Benefit Assessment of New Ecological and Safe driving Algorithm using Naturalistic Driving Data

Sepehr Ghasemi Dehkordi; Gregoire Sebastien Larue; Michael E Cholette; Andry Rakotonirainy

doi:10.1109/IVS.2018.8500670

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Benefit Assessment of New Ecological and Safe driving Algorithm using Naturalistic Driving Data

Conference paper

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Benefit Assessment of New Ecological and Safe driving Algorithm using Naturalistic Driving Data

Sepehr Ghasemi Dehkordi, Gregoire Sebastien Larue, Michael E Cholette and Andry Rakotonirainy

2018 IEEE Intelligent Vehicles (IV) Symposium , pp.1931-1936

IEEE Intelligent Vehicles Symposium (IV), 2018 (Changshu, China, 26-Jun-2018–30-Jun-2018)

Institute of Electrical and Electronics Engineers

2018

DOI: https://doi.org/10.1109/IVS.2018.8500670

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Abstract

Safety

fuels

acceleration

prediction algorithms

tuning

vehicles

trajectory

eco driving

safe driving

naturalistic driving study

model predictive control

A new Ecological and Safe (EcoSafe) driving control algorithm has been recently developed by the authors for controlling the longitudinal motion of the vehicle to minimize fuel consumption while respecting safety constraints. The algorithm uses a Model predictive control framework augmented with enhanced safety constraints based on Intervehicular Time (TIV) and the Time to Collision (TTC). This algorithm requires tuning to adapt to traffic condition. In this paper we propose a tuning method for EcoSafe algorithm which is deduced from driver preference and traffic flow information. In addition, to the best of our knowledge, the benefits of similar EcoSafe algorithms have not been tested with naturalistic data. Hence, we assessed the benefits of EcoSafe algorithm in terms of eco-driving and safety by using 1,100 km of naturalistic driving data. We use velocity profile extracted from the Australian Naturalistic Driving Study (ANDS) as the leading vehicle driving behaviour. The results show that our proposed strategy has a 14% reduction in fuel consumption on average while maintaining high safety levels without increasing travel time significantly.

Details

Title: Benefit Assessment of New Ecological and Safe driving Algorithm using Naturalistic Driving Data
Authors: Sepehr Ghasemi Dehkordi (Author) - Queensland University of Technology
Gregoire Sebastien Larue (Author) - Queensland University of Technology
Michael E Cholette (Author) - Queensland University of Technology
Andry Rakotonirainy (Author) - Queensland University of Technology
Publication details: 2018 IEEE Intelligent Vehicles (IV) Symposium , pp.1931-1936
Conference details: IEEE Intelligent Vehicles Symposium (IV), 2018 (Changshu, China, 26-Jun-2018–30-Jun-2018)
Publisher: Institute of Electrical and Electronics Engineers
Date published: 2018
DOI: 10.1109/IVS.2018.8500670; 10.1109/IV43497.2018
ISBN: 9781538644522
Organisation Unit: Road Safety Research Collaboration; University of the Sunshine Coast, Queensland; School of Law and Society
Language: English
Record Identifier: 99648949402621
Output Type: Conference paper

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