Large-scale Driver Identification Using Automobile Driving Data

We address a large-scale driver identification problem, which aims to predict the driver of a vehicle from various types of data, such as speed and acceleration information, that are collected during driving by using GPS sensors equipped with smart phones. While existing studies consider at most a few hundreds of drivers, we target a huge number of drivers up to 10,000 drivers. The results of our experiments show that our method identifies drivers more precisely than baseline methods. We also show that location features are quite effective in the large scale driver identification, and speed and acceleration features also contribute to driver identification.

[1]  Kazuya Takeda,et al.  Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification , 2007, Proceedings of the IEEE.

[2]  Rok Sosic,et al.  Drive2Vec: Multiscale State-Space Embedding of Vehicular Sensor Data , 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

[3]  Adrian D. C. Chan,et al.  Driver identification using vehicle acceleration and deceleration events from naturalistic driving of older drivers , 2017, 2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[4]  Paulius Lengvenis,et al.  Driving style classification using long-term accelerometer information , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).

[5]  Frank Gauterin,et al.  Online driving style recognition using fuzzy logic , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[6]  Erhan Akin,et al.  Estimating driving behavior by a smartphone , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[7]  Rok Sosic,et al.  Driver identification using automobile sensor data from a single turn , 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).

[8]  Rafik A. Goubran,et al.  Measuring variation in driving habits between drivers , 2014, 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[9]  Robert Ivor John,et al.  A Data Analysis Framework to Rank HGV Drivers , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[10]  Mohan M. Trivedi,et al.  Driver classification and driving style recognition using inertial sensors , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[11]  John H. L. Hansen,et al.  Leveraging sensor information from portable devices towards automatic driving maneuver recognition , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[12]  Mohan M. Trivedi,et al.  Driving style recognition using a smartphone as a sensor platform , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).