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Thread: [Academic] Survey --- Risk Perception and the Driving Environment

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    [Academic] Survey --- Risk Perception and the Driving Environment

    I am conducting a thesis study exploring drivers’ perception of road environments. Your responses would be greatly appreciated, and could contribute to improving our knowledge of traffic safety. The survey is intentionally brief, and should take no more than 10 minutes of your time. Participation is entirely voluntary.


    Begin the survey by clicking the following link:


    Survey Link: https://uni.co1.qualtrics.com/jfe/fo...Z3&Q_CHL=email

    Thank you for your participation!


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    Several weeks ago we asked for your participation in a survey regarding traffic safety and risk perception. Today, we have returned to share a summary of the thesis, and the key results.

    Supplements:
    Link to Figures
    Link to References
    Link to Selected Intersection Case Studies

    Introduction:
    We are consciously, or cognitively, aware that driving poses great risks to ourselves and others, with consequences ranging from property damage, to injury and death. However, once we actually take the wheel, we are more likely reliant on our affective perceptions - our emotions, intuitions, and experiences - to guide our risk perception. Although practice and experience can improve our perception and our responses, the misperception of risk can aggravate the development of a hazardous situation.

    To increase our understanding of risk perception in the automotive environment, this study was designed to record participants’ perceptions of road risk from roadway geometrics visible in still photography (controlling for variables such as time of day, weather, and traffic). These records enabled a comparative analysis between the perception of risk, and the underlying crash histories of photographed road sites.

    Literature:
    Our perception of risk has been shown to be highly subjective (Slovic, 1992). Even within an individual, there is often a striking divergence between our cognitive, or calculated, estimations of risk and our affective perception of risk (Loewenstein, Weber, Hsee, & Welch, 2001; Kahneman, 2011). We tackle tens, if not hundreds, of small risk decisions everyday without much thought, suggesting that our affective perceptions are predominant (Keller, Siegrist, & Gutscher, 2006). Additional limitations can increase our reliance on our affective perception, such as having limited decision-making time (Slovic & Peters, 2006), a lack of complete knowledge (Kuklinski, Metlay, & Kay, 1982), or from experiencing cognitive overload (Brookhuis & De Waard, 2010). This understanding of risk perception is critical for driver safety.


    As drivers, our affective perceptions of risk are vulnerable to potential bias. We often underestimate our own risk due to familiarity, overexposure, and complacency (Rundmo, Nordfjærn, Iversen, Oltedal, & Jørgensen, 2011), due to the perceived controllability of the task (McKenna, 1993), and due to the voluntariness of driving (Fischhoff, Slovic, Lichtenstein, Read, & Combs, 1978; Starr, 1969). We often compound our underestimation of risk by overestimating our abilities (Wohleber & Matthews, 2016), and the capabilities of our vehicles (Svenson & Eriksson, 2017). Taken together, these biases may induce risk-taking behaviors, including engagement in secondary tasks such as eating or handling a cellphone (Li, Gkritza, & Albrecht, 2014).

    Safer driving requires a conscious effort. Calls for increased law enforcement, safety engineering, and technological innovation often prove prohibitively expensive (Elvik, 1999). Even when such interventions are afforded, the results are often less than predicted (Peltzman, 1975; Wilde, 2001). Although the Peltzman Effect has garnered robust empirical support, it does not consider the many biases underlying our perception of risk, or our potential lack of knowledge of such risk. This research addresses this by evaluating correlations between drivers’ perceptions of risk at specific road sites and the crash histories of those sites.


    Methods:
    For brevity, we will omit the lengthy discussion of the geospatial analysis of statewide crash records. It suffices to say, there are subjectivities in the way such data are handled, however, this research followed best practices set forth by various states’ Department of Transportation. The result of these procedures was tabular data for every intersection in a small, but urban, Iowan city (Cedar Falls, Iowa). Intersections were ranked in different ways, including crash frequencies, average crash severity, crash rate, severity-rate, and a weighted measure of frequency and severity - the equivalent-property-damage-only, or EPDO-rate. The use of the rate calculation is especially important for estimating personal risk at roadway sites (Hauer, 1996).

    We can also skim over the discussion of the survey -- many of you having been participants. To recap, the survey included very limited demographic data, including questions about miles driven per year, U.S. residency, and driver ability. There was also an eight-item Likert-response modeled after the Brief Sensation Seeking Scale (Fan et al., 2014). The bulk of the survey was comprised of 23 images with a response scale for perceived risk ranging from “Far Below Average” to “Far Above Average” with six selectable stops. The first 3 images were presented as a warmup, the remaining 20 images depicted 9 different intersections (2 perpendicular views for 8 intersections, 4 views for 1 intersection).

