and meaningful and enjoyable involvement. A crucial precondition for well-being in older age is independence. A condition for this, in turn, is the ability to move easily from place to place, i.e., the ready availability of means of transportation. Older people in urban settings may have access to various forms of public transportation. Some of these are particularly adapted to the needs of older travelers (e.g., “kneeling” buses that facilitate entrance and exit, paratransportation services that pick up people at their homes). Many mass-transit systems in metropolitan areas are also designed to accommodate older passengers. These forms of transportation have obvious societal and environmental value, and their use should be encouraged. However, transportation for the majority of older adults in the United States, and increasingly in other parts of the world, means using a privately owned and driven car (Coughlin, 2001a). The issue of well-adjusted aging is therefore closely related to the ability to continue to drive for as long as possible and to maintain the independence provided by a car. However, an older person′s driving at an advanced age may cause concern if the person has some limitations that affect driving safety. Numerous questions need to be answered regarding older drivers′ continuing to drive. Government and regulatory agencies, car manufacturers, healthcare providers, families, and society at large must address
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Technology for Adaptive Aging these questions. The answers to these questions and the solutions provided by the different agencies should be based on sound scientific research rather than on guesswork and unfounded beliefs. Some of the relevant data are already available from the large body of research on aging and driving, but many questions remain open. These issues should be at the focus of the research agenda for the coming years. In this chapter I address a number of relevant issues. I begin by discussing the transportation needs and driving patterns of older drivers. I review some of the reasons why older drivers might differ from other driver populations and focus on vision as one of the fields in which there is compelling evidence for age related decline in abilities that can affect driving. I then discuss whether older drivers constitute a safety risk (and for whom) and under which conditions they do so. I then review some of the changes that older drivers make to cope with the potential safety problems. I then discuss technologies and new in-vehicle devices and their potential to help older drivers, as well as some of the possible problems that may be associated with these technologies. I end the chapter with a brief discussion of some of the necessary research directions on older drivers in view of the new technologies that are available. CONTINUED DRIVING AT AN ADVANCED AGE The wish to be able to drive for as long as possible is understandable, given the fact that especially in rural and suburban communities there is often no alternative form of transportation other than a car. A person must use a car to go shopping, to access medical services, to attend social functions, and to visit friends and family (Rosenbloom, 1993). The loss of a driver′s license thus implies losses in many aspects of life, including personal freedom, independence, and the possibility of making useful contributions to society (Waller, 1991; Coughlin, 2001b). For the importance of mobility for the well-being of older people, see also Carp (1988). Indeed, an increasing number of people continue to drive up to an advanced age, leading to a steady growth in the number of “older old” drivers, those aged 75+ or 80+ according to different definitions (Barr, 1991). Kosnick et al. (1988) report that people 65 years and older use the automobile for 80 percent of their errands and trips. Similarly, Jette and Branch (1992) found that older drivers continue to drive for as long as possible and they resist any change in the preferred mode of travel, although they may lower the frequency of travels. Chipman, Payne, and McDonough (1998) report that 37.5 percent of a sample of Ontario, Canada, drivers aged 80 and over reported that they still drove. Relatively healthy older people were especially likely to drive. Although most of the drivers and the nondrivers suffered from two and more chronic
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Technology for Adaptive Aging diseases and more than 84 percent of both groups suffered from at least one chronic disease, the drivers had fewer chronic diseases than the nondrivers. Given the importance of driving, driving cessation can have strong adverse effects on a person. For example, Marottoli et al. (1997) showed an increase in depressive symptoms among older adults who stopped driving. The continuing ability to drive seems to be a precondition for some older people′s well-being. However, this is not a general need. Chipman et al. (1998) found in their study of 80+ years old drivers in Canada that driving cessation did not lead to a significant decrease in contacts with relatives and friends. Thus, driving, at least for this group, was not necessary for maintaining social relations. WHAT MAKES OLDER DRIVERS DIFFERENT? Discussing the issue of older drivers assumes that this group differs in some way from other groups of drivers. Obviously, one variable on which older drivers differ from other drivers is their age. However, it is not at all clear at what age a person becomes an “older driver.” Visual capabilities begin to decline in the 20th year, whereas other skills and abilities remain often practically unimpaired up to an advanced age. There is no general age criterion to define older drivers, and different studies have adopted different definitions. In spite of the lack of a universal criterion for defining older drivers, a fairly large number of studies show systematic differences between drivers as a function of age. The cause for these differences is not always clear. Below I discuss four possible reasons for differences between age groups. Cohort Effects Drivers from different age groups belong to different generations. These generations grew up in different cultural, social, and technological environments. Consequently the differences between members of the age groups may be due to these generational effects, which caused them to be exposed to different environments during critical phases of their development. One cohort effect that affects driving is the progressive motorization of Europe and the United States. Whereas most 20-year-old people today have access to cars, the same was not true 60 years ago. Women in particular had less driving experience. These differences can still affect older women′s current driving behavior. If this is the case, then differences between today′s older men and women in the frequency of trips and the use of cars will disappear in the future when the baby boom generation approaches retirement. Also, overall car use and trip frequency
