bibtype J - Journal Article
ARLID 0427942
utime 20240111140847.0
mtime 20140519235959.9
WOS 000339037100017
DOI 10.1016/j.trc.2014.04.009
title (primary) (eng) Data-based Speed-limit-respecting Eco-driving System
specification
page_count 12 s.
serial
ARLID cav_un_epca*0255260
ISSN 0968-090X
title Transportation Research. Part C: Emerging Technologies
volume_id 44
volume 1 (2014)
page_num 253-264
publisher
name Elsevier
keyword eco-driving
keyword fuel consumption
keyword recommended speed
keyword recursive estimation
keyword quadratic optimal control
keyword dynamic programming
author (primary)
ARLID cav_un_auth*0108105
name1 Suzdaleva
name2 Evgenia
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101167
name1 Nagy
name2 Ivan
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type pdf
url http://library.utia.cas.cz/separaty/2014/AS/suzdaleva-0427942.pdf
cas_special
project
project_id TA01030123
agency GA TA ČR
ARLID cav_un_auth*0271776
abstract (eng) The paper describes application of data-based Bayesian approach to model identification and control problems in the field of fuel consumption optimization for conventional vehicles. The main contributions of the presented approach are: (i) analysis of data measured on a driven vehicle; (ii) data-based model construction, its real-time estimation and adaptation; (iii) control criterion using simultaneously setpoints for fuel consumption and speed; (iv) universal recursive Bayesian algorithms of estimation and control implemented as semi-automatic eco-driving system. Experiments with real data report reduction in fuel consumption.
reportyear 2015
RIV BC
num_of_auth 2
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0233598
confidential S
mrcbT16-e TRANSPORTATIONSCIENCETECHNOLOGY
mrcbT16-j 1.147
mrcbT16-s 2.045
mrcbT16-4 Q1
mrcbT16-B 82.155
mrcbT16-C 86.364
mrcbT16-D Q1
mrcbT16-E Q1
arlyear 2014
mrcbU34 000339037100017 WOS
mrcbU56 pdf
mrcbU63 cav_un_epca*0255260 Transportation Research. Part C: Emerging Technologies 0968-090X 1879-2359 Roč. 44 č. 1 2014 253 264 Elsevier