A method for identifying aggressive driving by using naturalistic driving data
Paper in proceedings, 2018

Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. By understanding the behavior of the drivers and finding quantitative ways to categorize the behavior associated with higher crash risk, programs for modifying driver behavior towards safer driving can be designed. The objective of this study is to identify aggressive drivers by metrics calculated from naturalistic driving data.
The drivers are separated by the aggressive behavior of following too closely to a front vehicle, i.e. tailgating. Furthermore, two jerk metrics are calculated to identify aggressive drivers: a) number of large positive jerks when pressing the gas pedal and b) number of large negative jerks when pressing the brake pedal. Moreover, drivers’ gender, Arnett Inventory of Sensation Seeking (AISS) score, Driver Behavior Questionnaires (DBQ) and country effects on the metrics are analyzed.
The results show that the aggressive drivers, defined for car following situations using tailgating metric, were associated with significantly higher frequency of using large negative jerk. The results could be potentially applied in programs for driver training and education, advanced driver coaching, and in the context of usage-based insurance.

tailgating

car-following

aggressive driving

Longitudinal jerk

Author

Jordanka Kovaceva

Chalmers, Mechanics and Maritime Sciences, Vehicle Safety

Irene Isaksson-Hellman

7th International Symposium on Naturalistic Driving Research

7th International Symposium on Naturalistic Driving Research
Blacksburg, Virginia, USA,

Driving Forces

Sustainable development

Areas of Advance

Transport

Subject Categories

Infrastructure Engineering

Applied Psychology

Vehicle Engineering

More information

Latest update

9/3/2018 1