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Technology for Adaptive Aging of older drivers will increase for the older drivers of the future. This will lead to an even greater increase in the presence of older drivers on the road, beyond the increase due to changes in demographics. Changing Lifestyles The aging process is not only a physiological process in which biological systems undergo changes, but it is also a social process in which a person changes involvement in activities and obligations. One major change that affects the driving habits of many older drivers is the fact that older people cease to commute regularly after they retire from work. This relieves them of the need to drive daily without considering the traffic and weather conditions. After retirement, these drivers are likely to limit their driving in adverse conditions, and after some time they may feel less confident driving at all in these conditions. Thus the exit from the work force (or other changes in lifestyle) may be a cause for changes in driving patterns. Here, too, future older drivers will differ from today′s older drivers because of the expected continuing involvement of older people in the work force beyond the current retirement age. Disease and Medication The aging process is related to an increase in the frequency of chronic and acute diseases that have adverse effects on a person′s functioning in general and driving in particular. The most extreme cases are degenerative diseases, such as Alzheimer′s disease, that limit a person′s ability to function to an extent that eventually requires constant supervision and care. More frequent are other diseases with less severe impacts. It is not quite clear how chronic disease affects driving ability. For example, Gresset and Meyer (1994) found in a study on Canadian drivers that only arrhythmia (from among a number of medical problems) was associated with a significant increase in the risk of being involved in a crash. In addition to the possible adverse effects of the diseases themselves, there are also possible adverse effects of medication that is taken to control chronic or acute health problems. Some types of medication may impair driving ability to an extent that makes continued driving unsafe. Age-Related Changes The fourth possible cause for differences between age groups is changes that are due to the physiological aging process itself. With increasing age certain basic functions change, and in most cases these changes are in the direction of lessened abilities. An extensive review of
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Technology for Adaptive Aging age-related sensory, cognitive, and motor changes is presented in Chapters 2 and 3 of this report (Schaie, and Ketcham and Stelmach, this volume). I concentrate in the following sections on those changes most likely (or actually demonstrated) to affect driving. With respect to driving, Planek (1972), in one of the earliest larger reviews of the literature on older drivers, identified three interconnected areas of deficiencies: (1) sensory reception, (2) neural processing and transmission, and (3) motor response. Later studies put greater emphasis on cognitive aspects of driving that are related to decision making (Hakamies-Blomqvist, 1996). Llaneras, Swezey, Brock, and Rogers (1993) and Shaheen and Niemeier (2001) summarize some of the age related sensory and cognitive changes that affect driving. SOME AGE-RELATED CHANGES THAT AFFECT DRIVING Vision One domain in which there is compelling evidence for age-related changes is vision. This sensory ability is particularly important, because driving is a continuous control task that is largely guided by visual information. Malfetti and Winter (1986) suggest that 85-95 percent of the sensory cues in the driving task are visual. It is therefore reasonable to assume that changes in visual performance are likely to affect driving. The decrease in visual abilities begins after the age of 20 and continues throughout a person′s life. Shinar and Schieber (1991) reach a number of general conclusions regarding the effect of normal aging on visual perception. First, apparently all visual functions deteriorate with age. Second, the amount, rate, and onset of deterioration vary widely between individuals and functions. Third, whereas static acuity begins to deteriorate in the 60s, other visual abilities deteriorate earlier. Fourth, performance differences between individuals increase with age. Table 10-1 presents a list of some of the major visual abilities that are relevant for driving. It also lists changes that occur with age in each of these abilities and the impact that these changes are likely to have on driving. The importance of vision for driving and the relative ease of administering vision tests led to the almost universal screening of drivers according to their visual ability. Tests of visual acuity are standard in the licensing procedure of most countries, and many countries require periodic retesting of acuity after a certain age. However, a closer inspection of the aging-related changes in visual performance shows that the changes in static acuity (which is measured in most vision evaluations) are by no means the only changes that occur. Also, it appears that static acuity may not be the visual ability that is most relevant for safe driving. Groeger
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Technology for Adaptive Aging TABLE 10-1 Age-Related Changes in Visual Abilities Ability Major Changes Some Implications for Driving Selected References Visual acuity: Ability to resolve small details when viewed from a distance Decline of visual acuity (myopia, near sightedness); can be partly corrected with lenses Need for corrective lenses while driving Anderson and Palmore (1974), Kline et al. (1992), Kosnick et al. (1988), Reuben et al. (1988) Dynamic visual acuity: Ability to correctly observe the direction and speed of a moving object Decline in dynamic visual acuity Difficulty in determining rate of approach and time to collision of moving obiects Sekuler et al. (1982), Wist et al. (2000) Focusing on near objects: Ability to resolve small details in a near object (farsightedness or presbyopia when related to age) Difficulty in focusing on near objects due to the loss of elasticity in the lens of the eye; can be corrected with reading glasses or bifocal lenses Need for-bifocal lenses or reading glasses to see in-vehicle displays or to locate smaller controls Bruckner (1967), Kline et al. (1992) Contrast sensitivity: Ability to detect changes in the lightness of a surface Decline in contrast sensitivity Difficulty in detecting objects or changes in the road that appear as changes in shading Fozard (1990), Owsley et al. (1983) Night vision: Ability to see in poor lighting conditions Cataracts and senile miosis limit the amount of light that reaches the receptors Difficulty in seeing objects in dim lighting (at night, in tunnels, or garages) Charness and Bosman (1992), Kline et al. (1992) Disability glare resistance: Poor vision in glare conditions Less luminance is required to produce disability glare Difficulty in night driving and in changing levels of illumination Olson (1988), Olson and Sivak (1984), Sanders et al. (1990)
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Technology for Adaptive Aging Recovery from glare: Time required to regain night vision after exposure to bright light Increased susceptibility to glare and slower recovery from glare Difficulty in night driving and driving in changing levels of illumination Charness and Bosman (1992), Pulling et al. (1980), Sloane et al. (1988), Wolf (1960) Peripheral vision: Angular width of field of view in which motion information is perceived Decrease in size of horizontal peripheral visual field Late detection of events that develop in the periphery, such as approaching cars Burg (1968), Retchin et al. (1988) Useful field of view: Width of visual field over which information can be acquired in a quick glance Decline in spatial and peripheral vision Difficulty in detecting events that develop at the sides of the visual field (merging cars, etc.) Haegerstrom-Portnoy et al. (1999), Sekuler et al. (2000) Color vision: Differential perception of light with different wavelengths Loss of sensitivity to shorter wavelengths resulting in reduced ability to discriminate blues, greens and violets Responses to color-coded displays may be affected Botwinick (1984) Visual scan: Speed and efficiency of movement of fixations in the visual field Slowing of visual scan Difficulty taking in complex traffic situations Maltz and Shinar (1999)
