Adapted Performance Assessment For Drivers Through Behavioral Advantage.
Reference:
@article{qiu2018adaptive,
title={Adaptive Performance Assessment For Drivers Through Behavioral Advantage},
author={Qiu, Dicong and Paga, Karthik},
journal={arXiv preprint arXiv:1804.08219},
year={2018},
month={apr}
}
The potential positive impact of autonomous driving and driver assistance technologies have been a major impetus over the last decade. On the flip side, it has been a challenging problem to analyze the performance of human drivers or autonomous driving agents quantitatively. In this work, we propose a generic method that compares the performance of drivers or autonomous driving agents even if the environmental conditions are different, by using the driver behavioral advantage instead of absolute metrics, which efficiently removes the environmental factors. A concrete application of the method is also presented, where the performance of more than 100 truck drivers was evaluated and ranked in terms of fuel efficiency, covering more than 90,000 trips spanning an average of 300 miles in a variety of driving conditions and environments.
Below is the information of the authors.
- Dicong Qiu (dq@cs.cmu.edu, http://www.davidqiu.com)
- Karthik Paga (kpaga@cs.cmu.edu)
Copyright (C) 2018, Dicong Qiu & Karthik Paga.