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Volatile driving, characterized by fluctuations in speed and accelerationsand aggressive lane changing/merging, is known to contribute to transportationcrashes. To fully understand driving volatility with the intention of reducingit, the objective of this study is to identify its key correlates, whilefocusing on highly volatile trips. First, a measure of driving volatility basedon vehicle speed is applied to trip data collected in the California HouseholdTravel Survey during 2012-2013. Specifically, the trips containing drivingcycles (N=62839 trips) were analyzed to obtain driving volatility. Second,correlations of volatility with the trip, vehicle, and person level variableswere 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 thetrips taken by sedans. Moreover, longer trips have less driving volatility. Inaddition, younger drivers are more volatile drivers than old ones. Overall, theresults of this study are reasonable and beneficial in identifying correlatesof driving volatility, especially in terms of understanding factors thatdifferentiate highly volatile trips from other trips. Reductions in drivingvolatility have positive implications for transportation safety. From amethodological standpoint, this study is an example of how to extract useful(volatility) information from raw vehicle speed data and use it to calm downdrivers and ultimately improve transportation safety.

Analyzing Highly Volatile Driving Trips Taken by Alternative Fuel Vehicles