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Let's Get Real About Perception-Reaction Time

Marc Green

Imagine a trial about a botched surgical procedure. A surgery "expert" takes the stand to give his opinion. Upon examination, he says that no, he has never done any surgery himself. Nor has he ever studied the underlying scientific disciplines of anatomy or physiology. He says that he qualified, however, because he has read a book chapter on surgery by the noted physician Paulski Olsonovich and that he once took a 2-day chiropractor course that included a 2 hour discussion of surgery.

Would this surgery "expert" be allowed to testify? Not likely. But substitute the phrases "perception-reaction time" for "surgery," "vision" for "anatomy" and "cognition" for "physiology" and apparently, voila, the "expert" is qualified.

This probably explains why there is no area of "expert" opinion on road accidents that has more misinformation, more inappropriate use of canned numbers, more misunderstanding and, to use scientific terminology, more good old fashioned BS. Like the surgery expert above, most PRT "experts" have never actually done the task that they feel free to opine about. They have likely never measured a reaction time nor done any other behavioral scientific research and do not understand the complexities of scientific research and how much the methodological details determine what a scientific research study can actually tell you. In short, science, like surgery, is something you do and not just something you know. Moreover, most "experts" have never read the original source data and don't have the background to evaluate and interpret the studies if they did. Like the surgery expert, they have no training or experience in foundational scientific areas, human learning, memory, perception, decision-making, etc., to put the results into a broader behavioral context. They rely on secondary sources that omit many of the critical methodological details necessary to interpret the data.

Accident reconstruction is about physics - speeds, time, distances, etc. Accident reconstructionists, however, sometimes feel compelled to go beyond physics and to give an opinion on causality and accident avoidability. Here is where the trouble starts. The accident reconstructionist cannot give an avoidability opinion without providing a PRT value. This clearly goes beyond physics into the realm of human behavior, i .e. the field of psychology. With no scientific experience in psychology, however, the "expert" simply parrots a value that he has heard in a course, read in a secondary source book, pulled blindly from a computer program, etc. although he has no real understanding of where it comes from or what it means.

The article below, published in Collision 2009, demonstrates why such an approach is inadequate. It also shows why it is necessary to actually read the original source research and why a background in basic perception, cognition, etc. is necessary to understand what the research is really saying. Lastly, it shows why a background in having actually performed behavioral research is essential to opine on topics such as perception-reaction time.

Perception-Reaction Time: Is Olson & Sivak All You Need To Know?
Collision, (2009), 4, 88-95.

Accident reconstruction often requires a driver "perception-reaction time" (PRT), the interval between obstacle appearance and driver response initiation, I .e., the foot just touches the brake pedal and/or the hands just start turning the wheel. The PRT number is often a critical factor in establishing causation and subsequently in assigning blame.

There are two popular opinions and rationales for PRT. The first opinion is that the PRT is 1.5 seconds. The usual basis for 1.5 seconds is that the reconstructionist read it in an accident reconstruction book, learned it in a class or simply believes that it is the "accepted value." The second opinion is that the PRT is 1.1 (or 1.6 for the 95th percentile driver) based on "Olson." This opinion almost invariably means that the accident reconstructionist has read one of Olson's secondary sources, such as a chapter in Forensic Aspects of Driver Perception And Response (2003), or has simply seen it cited somewhere. In fact, the data stem from Olson & Sivak (1986), but Sivak remains anonymous because few have read the original research. For simplicity, I will simply refer to the data as "Olson," which is how they are usually referenced.

In either case, the rationale is inadequate. PRT is a very complex, situationally-dependent phenomenon that cannot be captured in the canned numbers that are so typically employed. Few who reconstruct accidents know much about the underlying science, where the numbers they quote originate, how they were obtained or what they really mean.

This article addresses the misuse of canned numbers (including the AASHTO 2.5 seconds and computer programs) in general but focuses primarily on the "Olson values." There are three main problems. First, every research study has limited generality because it is conduced under a specific set of conditions. An accident reconstructionist wishing to apply Olson, or any other research study, to a specific accident should understand the differences between the driving situation in the study and the specific accident. These differences will be smaller in some cases and larger in others, but there will be always differences. In some cases, Olson does not apply at all. In fact, the concept of PRT itself may not even apply. The discussions below of visibility and the tollbooth problem are examples.

