Evaluation and Optimization of Adaptive Cruise Control Policies Via Numerical Simulations

Clement U. Mba, Carlo Novara

2016

Abstract

Adaptive Cruise Control (ACC) makes the driving experience safer and more pleasurable. Several appealing ACC policies have been introduced so far. However, it is difficult in general to understand which is the actual performance that can be guaranteed on a real vehicle. Another relevant issue is that no systematic methods can be found for the optimization of a control policy performance. The first aim of this paper is to compare different ACC policies by means of extensive simulations, considering different realistic road scenarios. This kind of study is important to analyze which policies can be more effective in view of their implementation on real vehicles. The second aim is to develop an optimization method based on a multi-objective Pareto criterion, finalized at designing high-performance policies. The method is tested by means of extensive simulations.

Paper Citation

in Harvard Style

Mba C. and Novara C. (2016). Evaluation and Optimization of Adaptive Cruise Control Policies Via Numerical Simulations . In Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-185-4, pages 13-19. DOI: 10.5220/0005621100130019

in Bibtex Style

@conference{vehits16,
author={Clement U. Mba and Carlo Novara},
title={Evaluation and Optimization of Adaptive Cruise Control Policies Via Numerical Simulations},
booktitle={Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2016},
pages={13-19},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005621100130019},
isbn={978-989-758-185-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Evaluation and Optimization of Adaptive Cruise Control Policies Via Numerical Simulations
SN - 978-989-758-185-4
AU - Mba C.
AU - Novara C.
PY - 2016
SP - 13
EP - 19
DO - 10.5220/0005621100130019