For each race and gender comparison, drivers aged have rates far higher than those for drivers aged 50 or older by factors between 3. The number of traffic tickets a driver gets in a year reflects more than just the propensity to violate traffic law. Drivers in each of the 12 cells in Table travel different distances at different times, and therefore necessarily have different probabilities of being observed by police.
What is a more controversial and difficult issue is that all individuals may not have identical probabilities of receiving tickets even for identical behavior in identical circumstances. The probability that a police officer issues a ticket might be prejudicially affected by the gender, age, or race of the driver. The data alone cannot provide information on the extent to which sexism, ageism, or racism are present.
The agreement of the gender and age dependence of ticket rates with casualty rates supports that a major reason why drivers receive tickets is that their behavior in traffic increases the risk that they will be in a fatal crash. However, contributions from other factors cannot be ruled out.
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Among young aged drivers, African Americans of both genders have lower citation rates than white drivers of the same gender and age. This may reflect less availability of vehicles, less driving, or perhaps young African Americans are driving more carefully because they believe that police are prejudicially targeting them.
Such a belief, whether true or not, would save lives of those who believed it. The higher rates for African Americans in the other age groups may reflect a largely universal socioeconomic effect in which risk taking in a host of activities declines with increasing affluence. Many results based on these variables have been presented in earlier chapters.
Mortality from the National Center for Health Statistics contains more detailed information on those dying from any cause. By linking this data set with FARS, together with information on distance of travel from the Nationwide Personal Transportation Survey, fatality rates for the same distance of travel were estimated for factors in addition to those included in FARS.
The study examined occupant fatality risks for children aged and teenagers aged years , and compared the risks for Hispanics, non-Hispanic blacks, and non-Hispanic whites. For each billion vehicle miles of travel, 14 non-Hispanic black children were killed, compared to 8 Hispanics, and 5 non-Hispanic whites. For teenagers the rates were 45 for Hispanics, 34 for non-Hispanic blacks, and 30 for non-Hispanic whites.
Unquestionably, socioeconomic status makes a large contribution to any such differences, as well as to the differences in Table However, a later study of adult risk that does incorporate a measure of socioeconomic status concludes that this variable cannot account for all of the differences. Self-reported behavior in questionnaires Questionnaire, or survey, studies have the advantage of producing information on many factors for large numbers of respondents. A disadvantage is that self-reports of behavior may depart substantially from actual behavior, particularly if the behavior is considered to be socially undesirable or is illegal.
Even in the unlikely event that drivers knew how often they speeded, they might not respond truthfully. Comparing self-reports to observed behavior shows that speeders tend to underreport their speeding. Still, responses reflect some mix of true speeds, the responder's ability to estimate true speeds, and the self-image the responder wishes to convey. These are all factors relevant to safety.
Responses were obtained from 1, licensed drivers in Scotland in a minute in-home interview.
Table shows the percent characterized as speeders, defined as reporting that they had been stopped by the police for speeding during their driving career, or had been flashed by a speed camera in the previous three years the driver is aware when a flash photograph, indicating speeding, is taken. At all ages, male rates exceed female rates by factors between 1. The data do not provide information on speeding versus age because, as drivers age, their life-long exposure to the risk of a speeding offense can only increase.
The same survey asked drivers how they would adjust their speed under various driving conditions.
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Differences reported to be statistically significant are listed in Table , again demonstrating that males are associated with riskier behavior. The greater tendency of males to slow down in light rain could possibly reflect greater appreciation of the relationship between braking and wet roadways, or more likely driving closer to the margin on dry roads.
How Scottish drivers of different genders indicated they would respond to changed conditions. Observational studies Driver propensity to take risk, as indicated by chosen speed or by following headway gap between a driver's vehicle and the one in front , was measured in a series of observational studies in which oncoming cars were photographed from freeway overpasses. A photographed driver judged not to differ in age or sex from the registered owner was assumed to be the owner.
The studies found that speed on a rural two-lane road decreased with increasing driver age. The proportion of vehicles observed following the vehicle in front at dangerously short headways tailgating declined with increasing driver age.
The risk taking behaviors of speeding and tailgating were more prevalent among male drivers. These results are summarized in more detail elsewhere.
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The behavior of individuals within a given demographic category vary more than differences between demographic categories - there are many young males who drive at lower risk than many older females. There has been much effort to attempt to explain such variation in terms of personality. The first study indicating "we drive as we live" One of the earliest studies to examine the relationship between crash involvement and personality was published in Characteristics of 96 Toronto taxi drivers who had four or more crashes were compared to those of taxi drivers with no crashes.
The two groups, matched in age and driving experience, provided the results in Table Frequency of contact with social agencies by 96 Toronto taxi drivers with four or more crashes compared to with no crashes. The authors conclude: It would appear that the driving hazards and the high accident record are simply one manifestation of a method of living that has been demonstrated in their personal lives. Truly it may be said that a man drives as he lives. If his personal life is marked by caution, tolerance, foresight, and consideration for others, then he would drive in the same manner.
