A toolbox for automated driving on the STISIM driving simulator

Journal article (2018)

Authors

A. Eriksson Swedish National Road and Transport Research Institute, University of Southampton
J.C.F. de Winter Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering , Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Neville A. Stanton University of Southampton
Research Group
Biomechatronics & Human-Machine Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2018 A. Eriksson, J.C.F. de Winter, Neville A. Stanton
DOI
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https://doi.org/10.1016/j.mex.2018.08.003
Automated driving Human factors Toolbox Driving simulator OA-Fund TU Delft Highly automated driving Adaptive cruise control STISIM
More Info
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Published Date

2018

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Biomechanical Engineering

Research Group

Biomechatronics & Human-Machine Control

Abstract

Driving simulators have been used since the beginning of the 1930s to assist researchers in assessing driver behaviour without putting the driver in harm’s way. The current manuscript describes the implementation of a toolbox for automated driving research on the widely used STISIM platform. The toolbox presented in this manuscript allows researchers to conduct flexible research into automated driving, enabling independent use of longitudinal control, and a combination of longitudinal and lateral control, and is available as an open source download through GitHub. The toolbox allows the driver to adjust parameters such as set speed (in 5 kph increments) and time-headway (in steps of 1, 1.5, and 2 s) as well as automation mode dynamically, while logging additional variables that STISIM does not provide out-of-the-box (time-headway, time to collision). Moreover, the toolbox presented in this manuscript has gone through validation trials showing accurate speed, time-headway, and lane tracking, as well as transitions of control between manual and automated driving.