Predicting Driver Braking and Stopping Behavior using an Intelligent Speed Adaptation System

Predicting Driver Braking and Stopping Behavior using an Intelligent Speed Adaptation System
Authors : Dr. Stephen Arhin, Dr. Azim Eskandarian
Publication Date: 23-06-2015


Author(s):  Dr. Stephen Arhin, Dr. Azim Eskandarian

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 4 - Issue. 06 , June - 2015

e-ISSN:   2278-0181


The efficacy of Intelligent Speed Adaptation systems (ISAs) hasbeen evaluated in mitigating excessive speeding in simulator and field operation experiments in Europe, and most recently in the United States.Different roadway scenarios have been used to mimic real-life driving conditions in simulation experiment performed using ISAs in virtual driving scenarios.This paper presents regression models for three types of ISAs: Warning, Mandatory and Advanced Vehicle Speed Adaptation System (AVSAS) on approach to a stop-controlled intersection and a curve.The dependent variables for the un-signalized intersection and curve approach were respectively stopping distance and approach speed. The resulting predictive behavior models have associated R2 values ranging from 63% to 93%. These models could be used to enhance or refine the realism of the roadway designs for simulator-based ISA experiments. In addition, these models can be incorporated in the development of future ISA algorithms as predictors of driver behavior after being validated in field operational tests.


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