Second, Olson is a perfectly fine study, but it is only one of perhaps 100+ driver PRT studies. These other studies provide data for other sets of conditions. Knowledge of these studies allows the reconstuctionist to better interpolate and extrapolate PRT for a broader set of conditions. However, there are no existing data for many common accident scenarios, so it is often impossible to determine a PRT with much precision. For example, there are almost no data for PRT at night, when accidents are frequent.

Third, assigning a reasonable PRT requires knowledge that goes even beyond the PRT literature. The issue of driver PRT cannot be snipped off from the larger topics such as perception, memory and learning and examined independently. This is especially true in accident scenarios where no PRT data exist. The assessment of older driver PRT, as discussed later, is a good example.

What Does Olson Actually Say?

In order to properly use Olson (or any other study) as a basis for estimating real world PRT's, the first step is to carefully analyze the experimental procedure. The second step is to determine the differences between research conditions and the accident conditions. The last step is to compensate for the differences. This is the most difficult problem.

A close reading of the Olson & Sivak study reveals the important methodological details. Olson tested two groups, a younger group of 49 drivers with an age range of 18-40 and an older group of 15 drivers with an age range of 50-84. The drivers were told only that they would be a study of driver behavior. They drove the test vehicle during daylight at about 27-31 mph with the experimenter sitting in the rear seat. The route took them over a rural road chosen so that there would be no distractions or possible hazards. After 10-15 minutes, the vehicle came to a hill. The experimenters had placed an obstacle, a 6" x 36" block of foam, in the left side of the lane directly in front of the driver. As the driver ascended the hill, the obstacle came into view. The sight distance to the obstacle was about 150 ft (46 meters), which translated to about 3.3-3.8 seconds time-to-collision (TTC). Instruments measured the time/location at which the driver released the accelerator and pressed the brake. In order to determine the PRT, the driver had to re-travel the route and tell the experimenter where he had first seen the obstacle. Olson then calculated the putative PRT time by measuring the distance from the location where the driver claimed to have first seen the obstacle to the location where he released the accelerator. PRT is this distance divided by speed.

Their results show a median PRT of about 1.1 second to press the brakes, with no difference between younger and older drivers. The 5th percentile drivers responded in .8 second while the 95th percentile driver responded in about 1.6 seconds. Olson has published these results in several later book chapters but without the methodological details.

First, the research was not exactly a study of PRT to an unexpected obstacle. The PRT determination required the driver to return to the scene and to say where he first saw the obstacle. At this point, the obstacle was expected and not a surprise.

This is a very unusual way to determine PRT. Usually, the PRT clock starts counting at the moment the signal is presented. It is unclear how accurately drivers could say where they were when they first saw the obstacle, so there are questions about what this study actually measured. However, one thing is certain: if the PRT clock had started counting at the moment when the driver first had a clear sightline to the obstacle, then the PRT would have been longer.

Reading the actual study reveals that the methodology was biased to produce short PRT's. There are many other procedural factors that further promoted very short PRT and that limit the study's generality for assigning PRT to real accidents.

1. Drivers were alerted. The term "alerted" unfortunately has two senses, which often creates confusion. Some authors use the term "alerted" to mean that the driver knew that there was an obstacle or even a particular obstacle ahead. In this sense, "alerted" means "expecting."

The other sense of "alert" refers to general arousal level. Drivers in the Olson study may not have been expecting a particular obstacle, but they certainly were alert and had a very high arousal level: they were participating in an experiment where their behavior was being monitored. There was even someone sitting in the back seat watching them. Moreover, they had been driving only 10-15 minutes before encountering the obstacle. Arousal level is related to driving time. The well-known phenomenon of vigilance decrement (Mackworth, 1948), a rapid decline in detection, typically starts within a half hour after task initiation. Further, research (Philip, Taillard, Klein, Sagaspe, Davies, Guilleminault, & Bioulac, 2003) has shown that time spent driving is a better predictor of decrease in driver performance than hours without sleep. The short driving time in the Olson study gives the test drivers a significant arousal advantage over a real driver who may have been on the road for an extended period.

In sum, the Olson drivers' high arousal level likely produced shorter PRT's than would occur under many normal driving scenarios. Olson was fully aware of this likelihood when he noted that "The subjects in this study were possibly alert relative to the general population of drivers" and that "the results are probably conservative (I. e., lower) to what would be found in the real world."

2 The testing occurred during the day. Olson does not specify the times of his testing, but it is likely that much of it was performed when drivers are at a moderate or high point on their "circadian rhythms," the normal 24-hour cycle of arousal that all people experience.