If his personal life is devoid of these desirable characteristics then his driving will be characterized by aggressiveness, and over a long period of time he will have a much higher accident rate than his stable companion. A major deficiency of the study is that much of the interpretation is based on psychiatric-type interviews conducted while riding in the taxis.
This procedure is subjective in nature, and given the extreme differences between the groups of drivers, it was not possible for the interviewer to remain unaware of the group to which the driver most likely belonged, thus raising the possibility of bias. The comparison is between extremes some of the drivers with high crash rates verged on the psychopathic , so it could be argued that the results may not necessarily be applicable to a more moderate degree of crash over involvement.
The profiles were produced by conducting in-depth interviews with family members and associates of the deceased. These were compared to profiles of 25 control subjects selected from the same voter precincts in which the deceased had lived, and matched in such characteristics as age all were males. Many criticisms of this study are possible. The information gathering processes were necessarily quite different for the deceased and control subjects, and the sample sizes were small. However, the differences found are much larger than any that appear likely to be due to possible biases in the technique.
Even the few abnormal personalities among the control population were found to be less deviant, and to have more adequate coping mechanisms that helped compensate for their psychiatric liability. One problem is that crash rates depend strongly on factors, such as gender, age and alcohol use, so that any study of personality factors must control for these. This may require large sample sizes. Yet measures of personality are not available in large data sets, but must instead be determined by the investigators by, for example, administering one of many available personality instruments as components of questionnaire studies.
Large compared to normal departures from the norm. The large effects of personality discussed above were measured by comparing extreme cases, such as taxi drivers with four or more crashes to those with zero, or fatally injured drivers to typical drivers. Since the comparison is between such extremes, it could be argued that the results may not be valid when interpolated to the more moderate degrees of over involvement that are of such importance in traffic safety.
This problem is parallel to the dose-response problem in toxicology. Does a large, easily measured, deleterious effect associated with a massive dose of some substance support the inference that one tenth of the dose would still produce some deleterious effect, perhaps about one tenth the effect of the large dose? Or is there some threshold below which the substance produces no deleterious effect? Given that most crashes involve drivers not as far from the average as those in the studies discussed, it is important to know whether moderate variations within the normal ranges of behavior can explain variations in crash rates.
As in the toxicology case, the smaller the dose, the more difficult it is to measure the response, but the more people are involved. Above-average crash risks are still small. There are methodological problems inherent in comparing those with moderately above-average crash rates to those with below-average crash rates.
To illustrate, assume a hypothetical population of identical drivers each with the same average crash rate of 0. Column 4 of Table p.kinun-houju.com/wp-content/fuzuhuvi/2612.php
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Suppose one compared driver characteristics of groups of safe zero-crash and risky two or more crashes drivers. Because membership of either group is determined by the pure randomness of a Poisson process, driver characteristics in each group are identical. Such a finding could be misinterpreted to conclude falsely that drivers who crash do not differ from those who do not crash.
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Now suppose there is a group of genuine risky drivers who are twice as likely as average drivers to crash that is, their crash rate is 0. Likewise, any group of subjects selected on the basis of having no observed crashes will contain many high risk drivers, and any group selected on the basis of having two or more observed crashes will contain some low risk drivers. The high and low risk groups of subjects will indeed contain drivers with higher and lower average propensities to crash, but the difference will be but a fraction of the real factor of four difference.
This makes it more difficult to detect relationships based on comparing high and low risk drivers, and the effects measured in any relationships that are found will systematically underestimate the magnitude of the true effects by substantial amounts. There does not appear to be a way out of this dilemma. Statistical theory, together with various assumptions, can be used to estimate the most likely real effect from an observed difference, but as the observed difference is small even when the real difference is large, the estimate will lack precision.
One cannot use very long periods to accumulate larger numbers of crashes because crash risk, which depends so strongly on age, is not stable over long periods. Reviews13, mention studies that report that higher risk drivers are less mature, less intellectually oriented, less academically successful, less interested in aesthetic matters, lower in aspiration, poorer in attitudes toward the law, and generally less well adjusted socially.
They are more emotionally unstable, unhappy, asocial, anti-social, impulsive, and under stress.
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They are more likely to smoke and to have personality disorders and paranoid tendencies. They are more likely to have family histories, and current family relationships, reflecting higher degrees of disruption and conflict. More recent studies augment and extend these findings. Higher crash rates are related to high hostility in combination with poor self-esteem, high job stress, and self-reported tendencies to speed and to disregard traffic rules. Type-A personality drivers self-reported being involved in more crashes and displaying more aggression on the road than average drivers.
Survey respondents reacting to behavior of other drivers in different scenarios were more likely to attribute hostility to male drivers. Given all the correlates that have been identified with over involvement in crashes, it is not surprising that over involvement in crashes relates to a whole host of other unhealthy behaviors, such as smoking. Credit histories have been shown to be good predictors of crash involvement. The auto-insurance industry is using the credit ratings available in large data files to set premiums.
Emotional stress. Personality denotes stable character traits that do not change over short time periods.
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