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Technology for Adaptive Aging (1999) points out that, in spite of the long history of research on vision and driving, very little is known about the role of different visual parameters in driving. This fact that it is not at all clear what visual abilities are actually crucial for safe driving points to one of the major issues that require research and clarification in the future. Driving ability is likely to depend on factors that are difficult to measure. Also, drivers can be highly adaptive and can compensate for deficiencies in certain areas by changing their behavior (use different driving techniques, change the conditions in which they drive, use technology to help them deal with some of the problems, etc.). It will therefore be difficult to come up with a valid, objective test that can predict who can and who cannot continue to drive safely. Clearly, simply measuring visual acuity is not enough. The age-related changes in vision presented in Table 10-1 are by no means isolated phenomena. Rather, many of these changes are connected and may affect driving performance in similar conditions. One condition in which many of the changes will lower the older driver′s ability to obtain the necessary visual information for driving is at dusk and dawn and in darkness. Here a decrease in contrast sensitivity, general diminished night vision, and prolonged recovery from glare make driving more difficult and stressful. Older adults′ vision in low illumination is impaired, relative to younger adults, even if they are in good eye health (Owsley and Sloane, 1987; Sloane, Owlsey, and Alvarez, 1988). The decrease in contrast sensitivity in older adults can be attributed to age-related reduction in pupil size and the loss of lens transparency (Owsley, Sekuler, and Siemsen, 1983; Sloane et al., 1988). The effects of aging and decreased retinal illumination (for example, because of tinted glass) are not additive. It seems that aging enhances the effects of limited illumination. Levels of transmittance of tinted glass that have no effect on younger drivers can impair vision for older drivers (LaMotte, Ridder, Yeung, and DeLanel, 2000). Thus when any manipulation or condition can lower the retinal illumination, special attention should be given to the evaluation of its effect on older drivers. Changes in vision are obviously not the only age-related changes. In addition to the aging-related changes in visual abilities, a number of other major changes in sensory, motor, and cognitive functions are likely to occur with age. I briefly review the other major changes and point out their potential relevance for driving. Hearing Hearing acuity decreases progressively, beginning as early as age 40 (e.g., Stelmachowicz, Beauchaine, Kalberer, and Jesteadt, 1989). The
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Technology for Adaptive Aging main changes are in the higher frequency range. The causes for these changes can be structural changes with aging, the cumulative effects of noise exposure, the result of traumatic events or disease, or side effects of certain types of medication. The hearing loss itself does not necessarily have direct implications on driving performance. However, it needs to be considered when auditory stimuli are intended to guide the driver or to provide warning information. The design of these auditory displays may have to take the changing hearing abilities of older drivers into account. Attention The effects of aging on attention are complex. There exists a distinction between different attention skills. One is focused attention, which is the ability to concentrate resources on a single task or information source without being distracted by other sources of information or cognitive processes. A second skill is divided attention—the ability to divide attention between a number of concurrent tasks and the monitoring of different concurrent stimuli. A third skill is attention control, which is a person′s ability to switch the allocation of attentional resources from one task to another. There is evidence that older adults have greater difficulties dividing attention effectively compared with middle-aged and younger adults (Brouwer, Waterink, van Wolfelaar, and Rothengatter, 1991). The problem is particularly pronounced when two tasks require the same output modality (e.g., motor responses) and is reduced when the tasks employ different modalities (Brouwer, Ickenroth, Ponds, and van Wolfelaar, 1990). In a study on selective attention, Mihal and Barrett (1976; see also Barrett, Mihal, Panek, Stern, and Alexander, 1977) found a correlation between selective attention and accident rates for drivers 45-64 years old, and they found no such correlation for drivers 25-43 years old. Memory The existence of aging-related changes in memory is well established (e.g., Jacoby and Hay, 1998). Problems with short-term memory may cause difficulties in retaining information over short periods of time (e.g., instructions on route choice). Problems with long-term memory may be in the encoding of information (people may find it difficult to learn new names, routes, or information). Other problems with long-term memory may be in the retrieval of information, where information that was encoded in the past (which is evident by the fact that at some time in the past a person remembered this information) is
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Technology for Adaptive Aging now temporarily unavailable. Although these problems can occur at any age, they become increasingly common when a person ages. The memory difficulties may affect the use of new in-vehicle technologies, for example, by making it more difficult to remember procedures for using the system or by interfering with the recall of names and codes that are used in speech-activated systems. Another domain where aging-related changes may impact performance is skill acquisition (Craik and Jacoby, 1996). Generally skill acquisition becomes slower with age, and a person will find it difficult to alter familiar ways of performing certain tasks. On the other hand, the procedural memory for familiar tasks and skills may remain intact up to a very advanced age. Thus a person can perform complex sets of actions, such as playing a musical instrument or driving a car. However, they may find it difficult to acquire some new skills that require changes in well-established routines. Information Processing The major change in information processing is a general slowing in processing speed. This causes a lengthening of response times and slower actions and, in particular, slower responses to unexpected events (e.g., Falduto and Baron, 1986). One study that dealt with simple and choice response times as a function of age showed that simple response times were relatively little affected by age, whereas choice response times were much more severely affected (Fozard, Vercruyssen, Reynolds, Hancock, and Quilter, 1994). With respect to driving, it appears that there are only small differences in response times to hazards on the road as a function of age. It seems that older drivers are able to brake rapidly when they encounter a problematic situation as long as they expect it (Korteling, 1990; Lerner, 1993; Olson and Sivak, 1986). Decision Making Some age-related differences in decision making have been identified (see Schaie, this volume), but decision processes that are relevant for driving seem to be relatively little affected by age. For instance, a study by Dror, Katona, and Mungur (1998) showed no effect of age on the speed of risk-taking decisions. However, one difference that seems to exist is that with increasing age people become more safety conscious (Boyle, Dienstfrey, and Sothorn, 1998). This may be due to the fact that the consequences of adverse events, such as traffic accidents or falls, are likely to be more severe for older people than for younger ones.