For most people, the arousal cycle has lows in the late afternoon and especially in the early morning hours. During these periods, many performance measures, such as accident rates and PRT are at their worst. One study (Wylie, Shultz, Miller, Mitler, & Mackie, 1996) of long haul truck drivers, for example, found that accidents correlated with time-of-day, early morning hours, but not with time-without-sleep. As a rule of thumb, in fact, it takes about 24 hours before people exhibit major sleep-deprivation losses.

Olson's drivers then likely had this additional arousal advantage over normal drivers in the early morning hours who are at a low point on the circadian rhythm. However, drivers who habitually work nights may have their rhythm "phase shifted," so the peaks and lows are at different times than normal drivers.

3. The obstacle appeared at the point of fixation. Olson placed the obstacle on the roadway at the crest of a hill and directly in front of the driver. It likely the exact location where the driver was fixating at the moment he reached the 46 meter sight distance. Location of an obstacle in the visual field can affect PRT. The optimal location is along the sightline at the point of fixation. Objects located here cast their images on the fovea, the retinal area of sharpest vision and the focus of attention. Olson placed the obstacle in the ideal visual field location.

In contrast, many collision scenarios involve a lane incursion where a vehicle or pedestrian approaches from the side. The obstacle then first appears in peripheral vision, where visual sensitivity is lower and attention is weaker. Moreover, when a viewer detects an object in peripheral vision, he most likely makes a saccadic eye movement toward it. The saccade requires time to move the eye plus a "dwell time" for the viewer to perceive the scene. The total saccade time about is 1/3 second in good day visibility. At night, the time is likely to be longer. The first saccade may miss the object, so viewers may have to make more than one saccade to "home in" on the target. When the new fixation requires a significant change in distance, such as shifting gaze from a mirror to an obstacle a few hundred feet down the road, the eye's change of accommodation and vergence and reacquisition can drive the time up to as long as a second (Travis, 1948.)

Lastly, if the target is more than 15o from the sightline, the driver will likely also have to make a head turn. Imagine a driver approaching an intersection or railroad track. He must turn his head to look one direction and then the other. It takes the driver 85th percentile driver .7 seconds to turn his head one way and then another 1 second to turn back the other (Long & Nitsch, 2008). This 1.7 seconds search time is on top of the PRT.

Visual field effects likely explain why Olson & Sivak found a 1.1 median PRT second while studies (Green, 2008a) using lane incursions typically find slower mean PRT's of about 1.5 seconds. (About .1 second of this difference is likely due to the difference between using median and mean as measures of central tendency.) Olson and Sivak's 95th percentile level was 1.8 seconds while the 95th percentile lane incursion PRT would be about 2.4 seconds, which is also near value used by AASHTO in geometric road design.

In sum, the Olson study optimized the PRT by placing the obstacle at the fixation point directly ahead of the driver. PRT will be longer when objects approach from the side as well as for other reasons discussed in subsequent sections.

4. The visibility conditions were good. Olson tested drivers in daylight and good visibility, so obstacle visibility was not a limiting factor in driver behavior. PRT is likely to increase at night and under other low visibility conditions.

In fact, when visibility is sufficiently low, the concept of PRT becomes irrelevant. After all, if the driver can't see the obstacle, then he can't respond to it. For example, assume that PRT for a pedestrian cutting left-to-right across the driver's path in good visibility conditions 1.5 seconds. In this case, driver first sees the target in peripheral vision. At night, the same pedestrian wearing dark clothing emerges from outside the driver's headlamp beams. When the pedestrian is far to the left, he receives little headlamp illumination and is invisible.

As pedestrian and vehicle approach, more headlamp illumination falls on the pedestrian. At some point, driver sees the pedestrian. In theory, the 1.5 seconds reaction time clock starts when the pedestrian first becomes visible in the periphery. But when is that? [Note: Olson didn't start timing PRT until the point at which the driver actually saw the obstacle.] In order to state a well-defined PRT, it would be necessary to know the exact point at which the pedestrian became visible. Even if this could be calculated, then it would still be necessary to specify the point where the pedestrian became conspicuous enough to draw attention and eye movement. This point is likely unknowable with great precision.

It is impossible to precisely estimate of the amount of slowing that will occur at night. However, some qualitative statements are possible. For the same pedestrian walking the same path, driver will have less time to avoid the collision at night because the pedestrian will likely have to be much closer in order to achieve the required visibility. The difference between day and night PRT will depend on factor such as street lighting, pedestrian clothing, background clutter, etc. A pedestrian wearing white clothing, for example, will often have better visibility and more approximate daylight visibility conditions than a pedestrian wearing dark clothing. However, there are exceptions (Green, 2008b).

