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Sponsored by: |
Ontario Ministry of
Transportation
The Honourable David Turnbull,
Minister |
in cooperation
with: |
Transportation Research
Board |
in partnership with: |
The Traffic Safety Village at Drivers.com | | |
Spatial and temporal analyses of the variations in aggressive driving and road rage behaviors observed and reported on San Diego freeways
Sheila Sarkar, Alanna Martineau, Mohammad Emami, Mohammad Khatib, & Karen Wallace--San Diego State University
ABSTRACT
California Highway Patrol (CHP) in San Diego County receives cell phone calls reporting unsafe driving. The content of the calls varies, with drivers complaining about speeding cars driving over 100 miles per hour (estimated speed), other drivers weaving and cutting off or tailgating. In some cases, the driving conditions were even more volatile with drivers describing harassment, assaults with a weapon, running other vehicles off the road and so on. There were about 1987 reported incidents from the freeways of San Diego for the months of April, June and September 1998. The information received by the dispatchers was tabulated as shown in Table 1 and then put into five different categories: Aggressive Driving 1, 2, and 3, Speeding Alone and Road Rage based on definitions developed by the authors. Analyses indicated that 24.6% of the calls were for Aggressive Driving 1 (speeding and some other behavior); Aggressive Driving 2 (weaving and cutting) was reported most frequently (27.1% of all the calls), about 12.5% of the calls were for Aggressive Driving 3 (tailgating); Speeding Alone calls comprised 19.8% of the total, and the rest were for Road Rage (16.1%).
Of the 1987 calls, 33% were generated on Interstate 5, the busiest and longest in the county, followed by Interstate 15 which accounted for 22% of the calls. The reason for the high number of calls can be attributed to high Average Daily Traffic volumes at each interchange (over 130,000 vehicles) and lengths (Interstate 5 with 79 miles and Interstate 15 with 94 miles within San Diego county). Likewise, Interstate 8 seemed to have a lower number of calls than expected because the urban portion of the freeway is less than 17 miles with volumes of 180,000 per day for each interchange while the remaining distance had less than 30,000 vehicles at each interchange. This was further corroborated and both volume, r (10) = .69, p < .029, and length, r (10) = .77, p < .001, were robustly correlated with the number of phone reports per freeway. Additionally, chi-square tests indicated that the time of the day and day of the week influenced the type and number of calls received.
This paper has been accepted for publication in a forthcoming issue of the Transportation Research Record.
Read the full paper: (PDF format only)
READERS' COMMENTS:
Which other behaviour was most commonly associated with speeding in the Aggressive Driving 1 category? This category is especially useful because it suggests that we should be looking at speeding in context i.e. driving at high speeds results in more frequent traffic conflicts and leads to other aggressive maneuvers on the road.
For the "road rage" category, do have a further breakdown of the incidence of specific behaviours. I suspect that the majority of incidents might involve relatively less serious behaviours such as "flashing headlights" or "horn honking." What percentage of these behaviours involved clear criminal acts such as "threatening others with a weapon", "firing shots", "hitting vehicles with objects" or "trying to run another vehicle off the road." At present, you are probably, the only researchers who have data on actual observed behaviours, and such a breakdown might help put the "road rage" issue in perspective.
I commend the authors of the paper for their innovative approach to data collection and data analysis. The following questions arise:
1. Have you considered how you would validate your estimates of the percentage of aggressive driving events reported to the Highway Patrol call center?
2. Have you considered alternative methodologies for the collection of observational data related to aggressive driving?
Moderator
Thank you for your comments.
In regards to the first question.
1. Have you considered how you would validate your estimates of the percentage of aggressive driving events reported to the Highway Patrol call center?
We used the 911 calls reporting these events. We have been tracking these for the past three years to see what the trends are.
2. Have you considered alternative methodologies for the collection of observational data related to aggressive driving?
We haven't tried other methods but we have geocoded the data to identify spatial patterns using GIS. The paper will be presented at TRB next year.
Dr. Tasca,
Here's the info.
Which other behaviour was most commonly associated with speeding in the Aggressive Driving 1 category? This category is especially useful because it suggests that we should be looking at speeding in context i.e. driving at high speeds results in more frequent traffic conflicts and leads to other aggressive maneuvers on the road.
Response:We found that speeding was closely associated with weaving and cutting. This is very interesting and kind of make sense why callers feel threatened.
For the "road rage" category, do have a further breakdown of the incidence of specific behaviours. I suspect that the majority of incidents might involve relatively less serious behaviours such as "flashing headlights" or "horn honking."
Response: You are right. Also Rude gestures showed up as prominent way to express anger.
What percentage of these behaviours involved clear criminal acts such as "threatening others with a weapon", "firing shots", "hitting vehicles with objects" or "trying to run another vehicle off the road."
Response: Less than 10 percent. But we are working with 1999 and 2000 now and things might get worse.
At present, you are probably, the only researchers who have data on actual observed behaviours, and such a breakdown might help put the "road rage" issue in perspective.
At TRB if you get a chance drop by at our talk on spatial analyses using GIS.
Thank you for reading the paper.
Sheila et. al.,
A fascinating study, but it seems so obvious to me that the highest number of complaints would arise from the busiest roads at the busiest times that I wonder why you bothered. Consider the number of aggressive drivers as a proportion of the driving population. It stands to reason, then, that as the total volume of traffic passing through any specified spatial and/or temporal observation point increases so must the total number of aggressive drivers. Of course you will get an increase in complaints. I guess there may be some scientific justification to proving the point mathematically. Unfortunately, statistical analysis can only describe what has happened – not the reasons for it. For that you will have to go to the behavioural sciences.
Here are some behavioural factors that could influence your study:
1/ As traffic density increases, the drivers perceive an increase in the level of risk they are exposed to. This may increase their sensitivity to the aggressiveness of other drivers and lead to an increase in complaints that is not necessarily proportional to the increase in aggressive behaviours.
2/ The peak reporting period 3:00 to 6:00pm, is when parents are taking their children home from school. Parents tend to be very protective of their children and therefore would be less tolerant of the aggressiveness of other drivers. This could also lead to an increase in complaints that is not necessarily proportional to the increase in aggressive behaviours.
3/ The peak reporting period 3:00 to 6:00pm, is when people are returning home after their day’s work. Tired and grumpy people tend to be less tolerant of the behaviour of others. They may also feel disgruntled because they perceive that the other driver is gaining some unfair advantage by their aggressive driving (they are stuck in the traffic while the other gets home sooner). These factors could also lead to an increase in complaints that is not necessarily proportional to the increase in aggressive behaviours.
4/ Eyewitness reports are notoriously inaccurate. Just ask any crash investigator! Each one of those complaints you received will be coloured by the beliefs, values, and attitudes of the complainant.
Maybe you could study these effects by using your current data to identify suitable locations for more detailed analysis. Have the sites monitored by hidden video cameras and then correlate the complaints received with the video footage. This will give you some check on the relationship between the behaviours complained of and the actual event.
Thanks for the opportunity to comment.
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