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Technology for Adaptive Aging Actions and Motor Behavior In addition to the cognitive changes that occur with age, there are also motor changes. Together with the cognitive slowing of responses, there often occurs a motor slowing of responses, which causes an older person to perform a movement more slowly than a younger person. Under certain conditions this may delay responses to safety hazards. Muscular strength decreases approximately 12-15 percent between the ages of 30 and 70 (Blocker, 1992). Overall there is clear evidence for a loss of strength with age, especially after the age of 65. This loss of strength is more pronounced in women than in men (Bassey and Harries, 1993). There is also a loss in the speed of muscle contractions and coordination with age (Blocker, 1992). Thus an older driver is likely to have less strength than a younger person and may consequently have more need of power steering or power brakes. A third characteristic related to aging is lowered flexibility. Approximately half of the population over age 75 experiences some degree of arthritis (Adams and Collins, 1987). This makes vehicle ingress and egress more difficult. It also limits a person′s ability to turn the head and trunk, causing difficulty looking toward the sides and rear of the car. In particular the flexibility of the neck diminishes with age, leading older drivers to have less flexion and extension and rotation capability in the neck compared to younger people (Kuhlman, 1993). This lowered motility of the neck and head is a likely cause for accidents in which an older driver either collides with an object that is behind the car when backing up or fails, when changing lanes, to see a vehicle that comes up from behind in a parallel lane. ARE OLDER DRIVERS A PROBLEM AND, IF SO, WHAT IS THE PROBLEM? The age-related changes listed above seem to indicate that older drivers are likely to constitute a traffic safety problem. However, contrary to common beliefs, it is not at all clear whether older drivers are indeed a safety risk. There are some undisputable facts. For one, the fatality rate of older drivers is high compared with other age groups. It is close to the rate of 16-24-year-old drivers. Thus older drivers are at a greater risk of dying in an accident than most younger drivers. There are two possible causes for the increased fatality rate. First, older drivers may be more likely to die in accidents because of their frailty and fragility. Impact forces that are negligible for a younger person can lead to severe and even fatal injuries for an older person (e.g., Evans, 2000). Therefore the increased fatality rate is not an indication that older
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Technology for Adaptive Aging moment in time. For example, the system can be turned on or off and, if on, it can be engaged or not engaged. Older drivers may have more problems maintaining appropriate mode awareness and may therefore find automated systems less reliable, more confusing, and less useful. As a result, such systems, even if they could be particularly useful for an older driver, can go unused. Design of the Driving Environment In addition to design changes in the vehicle that can make driving easier and safer for older drivers, there are also various changes in the driving environment that can be made and that can be very beneficial for older drivers. The Federal Highway Administration has recently published a report pointing to ways in which roadways, intersections, signs, and markings can be designed to help older drivers (Staplin, Lococo, Byington, and Harkey, 2001). Older drivers are particularly likely to benefit from improved lighting, especially at intersections. Signs and pavement markings should be large and clearly visible. Longer merge and exit lanes will make it easier to cope with fast-flowing traffic. Adjusting roadways to the needs of older drivers will obviously also benefit other drivers, especially in difficult driving conditions such as heavy rain and fog. What Technologies Are Good for Older Drivers? The brief discussion of design issues and technologies for older drivers should make it clear that the introduction of a new device into the car is not always easy and will not necessarily constitute an improvement. Some of the new technologies that are introduced into the car require the driver to change behavior patterns that have served the older driver for decades. This change may be difficult, and the need to adopt new behaviors may rob older drivers of one of their main advantages—the extensive driving experience they have acquired over the years. The notion that a device makes sense on the drawing board does not ensure that it will have the desired effect once it is introduced into the car. A number of reasons make it difficult to predict the effects of introducing a new system. Users Do Not Necessarily Accept Innovation It is by no means assured that a technologically sound device that provides definite benefits for the user will eventually be adopted. The most effective protective system against injury in a crash is a properly fastened seat belt (e.g., Rivara, Koepsell, Grossman, and Mock, 2000). In
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Technology for Adaptive Aging spite of the fact that this was widely known, it took decades for seat belts to become accepted by the majority of drivers, and this only after major efforts on the part of government agencies involved with traffic safety. Good Intentions, Bad Outcomes It is also often difficult to predict how a device will affect driving, especially because the effects of new technologies can change greatly over time. Expectations based on preliminary testing during the development phase may be unjustified. For example, the antilock braking system promised to have major safety benefits, but the actual benefits turned out to be very small. In fact, the system had an initial negative effect on safety, and some time had to pass before the accident rate returned to its level before the system was introduced (Farmer, 2001). There are at least four reasons why a system that should improve safety can yield smaller than expected benefits and may at times even lead to negative effects. First, users may not use the device correctly and therefore may fail to obtain the safety benefits (e.g., drivers with an antilock braking system may cease to apply force to the brakes when the system is active and the brake pedal vibrates). Second, the introduction of a device can create a feeling of safety that can induce a person to take a greater risk than he or she would without the device. This notion is expressed in models, such as Wilde′s (1988) risk homeostasis theory, according to which people maintain a fairly constant level of risk and expose themselves to greater danger when they are protected by some safety device. Third, a device that should benefit older drivers may not have the desired effect because it does not fit the specific driving characteristics of older drivers. For example, because older drivers may be less likely to detect possible hazards (because of diminished vision, distraction, etc.), they should particularly benefit from warning systems that provide an alert for possible problems. Indeed, older drivers respond to in-vehicle warnings in the same way as younger drivers (Cottè, Meyer, and Coughlin, 2001). However, warning systems tend to have false alarms, and the proportion of false alarms out of all alarms increases as the driver becomes more cautious (Meyer and Bitan, 2002). To demonstrate this point, consider two drivers who drive with the same collision warning system. The system has a certain detection rate when a collision is genuinely imminent and a detection rate when a collision is unlikely, the so-called false alarm rate. One driver takes great risks and therefore has many near collisions. This driver will encounter frequent warnings, and most will be justified. This driver is likely to view the warning system as useful. The second driver is very cautious, and collisions can almost never