Lastly, low visibility conditions also slow cognitive processing by creating uncertainty and by impairing recognition. I explain this further in the next section.

5. The obstacle appeared suddenly and unambiguously. Olson's drivers responded reflexively and did not have to think much because the situation was very clear. There was minimal cognitive processing, little uncertainty and no complexity, so PRT was very short. Moreover, the variability is very small because people are relatively uniform in their speed of making reflexive responses.

Situations that are more ambiguous or which develop more gradually require conscious thinking that slows response and drastically increases variability. For example, a driver traveling at night who approaches red and white dots (e g., the rear reflective tape on a truck) at some ill-defined distance must gain "situational awareness." He must identify the lights, determine the distance, search memory for previous similar experiences, decide what is going to happen if he responds and if he doesn't respond, choose a response, chose how hard to make the response, etc. (Green, 2008). Moreover he must consider his ability to control vehicle speed and direction.

The "tollbooth problem" (Fajen, & Devaney, 2006) provides a good example. Imagine a driver on a high-speed limited-access road traveling 65 mph. Suddenly, he sees a tollbooth up a head about a mile away and realizes that he will have to stop. Does he start braking immediately? The answer, of course, is no. Immediate braking wastes time arriving at the tollbooth. Rather, the driver has an internal model of his vehicle's braking capabilities and has learned the mount of time/distance needed to stop at a comfortable deceleration (or even at an uncomfortable deceleration.) Eventually he reaches the critical distance and begins to brake.

Theoretically, PRT would be the time between first sighting of the tollbooth and the pressure on the brake pedal. However, this is not a "reaction" in any conventional sense, so the concept of PRT doesn't really apply. The driver does not brake because there is no need to act. While the tollbooth problem might seem trivial, drivers face similar problems frequently. Up ahead, they see brake lights or unidentifiable objects, some dim dots of red and light. Should the driver brake immediately or wait until he is sure of the situation?

The point of the tollbooth example is that there is much more to PRT than perception. Drivers have a mental model of their ability to control their vehicle. The decision to act is always based partly on this mental model. The model's constituents are the "safe field of travel" and "stopping distance" (Gibson and Crooks, 1938). As a driver travels down the road, he is surrounded by obstacles, cars ahead, curbs and other barriers, pedestrians crossing the road, etc. which define a safe field of travel. This field changes constantly as new vehicles, pedestrians, etc. appear and change position.

The driver also has a mental stopping distance and steering model of his ability to brake/swerve his vehicle. This area is like a cocoon that surrounds the driver, providing a buffer zone with obstacles. Drivers believe that they can avoid collision with obstacles outside the cocoon. Ideally, the driver steers his vehicle through the cocoon's center, adjust speed and direction as the safe field of travel dynamically changes.

For this scheme to work, the driver must accurately assess object distance, speed and stopping distance (or time). However, distance perception is highly fallible, especially for small points of light, unfamiliar objects, foggy atmosphere and some other situations. Drivers are also poor at judging their own speed (Denton, 1980) and there are many situational factors that can cause them to underestimate how fast they are going, I e., fog and, low edge rates (Denton, 1980.) Drivers may also err in their belief of stopping ability when driving an unfamiliar vehicle or on wet or icy roads, sharp downgrades, dark conditions, etc.

Moreover, most drivers have likely had little or no experience making sudden stops, especially at high speeds. They base their cocoon size on their experiences stopping at lower speeds. Since stopping distance increases with the square of speed rather than linearly with speed, they are likely to underestimate the needed distance.

Even if the driver decides to respond, the choice of response is sometimes unclear. A driver heading toward a tractor-trailer blocking the road may find that there is no time to brake and that steering to the left will take him into oncoming traffic while steering to the right will put him in a ditch. This is termed an "avoidance-avoidance" conflict where the driver must choose among a set of bad alternatives. In such cases, PRT typically is very, very long. Often, the driver can't decide and fails to respond at all before collision. The common example is the underride accident where there is an unfortunate tendency to assume the driver's failure to respond because he had fallen asleep. In fact, the driver may have been caught in an avoidance-avoidance crisis.