    Results:
    The survey link was clicked by 433 individuals, though only 300 participants completed the survey. Although this is a low completion rate (69.3%) for traditional survey methods, it is in line with expectations for a modern digital survey (Shatz, 2016). The highest completion rate among surveyed communities was from the readers of the NICOClub forums; the largest number of participants was recruited from Reddit’s r/motorcycles (the second largest number of participants was from ADVrider.com).

    The question, “Please rate your driving ability” was used to replicate findings from the literature, and to assess the validity of survey responses. Of the 7 selectable responses, from “Far Below Average” to “Far Above Average”, the overwhelming majority of respondents chose the 6th stop (“Above Average”). Given an equal distribution, this would imply most respondents believe themselves to be better than 85% of other drivers, assuming a standard normal distribution, this would imply respondents believe themselves better than 97.7% of drivers. (See Figure 1)

    Correlations between respondents’ perception of risk and the actual crash histories of survey image sites were statistically insignificant. Statistical insignificance should not be grounds for dismissing the results too hastily, however (Hauer, 2004). The correlation coefficients did demonstrate consistency. A positive correlation coefficient was found between perceptions of risk and crash frequency. Negative correlation coefficients were observed between perceptions and average severity, as well as for crash rate, severity rate, and EPDO-rate. (See Figure 2)

    Discussion:
    Our susceptibility to the “Above Average Effect” is just one small example of the biases that undermine our risk perception, and in turn impact our driving behaviors. Undoubtedly, some of the survey respondents are better than the average driver through their training, practice, and experience; however, this does not excuse us from becoming overconfident or complacent. Some of the best drivers in the world have met their end while at the wheel.

    The (lack of) results from the correlations suggests that our estimates of risk are approximately random (See Figure 3). Despite the absence of traffic or weather in the still photography used, there are definitive “crash hotspots” in our road system; furthermore, single-vehicle accidents are not an uncommon occurrence at such hotspots.

    The correlation coefficients suggest that our perception of risk increases when crash frequency increases; since higher crash frequencies usually follow higher-traffic, a simple explanation could be that we perceive larger, higher-traffic intersections to be more risky.


    The consistency of the negative relationship associated with the crash-rate calculations suggests that we underestimate our risk in relation to traffic volume. We might perceive busier roads to be more dangerous (and also hear about more crashes on these roads), but we are often times safer on such roads than on the residential roads in our own neighborhoods.
    Conclusion:
    The goal of this research was to promote safer driving. Regardless of the results, there is a hope that, simply by having participated in or read about this research, that you will become a more conscious and conscientious driver. “Vision Zero” is not strictly the responsibility of the engineers, the law officers, or the emergency medical teams; it is the responsibility of Everyone (IaDOT, 2013).


    * This work is Copyright by Dane Atkins, 2018.

  3. #3
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    The question, “Please rate your driving ability” was used to replicate findings from the literature, and to assess the validity of survey responses. Of the 7 selectable responses, from “Far Below Average” to “Far Above Average”, the overwhelming majority of respondents chose the 6th stop (“Above Average”). Given an equal distribution, this would imply most respondents believe themselves to be better than 85% of other drivers, assuming a standard normal distribution, this would imply respondents believe themselves better than 97.7% of drivers. (See Figure 1)

    Of course. All the tailgating texters, left lane dawdlers and those unable to smoothly merge, modulate speed and have no conception of driving etiquette comprise only 2.3% of drivers.

    If you can leave two black stripes from the exit of one corner to the braking zone of the next, you have enough horsepower. - Mark Donohue

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    Quote Originally Posted by ross1 View Post
    The question, “Please rate your driving ability” was used to replicate findings from the literature, and to assess the validity of survey responses. Of the 7 selectable responses, from “Far Below Average” to “Far Above Average”, the overwhelming majority of respondents chose the 6th stop (“Above Average”). Given an equal distribution, this would imply most respondents believe themselves to be better than 85% of other drivers, assuming a standard normal distribution, this would imply respondents believe themselves better than 97.7% of drivers. (See Figure 1)

    Of course. All the tailgating texters, left lane dawdlers and those unable to smoothly merge, modulate speed and have no conception of driving etiquette comprise only 2.3% of drivers.
    I'm even better with a coupla drinks under my belt!

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    If you can leave two black stripes from the exit of one corner to the braking zone of the next, you have enough horsepower. - Mark Donohue

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