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Technology for Adaptive Aging occur. This driver will encounter fewer warnings, and most warnings will be false alarms. Consequently this driver will believe that the warning system has only limited value. Considering that older drivers tend to drive more cautiously than younger drivers, they are likely to experience an unacceptably high false alarm rate in warning systems, causing the system to appear annoying and leading to its eventual rejection. Fourth, the user may develop new behavioral patterns following the introduction of the new technology. A backup collision warning system can serve as an example. Backup collisions are particularly likely when a person has difficulties turning the head, which is rather common for older drivers. The installation of such a system should help drivers avoid many of these collisions and should make driving safer. However, the system can also change the way a person drives. In extreme cases the user may come to back up without even bothering to look back, waiting for the warning system to cue them when to stop. This turns the warning system from being a safety device into a device for primary vehicle control. As long as the warning serves only as a safety device, a malfunction in the warning usually has no severe consequences. When the warning serves as the information source for vehicle control, its reliability becomes crucial and any malfunction can lead to an accident. The complex interplay of factors that determine the outcome of the introduction of a new device makes it necessary to develop new models and methodologies to predict the user′s reactions to a new technological system. It cannot be simply assumed that a certain system analysis that applies for the current use patterns of a device will also apply when the device is altered. The benefits that are to be expected from a new technology have to be considered very carefully. New technologies need to be evaluated over time, in conditions that are as close as possible to the actual use conditions, and with people who represent the future user population. The evaluation of devices also must take into account that the device will not be used in isolation. Rather, combinations of devices will be installed in the car and can at times be used together. For example, the driver may use a cellular phone to contact a person whom he or she intends to meet and at the same time look at the navigational system to receive directions on how to get to the meeting. The joint use of devices may create interactions that affect the utility and safety of using each of the separate devices. The prediction of the effects of new technologies is further complicated because more than the driver′s response to a system needs to be considered when evaluating the likelihood of its successful introduction. Legal and political issues are also crucial. For example, no system is perfect, and even with a very good system some collisions may occur. Some
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Technology for Adaptive Aging of them will likely be blamed on the system, and the manufacturer may be held liable. In view of this possibility, the manufacturer may take various steps to lower the chances of litigation, but these steps may also limit the usefulness of the system. Thus, the introduction of these systems requires a careful analysis of all aspects of the use of such a system, an analysis that requires the development of adequate predictive tools. CONCLUSIONS The question of how to provide older drivers with the opportunity to drive for as long as possible, while minimizing the risks due to incapacitated and unsafe drivers, is a crucial topic that will require even more attention in the future. There are numerous topics that need to be addressed to adjust for the aging driving population. For one, it is still largely unknown what causes the differences between older and younger drivers. We need to obtain a clearer picture of age-related driving characteristics. In particular it may be important to see how these characteristics change over cohorts and which of these characteristics will persist in the future. Also, the diversity of older drivers needs to be better understood, and more information must be collected on driving with different levels of impairment. At a second level we need to determine how we can change driving so that older drivers will find it easier to fit into the driving population. Some of the necessary means may involve training older drivers to become aware of age related changes and to cope effectively with safety issues. We may also want to consider changes in the driving environment. Some of these changes can be related to changes in the road infrastructure that will make it friendlier for older drivers. For example, older drivers tend to have difficulties making left turns across traffic. Left-turn traffic lights or the use of traffic circles can solve this problem. Also, at some places older drivers may have trouble merging with traffic because other drivers drive at excessive speeds. The use of traffic control devices to lower the speed of oncoming vehicles can help to cope with this problem. In the design of in-vehicle technologies, we are facing many unknowns regarding the effects of these technologies on drivers in various situations. The design of the device, the allocation of functions to it, and the design of the interface all require a thorough understanding of the interaction between users and technologies. This goes clearly beyond current knowledge in this field. The empirical basis for our research needs to be expanded by collecting both field and laboratory data. In addition, researchers need to develop appropriate design methodologies that take into account the unique characteristics of the driving situations and the
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Technology for Adaptive Aging needs and properties of the driver. This will be particularly important for older drivers, who may have less ability to adapt to a nonoptimal design of the system. Finally, models of the use of the automation and devices are needed for predicting how users will respond to a certain system design. Such models will allow us to move from the unsystematic engineering of human-vehicle systems that is practiced today to a more systematic and model-driven technique that approaches the methods used in other fields of engineering. The introduction of the new technologies into cars for older drivers also makes it necessary for car manufacturers to reconsider their roles. More attention will have to be paid to the familiarization of the new driver with the technologies in the car. The best ways to do this are still fairly unclear. Because the use of many new in-vehicle devices is not entirely intuitive, companies will need to invest resources in the training of users in order to teach them how to maximize the utility of the system and how to deal with adverse situations. This need for training is particularly important for safety-critical systems, which are usually used only rarely and in conditions in which a very rapid and almost automatic response is required. Training will be particularly important when the system requires the relearning of some well-established skills. This is likely to be a greater problem for older drivers who, on the one hand, have much experience with older systems, and who are, on the other hand, usually somewhat slower in the learning of new skills. Possibly car sales will have to include the use of simulator or test track driving to teach the driver how to respond to different events with the complex technologies. In addition, older drivers in particular will need to have the technologies customized to their particular needs. Drivers themselves can do this, but, in all likelihood, optimal customization should be based on the objective evaluation of the individual driver′s needs by a specialist. This will require the development and validation of techniques to determine the optimal configuration for a driver. Also, specialists for customizing cars to the needs of individual customers may have to be trained. It is unlikely that current sales personnel can be expected to do this job appropriately, unless they receive the tools and knowledge for this additional service. Thus the introduction of new in-vehicle technologies for older drivers requires us to expand the boundaries of our knowledge and our understanding in a wide variety of fields. It is likely that the insights gained here will be important in various domains, beyond the design of vehicles. Thus, this may be an opportunity to develop some of the major technologies for the twenty-first century, while helping an increasing number of people maintain independence, involvement, and quality of life.