6. The drivers were traveling slowly. Olson's drivers traveled at speeds ranging between 27-31 mph. At such slow speeds, sudden, abrupt braking or steering is less likely to cause an unrecoverable loss of control and to have dangerous consequences. In contrast, drivers traveling at 65 mph on a freeway may to hesitate to make sharp swerves or go to full-out braking because of potential control loss. They have to weigh the hazard of a collision with the hazard created by a loss of control that sends the vehicle over a median or guardrail, into other traffic or that initiates a side-skid and rollover. It is a type of avoidance-avoidance conflict that will likely lengthen PRT.

The fear of losing control is likely why drivers frequently resort to two-stage braking (Prynne & Martin, 1995). They initially push the brake pedal down part way and then monitor the situation, hoping that they can avoid the collision without and extreme response that risks loss of control. If collision is still likely, then the driver might go to the extreme maneuver.

7. The "older" drivers were not all old. Olson somewhat surprisingly failed to find any slowing in their "older drivers." This has caused many to claim that aging has no effect on PRT. However Olson's "old" group included drivers as young as age 50. While visual abilities start their decline in the early 40's, the significant effects do not begin until viewers enter the 60's. Olson does not give the ages of the individual drivers, so it is impossible to know the number who were in their 50's and early 60's where aging effects are small. However, it is very possible that Olson found no aging effect, in part, because their "older" drivers were too young.

Olson's task further likely minimized aging effects. As discussed elsewhere (Odom & Green, 2008), studies in the basic research literature have repeatedly found that impairments of aging (and other conditions such as distraction and alcohol use) are more pronounced when perceptual and cognitive abilities are taxed under conditions such as low visibility, uncertainty and complexity. The simple, virtually automatic avoidance task in the Olson study required little cognition. It was performed in good visibility, so perceptual abilities were not a limiting factor.

Moreover, research with older subjects always raises the issue of representativeness. Olson does not state how he recruited the subject drivers. However, most researchers would routinely screen their subjects, especially older ones, for any visual or other health problems. The older subject drivers are then likely to be healthier, more active, in better visual and cognitive condition than the population as a whole. Moreover, the drivers very likely agreed voluntarily to be in the study. Only the relatively healthy and "spry" senior is likely to volunteer for a research study. In sum, research on screened, self-selected older drivers likely overestimates abilities of the older population as a whole. In any event, the "older" group consisted of only 15 drivers.

This discussion of older driver PRT highlights the point that PRT assignment often requires knowledge of the general psychological literature and of scientific methodology. First, it is necessary to actually read Olson's study in order to learn that he placed drivers as young as age 50 in the old category. This is not a detail that is ever mentioned in secondary sources. Second, the effects of complexity and uncertainty on the size of age-related deficits do not appear anywhere in the driver PRT literature or any computerized PRT program. It is basic science published in basic science sources. Third, the important issue of representativeness would not be apparent to anyone who was not intimately familiar with the way scientific research is conducted.


Accident reconstructionists should take the Olson results for what they are - the fastest that a driver can avoid an "unexpected" obstacle in highly optimized conditions. Any deviation, such as low visibility, peripheral visual field location, complexity or uncertainty is almost certain to increase PRT. The finding that there is no loss of PRT with age is not generalizable and depends on specific conditions. Lastly, real drivers are unlikely to be as alert as the drivers in the study. Lower arousal level may produce longer PRT's, especially at low points in the circadian rhythm and after driving for extended periods.

Each of the 7 factors described above would doubtless add time to Olson's optimized 1.1/1.8 seconds PRT but assigning a precise number is difficult. I have sometimes seen opinions where someone arbitrarily adds 0.5 or 1 to compensate for nighttime or complex conditions. While essentially guesswork, these estimates are doubtless closer to reality than the simple, foveal, daytime, high-arousal values taken at face value. However, there are few if any PRT data for many of these conditions. This is why it is so important to have general knowledge about perception, attention and memory to fall back upon. They are often the only available guides.

Despite the lack of data for many situations, however, I can draw two practical conclusions about assigning a driver PRT. First, estimates will often cover a very broad range because precision is impossible. Second, estimates will often be very high - much higher than are normally seen. Low visibility and violated expectation make the obstacle disappear and even a moment's hesitation to search or to think or to decide upon response can eat up seconds. The AASHO Redbook's view of PRT written in 1973 remains true today:

"Whenever the driver is confronted with a complex traffic or highway situation and is required to make choices, judgments, and decisions, his response time may increase to 2, 3 or even 5 seconds" (p. 278).


American Association of State Highway Officials (1973). A Policy on Design of Urban Highways and Arterial Streets. Washington, DC: AASHO.

Denton G. (1980). The influence of visual pattern on perceived speed. Perception, 9, 393-402.

