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Authors: Saad Roustom and Hajo Ribberink

Affiliation: Natural Resources Canada, CanmetEnergy, 1 Haanel Dr, Ottawa, ON, Canada

Keyword(s): Connected, Automated Vehicles, Driving Behaviour, Traffic Performance, GHG Emissions.

Abstract: This study was conducted to identify an optimal driving behaviour of connected and automated vehicles (CAV) that can reduce traffic congestion and GHG emissions under different traffic demand levels. The study employed traffic simulations at the meso scale for the City of Ottawa, Canada, to assess traffic performance and used correlation models to estimate GHG emissions. Aggressive CAVs showed the greatest potential to enhance traffic performance and reduce GHG emissions under all traffic demand levels. The results show that Aggressive CAVs can increase highway capacity and lower vehicle travel time in comparison to Driver Operated Vehicles (DOVs) or CAVs with a less aggressive driving style. The findings of the study indicate that CAVs with aggressive driving behavior can play a crucial role in enhancing traffic performance and in helping to mitigate the adverse impact of transportation on the environment. The results of this study aim to encourage regulatory bodies to adopt effecti ve CAV-related policies that can enhance traffic performance and reduce GHG emissions. (More)

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Paper citation in several formats:
Roustom, S. and Ribberink, H. (2023). Optimizing CAV Driving Behaviour to Reduce Traffic Congestion and GHG Emissions. In Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-652-1; ISSN 2184-495X, SciTePress, pages 198-205. DOI: 10.5220/0011792500003479

@conference{vehits23,
author={Saad Roustom and Hajo Ribberink},
title={Optimizing CAV Driving Behaviour to Reduce Traffic Congestion and GHG Emissions},
booktitle={Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2023},
pages={198-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011792500003479},
isbn={978-989-758-652-1},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Optimizing CAV Driving Behaviour to Reduce Traffic Congestion and GHG Emissions
SN - 978-989-758-652-1
IS - 2184-495X
AU - Roustom, S.
AU - Ribberink, H.
PY - 2023
SP - 198
EP - 205
DO - 10.5220/0011792500003479
PB - SciTePress

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