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Finding Patterns in Accident Data

Finding Patterns in Accident Data

Telematics makes for a great business tool by being able to identify single safety events, such as a driver speeding or not wearing a seatbelt. All this helps fleets to train and work with drivers on reducing safety risks. But telematics can bring even more to the table by helping unfold a larger view on fleet safety.

There may be habits going on with your operators that could easily go unnoticed without stepping back and looking at the information for trends. We generated some data points on patterns in accident events.

Here are a few of the findings:

1. Time from Maximum Speed to Impact

The chart: This chart looks at the duration in minutes between a driver hitting the maximum speed in their trip and the point of impact in the accident (X-axis), and compares that to the number of vehicles in an accident during that time frame (Y-axis).

The findings: As you can see from the spike early on, there certainly seems to be a correlation with the speed and how soon a driver is likely to be in an accident.

In our sample:

  • 29% of accidents occurred within 1 minute of the driver hitting the maximum speed in their trip
  • 71% of accidents occurred within the first 10 minutes of the maximum speed

accident data chart time from max speed to impact

2. Time from Start of Trip to Impact

The chart: This chart compares the duration in minutes from the trip’s start time to the point of impact in an accident (X-axis) to the number of vehicles/accidents (Y-axis).

The findings: This trip accident study mostly gathered and used short trip data. By looking at the results presented in the chart below, it is clear that a large number of accidents can happen early on, right at the start of a trip. It is important for drivers to be fully prepared to practice safe and cautionary driving at all times.

In our sample:

  • 33% of accidents occurred within the first 10 minutes of a trip
  • 54% of accidents occurred within the first 20 minutes of a trip

accident data chart time from start to impact

3. Speed Prior to Impact

The chart: This chart shows the driver’s speed in miles per hour (X-axis) and compares that to the number of vehicles/accidents that occurred at that speed (Y-axis).

The findings: While this chart has spikes throughout (and likely has few accidents past 80 mph since few drivers are going beyond that speed), we found one particular statistic of interest in our sample:

  • 51% of accidents occurred below 40 mph in city driving conditions

accident data chart speed prior to impact

4. Maximum Speed of Drivers in an Accident

The chart: This chart looks at the maximum speed a driver hit during a trip (X-axis) and compares that to the number of vehicles/trips that had an accident in which that maximum speed occurred (Y-axis).

The findings: Drivers going more than 60 mph at any point during a trip seem to be more likely to get involved in an accident based on the spikes that can be seen in the chart above.

Even considering the maximum speed of some freeways, in our sample:

  • 32% of vehicles had a maximum speed above 70 mph during their trip in which an accident occurred

accident data chart speed prior to impact

Conclusion: Dig In

Don’t be afraid to extrapolate your own fleet’s data to find these larger trends and share them with your drivers as part of your safety training and safe driving reminders.

Related:

6 Road Crash Statistics You Shouldn’t Ignore

Accident Reconstruction with Telematics Data

Do Driver Scorecards Work?

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