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Driver modeling and implementation of a fuel-saving ADAS

Driver modeling and implementation of a fuel-saving ADAS
Driver modeling and implementation of a fuel-saving ADAS
Controlling vehicle velocity, by coaching the driver to eco-drive with an advanced driver assistance system (ADAS), is a promising method to decrease fuel consumption and greenhouse gas emissions for combustion engine-driven road vehicles. By using optimal control techniques, such a system may find velocity profiles in real-time that minimize fuel consumption. This is particularly useful to recommend the optimal time to initiate coasting, which is otherwise difficult to estimate by a driver. However, this ADAS should not choose velocities and accelerations that the driver will dislike, such as those that leave too much or too little space to the preceding vehicle, or those that take corners at high speed. To remedy this, we introduce an optimal control model of acceleration that mimics drivers' behavior and combine this with a model of fuel consumption to trade-off driver preferences and fuel savings. We give examples of the velocity profiles recommended in a typical driving scenario to demonstrate the potential fuel savings. Finally, we give details of a prototype system, which has recently been implemented in the driving simulator at the University of Southampton.
IEEE
Fleming, James
b59cb762-da45-43b1-b930-13dd9f26e148
Yan, Xingda
2d256fbf-9bee-4c5e-9d75-fe15d1a96ade
Allison, Craig
46b3ce37-1986-4a23-9385-a54d0abd08d5
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd
Lot, Roberto
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78
Fleming, James
b59cb762-da45-43b1-b930-13dd9f26e148
Yan, Xingda
2d256fbf-9bee-4c5e-9d75-fe15d1a96ade
Allison, Craig
46b3ce37-1986-4a23-9385-a54d0abd08d5
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd
Lot, Roberto
ceb0ca9c-6211-4051-a7b8-90fd6f0a6d78

Fleming, James, Yan, Xingda, Allison, Craig, Stanton, Neville and Lot, Roberto (2018) Driver modeling and implementation of a fuel-saving ADAS. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018). IEEE. 6 pp. (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Controlling vehicle velocity, by coaching the driver to eco-drive with an advanced driver assistance system (ADAS), is a promising method to decrease fuel consumption and greenhouse gas emissions for combustion engine-driven road vehicles. By using optimal control techniques, such a system may find velocity profiles in real-time that minimize fuel consumption. This is particularly useful to recommend the optimal time to initiate coasting, which is otherwise difficult to estimate by a driver. However, this ADAS should not choose velocities and accelerations that the driver will dislike, such as those that leave too much or too little space to the preceding vehicle, or those that take corners at high speed. To remedy this, we introduce an optimal control model of acceleration that mimics drivers' behavior and combine this with a model of fuel consumption to trade-off driver preferences and fuel savings. We give examples of the velocity profiles recommended in a typical driving scenario to demonstrate the potential fuel savings. Finally, we give details of a prototype system, which has recently been implemented in the driving simulator at the University of Southampton.

Text FuelSavingADAS_final_20Jul18 - Accepted Manuscript
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Accepted/In Press date: 17 June 2018

Identifiers

Local EPrints ID: 424455
URI: https://eprints.soton.ac.uk/id/eprint/424455
PURE UUID: 5ebf8457-008f-4ead-8489-58f5fe10460a
ORCID for James Fleming: ORCID iD orcid.org/0000-0003-2936-4644
ORCID for Roberto Lot: ORCID iD orcid.org/0000-0001-5022-5724

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Date deposited: 05 Oct 2018 11:37
Last modified: 06 Oct 2018 00:30

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