  Volatile driving, characterized by fluctuations in speed and accelerations
and aggressive lane changing/merging, is known to contribute to transportation
crashes. To fully understand driving volatility with the intention of reducing
it, the objective of this study is to identify its key correlates, while
focusing on highly volatile trips. First, a measure of driving volatility based
on vehicle speed is applied to trip data collected in the California Household
Travel Survey during 2012-2013. Specifically, the trips containing driving
cycles (N=62839 trips) were analyzed to obtain driving volatility. Second,
correlations of volatility with the trip, vehicle, and person level variables
were quantified using Ordinary Least Squares and quantile regression models.
The results of the 90th percentile regression (which distinguishes the 10%
highly volatile trips from the rest) show that trips taken by pickup trucks,
hatchbacks, convertibles, and minivans are less volatile when compared to the
trips taken by sedans. Moreover, longer trips have less driving volatility. In
addition, younger drivers are more volatile drivers than old ones. Overall, the
results of this study are reasonable and beneficial in identifying correlates
of driving volatility, especially in terms of understanding factors that
differentiate highly volatile trips from other trips. Reductions in driving
volatility have positive implications for transportation safety. From a
methodological standpoint, this study is an example of how to extract useful
(volatility) information from raw vehicle speed data and use it to calm down
drivers and ultimately improve transportation safety.