Fajen, B. R. & Devaney, M. C. (2006). Learning to control collisions: The role of perceptual attunement and action boundaries. Journal of Experimental Psychology: Human Perception and Performance, 32(3), 300-313.

Gibson, J.J. & Crooks, L.E. (1938). A theoretical field-analysis of automobile driving. American Journal of Psychology, 51, 453-471.

Green, M. (2008a) "How long does it take to stop?" Methodological Analysis of Driver Perception-Brake Times. In M. Green, B. Abrams, M. Allen,
Forensic Vision With Application To Highway Safety, 379-406. Tucson: Lawyers & Judges Publishing.

Green, M. (2008b) "Pedestrian accident analysis" Methodological Analysis of Driver Perception-Brake Times. In M. Green, B. Abrams, M. Allen, Forensic Vision With Application To Highway Safety, 329-348. Tucson: Lawyers & Judges Publishing.

Long, G. & Nitsch, A. (2008). Effect of dead turning on driver perception-reaction time at passive railroad crossings. Transportation Research board 2007 Meeting CD.

Mackworth NH (1948). The breakdown of vigilance during prolonged visual search. Quarterly Journal of Experimental Psychology, 1, 5-61.

Odom, J. & Green, M. (2008). Aging Vision. In M. Green, B. Abrams, M. Allen, Forensic Vision With Application To Highway Safety. Tucson: Lawyers & Judges Publishing.

Olson, P. & Farber, E. (2003). Forensic Aspects of Driver Perception and Response. Tucson: Lawyers & Judges Publishing.

Olson, P.L. & Sivak, M. (1986) Perception-response time to unexpected roadway hazards. Human Factors, 28, 96-99.

Philip P., Taillard J., Klein E., Sagaspe P., Charles A., Davies W., Guilleminault C., & Bioulac, B. (2003). Effect of fatigue on performance measured by a driving simulator in automobile drivers. Journal of Psychosomatic Research, 55, 197-200.

Prynne, K. and P. Martin 1995. Braking behavior in emergencies. SAE Technical Paper 950969.

Travis, R. (1948). Measurement of accommodation and convergence time as part of a complex visual adjustment. Journal of Experimental Psychology, 38, 395-403.

Wylie, C. D. Shultz, T. Miller, J. C. Mitler, M. M. and Mackie, R. R. (1996). Commercial motor vehicle driver fatigue and alertness study: Project report. Technical Report FHWAMC- 97-002, Federal Highway Administration, Washington DC.

Other Topics
Personal Injury: Road Accidents
  • Is The Moth-Effect Real?
  • Human Error in Road Accidents
  • Reaction Time
  • Let's Get Real About Perception-Reaction Time
  • Why PRT Is Not Like Gravity
  • Vision in Older Drivers
  • Weather and Accidents: Rain & Fog
  • Accidents At Rail-Highway Crossings
  • Seeing Pedestrians At Night
  • Underride Accidents
  • Rear End Collision: Looming
  • Night Vision
  • Distracted Pedestrians
  • Failure To See
  • Perception-Reaction Time (PRT) Programs
  • Twilight (3.3 lux) As A visibility Criterion
  • Human Error And Fault Tolerance
  • Junk Science Meets Impaired Drivers
  • Personal Injury: Warnings & Product Defects
  • Warnings and Warning Labels
  • Warning Effectiveness Checklist
  • The Psychology of Warnings
  • Drugs, Adverse Effects & Warnings
  • Are Warnings Effective?
  • Human Error Vs. Design Error
  • Product Misuse And "Affordances"
  • Safety Hierarchy: Design Vs. Warning
  • Thinking Like A Human Factors Expert
  • Personal Injury: Other
  • Diving Accidents in Pools
  • Falls Down Steps
  • Medical Error
  • Computer & Medical Error
  • Nursing Error
  • Criminal & Police
  • Errors in Eyewitness Identifications
  • Perceptual Error in Police Shootings
  • Eyewitness Memory Is Unreliable
  • Human Factors In Forensic Evidence
  • Intellectual Property
  • "Any Fool Can See The Trademarks Are Different"
  • Measuring Confusion For Intellectual Property
  • Color in Trademark and Tradedress Disputes
  • Color Functionality: A Case Example
  • Forensic Human Factors
  • Seeing Color
  • Determining Visibility
  • "Inattentional Blindness" & Conspicuity
  • Computer animation has perceptual limitations
  • Photographs vs. Reality
  • The Six Laws Of Attention
  • What is "inattention?"

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