A simple way to study driver distraction
This blog describes a simple way to study driver distraction.
There are several methods for studying driver distraction. Some require expensive simulators or instrumented vehicles and are cost prohibitive. However, an inexpensive yet effective method uses naturalistic observation. This involves watching people to see if using a cell phone changes how they behave.
What follows is a brief description of how to perform a study using naturalistic observation. For those not interested in learning how to do this, feel free to skip to the next blog (sorry about that...). But if you do try your hand at naturalistic observation, send me a note about what you find. I'll compile the data and report back later on.
So, here are the instructions for naturalistic observation (of course, feel free to modify your observations to fit your interest).
- Locate two or three 4-way intersections with stop signs in all directions (e.g., intersections with crosswalks near an elementary school or shopping center are a good choice).
- Consult with your local police department to learn the definition of a legal stop at the intersection and what is a violation of the law.
- Plan to spend an hour or two at each intersection on different days (select times when there is moderate traffic on the road). This means you might spend up to six hours over a few days collecting data. As a general rule, more observations will give you more reliable results.
- As drivers approach the intersection, determine a) if they are on the phone or not, and b) if they come to a legal stop at the intersection or not. The more accurate your observations, the more precise your data.
Enter the observed data into a 2 x 2 table like the one below. Each driver will be an observation in the table. For example, if a driver was on the cell phone and failed to make a legal stop, add one to the upper left cell.
Traffic Violation No Traffic Violation On Cell Phone Not on Cell Phone
- Now that you've collected your data, you need to determine if any differences are meaningful. You can analyze your data using a logistic regression calculator. Enter the data from your table into the data entry section and hit calculate1.
- Scroll down to the summary and find the log odds ratio -- the log odds ratio is referred to as exp(slope) in the summary. The log odds ratio tells you the likelihood of running a stop sign for drivers using a cell phone compared to drivers not on the phone.
- Also record the Chi-square value and the associated probability (a p < 0.05 is considered statistically significant in scientific research).
If you find a log odds ratio greater than 1.0 with a Chi-square value that is associated with a probability of p<.05, then that means that drivers on a cell phone are significantly more likely to fail to stop at the intersection than drivers who are not on the phone.A few years ago, my son Kyle and his friend Henrik used this procedure and collected the following data:
Traffic Violation No Traffic Violation On Cell Phone 82 28 Not on Cell Phone 352 1286
Kyle and Henrik entered their data into the logistic regression calculator like this:
0 82 28
1 352 1286
This resulted in a log odds ratio of 10.7, with a Chi-square of 129.8, and a p <.01.
So what do Kyle and Henrik's results mean?
Their results indicate that the likelihood of failing to stop at the intersection was significantly higher for drivers using their cell phone. This is a whopping effect!
Considering that these observations were made at intersections near an elementary school, there are obvious safety implications.