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Technology for Adaptive Aging REFERENCES Abdel-Aty, M.A., Chen, C.L., and Schott, J.R. (1998). An assessment of the effect of driver age on traffic accident involvement using log-linear models. Accident Analysis and Prevention, 30, 851-861. Adams, P.F., and Collins, G. (1987). Measures of health among older persons living in the community. In R.J. Havlik, B.M. Liu, and M.G. Kovar (Eds.), Health statistics on older persons, United States, 1986. Vital and Health Statistics (DHHS Publication No. 87-1409). Washington, DC: U.S. Government Printing Office. Anderson, D., and Palmore, E. (1974). Longitudinal evaluation of ocular function. In E. Palmore (Ed.), Normal aging: II. Reports from the Duke longitudinal studies, 1970-1973 (pp. 166-230). London: Butterworth. Ball, K., Owsley, C., Stalvey, B., Roenker, D.L., Sloane, M.E., and Graves, M. (1998). Driving avoidance and functional impairment in older drivers. Accident Analysis and Prevention, 30, 313-322. Barr, R.A. (1991). Recent changes in driving among older adults. Human Factors, 33, 597-600. Barrett, G.V., Mihal, W.L., Panek, P.E., Stern, H.L., and Alexander, R.A. (1977). Information processing skills predictive of accident involvement for younger and older commerical drivers. Industrial Gerontology, 4, 173-182. Bassey, E.J., and Harries, U.J. (1993). Normal values for handgrip strength in 920 men and women aged over 65 years, and longitudinal changes over 4 years in 620 survivors. Clinical Science, 84, 331-337. Bengtsson, B., and Krakau, C.E.T. (1979). Automatic perimetry in a population survey. Acta Ophthalmologica, 57, 929-937. Blocker, W. (1992). Maintaining functional independence by mobilizing the aged. Geriatrics, 47 (1), 42-56. Botwinick, J. (1984). Aging and behavior: A comprehensive integration of research findings. New York: Springer-Verlag. Boyle, J., Dienstfrey, S., and Sothorn, A. (1998). National survey of speeding and other unsafe driving actions. (Report No. NHTSA DOT HS 808 749). Washington, DC: U.S. Department of Transportation. Brouwer, W., Ickenroth, J.G., Ponds, R.W.H.M., and van Wolfelaar, P.C. (1990). Divided attention in old age. In P. Drenth, J. Sergeant, and R. Takens (Eds.), European perspectives in psychology (Vol. 2, pp. 335-348). Indianapolis, IN: John Wiley and Sons. Brouwer, W., Waterink, W., van Wolfelaar, P., and Rothengatter, T. (1991). Divided attention in experienced young and older drivers: Lane tracking and visual analysis in a dynamic driving simulator. Human Factors, 33, 573-582. Bruckner, R. (1967). Longitudinal research on the eye. Gerontologia Clinica, 9, 87-95. Burg, A. (1968). Lateral vision field as related to age and sex. Journal of Applied Psychology, 52, 10-15. Carp, F.M. (1988). Significance of mobility for well-being of the elderly. In Transportation in an aging society: Improving mobility of older persons. (Special Report 218). Washington, DC: Transportation Research Board. Charness, N., and Bosman, E. (1992). Human factors and age. In F.I.M. Craik and T.A. Salthouse (Eds), Handbook of aging and cognition (pp. 495-552). Mahwah, NJ: Lawrence Erlbaum. Chipman, M.L., Payne, J., and McDonough, P. (1998). To drive or not to drive: The influences of social factors on the decision of elderly drivers. Accident Analysis and Prevention, 30, 299-304. Cooper, P.J. (1990). Elderly drivers′ view of self and driving in relation to the evidence of accident data. Journal of Safety Research, 21, 103-113.
OCR for page 278
Technology for Adaptive Aging Cottè, N., Meyer, J., and Coughlin, J.F. (2001). Older and younger drivers′ response to collision warning systems. In Proceedings of the Human Factors and Ergonomics Society 45th Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society. Coughlin, J.F. (2001a). Beyond health and retirement: Placing transportation on the aging policy agenda. Public Policy and Aging, 11(4), 1-23. Coughlin, J.F. (2001b). Transportation and older persons: Needs, preferences and activities. Washington, DC: AARP Public Policy Institute. Coughlin, J.F., and Tallon, A. (1999). Older drivers and ITS: Technology, markets and public policy. ITS Quarterly, 7, 123-134. Craik, F.I.M., and Jacoby, L.L. (1996). Aging and memory: Implications for skilled performance. In W.A. Rogers, A.D. Fisk, and N. Walker (Eds.), Aging and skilled performance: Advances in theory and applications (pp. 113-137). Mahwah, NJ: Lawrence Erlbaum. Drachman, D.A., and Swearer, J.M. (1993). Driving and Alzheimer′s disease: The risk of crashes. Neurology, 43, 2448-2456. Dror, I.E., Katona, M., and Mungur, K. (1998). Age differences in decision making: To take a risk or not. Gerontology, 44, 66-71. Dubinsky, R.M., Williamson, A., Gray, C.S., and Glatt, S.L. (1993). Driving in Alzheimer′s disease. Journal of the American Geriatric Society, 40, 1112-1116. Eberhard, J. (1996). Safe mobility for senior citizens. IATSS Research, 20, 29-37. Evans, D.A. (1990). Estimated prevalence of Alzheimer′s disease in the United States. Milbank Quarterly, 68(2), 267-289. Evans, L. (1991). Traffic safety and the driver. New York: Van Nostrand Reinhold. Evans, L. (2000). Risks older drivers face themselves and threats they pose to other road users. International Journal of Epidemiology, 29, 315-322. Falduto, L.L., and Baron, A. (1986). Age-related effects of practice and task complexity on card sorting. Journal of Gerontology, 41, 659-661. Farmer, C.M. (2001). New evidence concerning fatal crashes of passenger vehicles before and after adding antilock braking systems. Accident Analysis and Prevention, 33, 361-369. Flyte, M. (1995). The safe design of in-vehicle information and support systems: The human factors issues. International Journal of Vehicle Design, 16, 158-169. Fozard, J. (1990). Vision and hearing in aging. In J.E. Birren and K.W. Schaie (Eds.), Handbook of the psychology of aging (3rd ed., pp. 150-170). San Diego, CA: Academic Press. Fozard, J.L., Vercruyssen, M., Reynolds, S.L., Hancock, P.A., and Quilter, R.E. (1994). Age differences and changes in reaction time: The Baltimore Longitudinal Study of Aging. Journal of Gerontology, 49(4), P179-189. Gresset, J., and Meyer, F. (1994). Risk of automobile accidents among elderly drivers with impairments or chronic disease. Canadian Journal of Public Health, 85(282-285). Groeger, J.A. (1999). Expectancy and control: Perceptual and cognitive aspects of the driving task. In P.A. Hancock (Ed.), Human performance and ergonomics (pp. 243-264). San Diego, CA: Academic Press. Haegerstrom-Portnoy, G., Scheck, M.E., and Brabyn, J.A. (1999). Seeing into old age: Vision function beyond acuity. Optometry and Vision Science, 76, 141-158. Hakamies-Blomqvist, L. (1993). Fatal accidents of older drivers. Accident Analysis and Prevention, 25, 19-27. Hakamies-Blomqvist, L. (1994). Compensation in older drivers as reflected in their fatal accidents. Accident Analysis and Prevention, 26, 107-112. Hakamies-Blomqvist, L. (1996). Research on older drivers: A review. Journal of the International Association of Traffic and Safety Sciences, 20, 91-101. Hakamies-Blomqvist, L. (1998). Older drivers′ accident risk: Conceptual and methodological issues. Accident Analysis and Prevention, 30, 293-304.
OCR for page 279
Technology for Adaptive Aging Hunt, L., Morris, J.C., Edwards, D., and Wilson, B.S. (1993). Driving performance in persons with mild senile dementia of the Alzheimer type. Journal of the American Geriatric, 41, 747-753. Jacoby, L.L., and Hay, J.F. (1998). Age-related deficits in memory: Theory and application. In M.A. Conway, S.E. Gathercole, and C. Cornoldi (Eds.), Theories of memory (Vol. 2 pp. 111-134). East Sussex, England: Psychology Press. Jette, A.M., and Branch, L.G. (1992). A ten-year follow-up of driving patterns among the community-dwelling elderly. Human Factors, 34, 25-31. Johnson, C.A., and Keltner, J.L. (1983). Incidence of visual field loss in 20,000 eyes and its relationship to driving performance. Archives of Ophthalmology, 101, 371-375. Keskinen, E., Ota, H., and Katila, E. (1998). Older drivers fail in intersections: Speed discrepancies between older and younger male drivers. Accident Analysis and Prevention, 30, 323-330. Ketcham, C.J., and Stelmach, G.E. (2004). Movement control in the older adult. In National Research Council, Technology for adaptive aging (pp. 64-92). Steering Committee for the Workshop on Technology for Adaptive Aging. R.W. Pew and S.B. Van Hemel (Eds.). Board on Behavioral, Cognitive, and Sensory Sciences. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press. Kline, D.W., Kline, T.J.B., Fozard, J.L., Kosnick, W., Schieber, F., and Sekuler, R. (1992). Vision, aging, and driving: The problems of older drivers. Journal of Gerontology: Psychological Sciences, 47, 27-34. Korteling, J.E. (1990). Perception-response speed and driving capabilities of brain-damaged and older drivers. Human Factors, 32, 95-108. Kosnick, W., Winslow, L., Kline, D., Rasinski, K., and Sekuler, R. (1988). Vision changes in daily life throughout adulthood. Journal of Gerontology, 43, 63-70. Kuhlman, K.A. (1993). Cervical range of motion in the elderly. Archives of Physical Medicine and Rehabilitation, 74, 1071-1079. Kweon, Y.J., and Kockelman, K.M. (2003). Overall injury risk to different drivers: Combining exposure, frequency and severity models. Accident Anaylsis and Prevention, 35, 441-450. LaMotte, J., Ridder, W., Yeung, K., and DeLanel, P. (2000). Effect of aftermarket automobile window tinting films on driver vision. Human Factors, 42, 327-336. Lerner, N.D. (1993). Brake reaction times of older and younger drivers. In Proceedings of the Human Factors Society 37th Annual Meeting (pp. 206-210). Santa Monica, CA: Human Factors Society. Li, G., Braver, E.R., and Chen, L.H. (2003). Fragility versus exessive crash involvement as determinants of high death rates per vehicle-mile of travel among older drivers. Accident Analysis and Prevention, 35, 227-235. Liu, Y. C. (2000). Effect of advanced traveler information system displays on younger and older drivers′ performance. Displays, 21, 161-168. Llaneras, R.E., Swezey, R.W., Brock, J.F., and Rogers, W.C. (1993). Human abilities and age-related changes in driving performance. Journal of the Washington Academy of Sciences, 83, 32-78. Malfetti, J.L., and Winter, D. (1986). Drivers 55 plus: Test your own performance. Washington, DC: AAA Foundation for Traffic Safety. Maltz, M., and Shinar, D. (1999). Eye movements of older and younger drivers. Human Factors, 41 , 15-25. Marottoli, R.A., Mendes de Leon, C.F., Glass, T.A., Williams, C.S., Cooney, L.M.Jr., Berkman, L.F., and Tinetti, M.E. (1997). Driving cessation and increased depressive symptoms: Prospective evidence from the New Haven EPESE (Established Populations for Epidemiological Studies of the Elderly). Journal of the American Geriatric Society, 45, 202-206.
OCR for page 280
Technology for Adaptive Aging Meyer, J., and Bitan, Y. (2002). Why better operators receive worse warnings. Human Factors, 44, 343-354. Mihal, W.L., and Barrett, G.V. (1976). Individual differences in perceptual information processing and their relation to automobile accident involvement. Journal of Applied Psychology, 61, 229-233. Mortimer, R.G., and Fell, J.C. (1989). Older drivers: Their night fatal crash involvement and risk. Accident Analysis and Prevention, 21, 273-282. Nelson, T.M., Evelyn, B., and Taylor, R. (1993). Experimental intercomparisons of younger and older drivers′ perceptions. International Journal of Aging and Human Development, 36, 239-253. Olson, P. (1988). Problems of nighttime visibility and glare for older drivers. In Society of Automotive Engineers, Effects of Aging on Driver Performance (SP-762, pp. 53-60). Warrendale, PA: Society of Automotive Engineers. Olson, P.L., and Sivak, M. (1984). Glare from automobile rear-vision mirrors. Human Factors, 26, 269-282. Olson, P.L., and Sivak, M. (1986). Perception-response time to unexpected roadway hazards. Human Factors, 28, 91-96. Owens, A., Helmers, G., and Sivak, M. (1993). Intelligent vehicle highway systems: A call for user-centered design. Ergonomics, 36, 363-369. Owsley, C., Sekuler, R., and Siemsen, D. (1983). Contrast sensitivity throughout adulthood. Vision Research, 23, 689-699. Owsley, C., and Sloane, M.E. (1987). Contrast sensitivity, acuity, and the perception of “real world” targets. British Journal of Ophthalmology, 71, 791-796. Planek, T.W. (1972). The aging driver in today′s traffic: A critical review. In T. W. Planek, W. A. Mann, and E. L. Wiener (Eds.), Aging and highway safety: The elderly in a mobile society (pp. 1-38). Chapel Hill, NC: North Carolina Symposium on Highway Safety. Planek, T.W. (1981). The effects of aging on driver abilities, accident experience, and licensing. In H.C. Foot, A.J. Chapman, and F.M. Wade (Eds.), Road safety: Research and practice (pp. 171-179). New York: Praeger. Planek, T.W., Condon, M.E., and Fowler, R.C. (1968). An investigation of the problems and opinions of aged drivers. Chicago: National Safety Council. Pulling, N.H., Wolf, S.P., Sturgis, D.R., Vaillancourt, D.R., and Dolliver, J.J. (1980). Head-light glare resistance and driver age. Human Factors, 22, 103-112. Retchin, S.M., Cox, J., Fox, M., and Irvin, L. (1988). Performance-based measurements among elderly drivers and non-drivers. Journal of the American Geriatric Society , 36, 813-819. Reuben, D.B., Stillman, R.A., and Traines, M. (1988). The aging driver. Journal of the American Geriatric Society, 36, 1135-1142. Rivara, F.P., Koepsell, T.D., Grossman, D.C., and Mock, C. (2000). Effectivencess of automatic shoulder belt systems in motor vehicle crashes. Journal of the American Medical Association, 283, 2826-2827. Rosenbloom, S. (1993). Transportation needs of the elderly population. Clinical Geriatric Medicine, 9, 297-310. Rothe, J.P. (1990). The safety of elderly drivers. London: Transaction. Sanders, M., Shaw, B., Nicholson, B., and Merritt, J. (1990). Evaluation of glare from center-high-mounted stop lights. Washington, DC: National Highway Traffic Safety Administration. Sarter, N.B., and Woods, D.D. (1995). How in the world did we ever get into that mode? Mode error and awareness in supervisory control. Human Factors, 37(1), 5-19.
OCR for page 281
Technology for Adaptive Aging Schaie, K.W. (2004). Cognitive aging. In National Research Council, Technology for adaptive aging (pp. 43-63). Steering Committee for the Workshop on Technology for Adaptive Aging. R.W. Pew and S.B. Van Hemel (Eds.). Board on Behavioral, Cognitive, and Sensory Sciences. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press. Sekuler, R., Kline, D., and Dismukes, K. (1982). Aging and visual function of military pilots: A review. Aviation, Space and Environmental Medicine, 53(8), 747-758. Sekuler, A.B., Bennett, P.J., and Mamelak, M. (2000). Effects of aging on the useful field of view. Experimental Aging Research, 26, 103-120. Shaheen, S.A., and Niemeier, D.A. (2001). Integrating vehicle design and human factors: Minimizing elderly driving constraints. Transportation Research Part C, 9, 155-174. Shinar, D., and Schieber, F. (1991). Visual requirements for safety and mobility of older drivers. Human Factors, 33, 507-519. Shinar, D., Schechtman, E., and Compton, R. (2001). Self-reports of safe driving behaviors in relation to sex, age, education and income in the U.S. adult driving population. Accident Analysis and Prevention, 33, 111-116. Sloane, M.E., Owlsey, C., and Alvarez, S.L. (1988). Aging, senile miosis and spatial contrast sensitivity at low luminance. Vision Research, 28, 1235-1246. Staplin, L., Lococo, K., Byington, S., and Harkey, D. (2001). Guidelines and recommendations to accommodate older drivers and pedestrians (Report No. FHWA-RD-01-051). Washington, DC: Federal Highway Administration. Stelmachowicz, P.G., Beauchaine, K.A., Kalberer, A., and Jesteadt, J. (1989). Normative thresholds in the 8- to 20-kHz range as a function of age. Journal of the Acoustical Society of America, 86, 1384-1391. Waller, P.F. (1991). The older driver. Human Factors, 33, 499-505. Wilde, G.J.S. (1988). Risk homeostasis theory and traffic accidents: Propositions, deductions and discussion of recent commentaries. Ergonomics, 31, 441-468. Wist, E.R., Schrauf, M., and Ehrenstein, W.H. (2000). Dynamic vision based on motion-contrast: Changes with age in adults. Experimental Brain Research, 134, 295-300. Wolf, E.W. (1960). Glare and age. Archives of Ophthalmology, 64, 502-514.
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Representative terms from entire chapter: