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            "abstractNote": "The energy associated with the use of road infrastructure exceeds in few years the energy needed for its construction. The link between infrastructure and use energy has not been, however, studied in depth, particularly as the legitimate transport societal expectations are related to efficiency and safety. However, we can consider reducing the energy use by working out minor optimizations of the road infrastructure itself, which is a major challenge in a context of overall decrease of resources and increasing pressures on the environment. Experimental work is carried out here to develop one of these optimizations by improving the eco-driving potential of roads. It is based on the adequacy between vehicles dynamics, the road longitudinal profile and the speed sectioning of the infrastructure. This sectioning corresponds to the succession of speed limitations (road signs, roundabouts, intersections.). It may allow drivers to eco-drive or not, depending on dynamics, slopes, and secondary parameters as driver reaction time or distance of visibility. Optimal speed sectioning aims to limit the mechanical braking needed by potential energy reduction, due to slopes, which can be encountered simultaneously with the needed kinetic energy reduction. Evaluation has been made on actual road sections, while recording both vehicle dynamics, driver commands, road signs positions and road longitudinal profile. Results show that energy consumption of vehicles approaching a speed reduction sign can be reduced by moving backward this sign of about 700 meters, without penalizing the primary safety function. The associated gain, for this optimization, has been evaluated to 14 liters of fuel per day for one of the experimental sites, considering traffic data. Application of this method on a network could then lead to considerable energy saving by allowing eco-driving.",
            "proceedingsTitle": "ROAD AND RAIL INFRASTRUCTURE IV",
            "conferenceName": "4th International Conference on Road and Rail Infrastructure (CETRA)",
            "publisher": "Univ Zagreb, Fac Civil Engineering",
            "place": "Zagreb",
            "date": "2016",
            "eventPlace": "",
            "volume": "",
            "issue": "",
            "numberOfVolumes": "",
            "pages": "589-595",
            "series": "",
            "seriesNumber": "",
            "DOI": "",
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            "language": "English",
            "libraryCatalog": "Clarivate Analytics Web of Science",
            "callNumber": "",
            "rights": "",
            "extra": "ISSN: 1848-9850\nNum Pages: 7\nSeries Title: Road and Rail Infrastructure\nWeb of Science ID: WOS:000518215900071",
            "tags": [
                {
                    "tag": "ENERGY",
                    "type": 1
                },
                {
                    "tag": "Eco-design",
                    "type": 1
                },
                {
                    "tag": "Eco-driving",
                    "type": 1
                },
                {
                    "tag": "energy consumption",
                    "type": 1
                },
                {
                    "tag": "full-scale experiment",
                    "type": 1
                },
                {
                    "tag": "longitudinal profile",
                    "type": 1
                },
                {
                    "tag": "public policy",
                    "type": 1
                },
                {
                    "tag": "road infrastructure",
                    "type": 1
                },
                {
                    "tag": "use phase",
                    "type": 1
                },
                {
                    "tag": "vehicle dynamics",
                    "type": 1
                }
            ],
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            "dateAdded": "2024-04-12T13:18:09Z",
            "dateModified": "2024-04-12T13:18:09Z"
        }
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            "title": "A revised Durbin-Wu-Hausman test for industrial robot identification",
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                {
                    "creatorType": "author",
                    "firstName": "Alexandre",
                    "lastName": "Janot"
                },
                {
                    "creatorType": "author",
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                },
                {
                    "creatorType": "author",
                    "firstName": "Maxime",
                    "lastName": "Gautier"
                }
            ],
            "abstractNote": "This paper addresses the topic of robot identification. The usual identification method makes use of the inverse dynamic model (IDM) and the least squares (LS) technique while robot is tracking exciting trajectories. Assuming an appropriate bandpass filtering, good results can be obtained. However, the users are in doubt whether the columns of the observation matrix (the regressors) are uncorrelated (exogenous) or correlated (endogenous) with the error terms. The exogeneity condition is rarely verified in a formal way whereas it is a fundamental condition to obtain unbiased LS estimates. In Econometrics, the Durbin-Wu-Hausman test (DWH-test) is a formal statistic for investigating whether the regressors are exogenous or endogenous. However, the DWH-test cannot be straightforwardly used for robot identification because it is assumed that the set of instruments is valid. In this paper, a Revised DWH-test suitable for robot identification is proposed. The revised DWH-test validates/invalidates the instruments chosen by the user and validates the exogeneity assumption through the calculation of the QR factorization of the augmented observation matrix combined with a F-test if required. The experimental results obtained with a 6 degrees-of-freedom (DOF) industrial robot validate the proposed statistic. (C) 2015 Elsevier Ltd. All rights reserved.",
            "publicationTitle": "CONTROL ENGINEERING PRACTICE",
            "publisher": "",
            "place": "",
            "date": "MAR 2016",
            "volume": "48",
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            "pages": "52-62",
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            "extra": "Num Pages: 11\nPlace: Oxford\nPublisher: Pergamon-Elsevier Science Ltd\nWeb of Science ID: WOS:000370906700005",
            "tags": [
                {
                    "tag": "BASE INERTIAL PARAMETERS",
                    "type": 1
                },
                {
                    "tag": "CLOSED-LOOP",
                    "type": 1
                },
                {
                    "tag": "DWH-test",
                    "type": 1
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                    "tag": "Heteroskedasticity",
                    "type": 1
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                {
                    "tag": "INSTRUMENTAL VARIABLE APPROACH",
                    "type": 1
                },
                {
                    "tag": "Instrumental variable method",
                    "type": 1
                },
                {
                    "tag": "Rigid robot dynamics",
                    "type": 1
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                {
                    "tag": "Robots identification",
                    "type": 1
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                {
                    "tag": "Wald-statistic",
                    "type": 1
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            "creatorSummary": "Lejeune et al.",
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            "title": "Towards eco-aware timetabling: evolutionary approach and cascading initialisation strategy for the bi-objective optimisation of train running times",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Aurelien",
                    "lastName": "Lejeune"
                },
                {
                    "creatorType": "author",
                    "firstName": "Remy",
                    "lastName": "Chevrier"
                },
                {
                    "creatorType": "author",
                    "firstName": "Pierre-Olivier",
                    "lastName": "Vandanjon"
                },
                {
                    "creatorType": "author",
                    "firstName": "Joaquin",
                    "lastName": "Rodriguez"
                }
            ],
            "abstractNote": "In railway planning, the timetabling step needs, as input, the train running times, which are calculated from a train dynamic model. Usually, this model determines the most energy-efficient train trajectory for a predefined time. However, this time may not correspond to the timetable-makers' needs. They should have the choice among a set of solutions, more or less energy-consuming. This study proposes a method capable of producing a set of alternative running times with the associated mechanical energy required. To this end, the authors' contribution is to set up an efficient evolutionary multi-objective algorithm builds a set of well-spread and diversified solutions which approximate a Pareto front. The solutions are all compromises between running time and energy-consumption, the two minimisation objectives concurrently optimised. Given that an evolutionary algorithm is strongly dependent on the initialisation phase, the efficiency of the algorithm is improved through a specific and original mechanism connecting multiple initialisations in cascade in order to accelerate the convergence towards the best solutions. A set of results obtained on randomly-generated instances is analysed and discussed.",
            "publicationTitle": "IET INTELLIGENT TRANSPORT SYSTEMS",
            "publisher": "",
            "place": "",
            "date": "SEP 2016",
            "volume": "10",
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            "pages": "483-494",
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            "journalAbbreviation": "IET Intell. Transp. Syst.",
            "DOI": "10.1049/iet-its.2014.0309",
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            "shortTitle": "Towards eco-aware timetabling",
            "language": "English",
            "libraryCatalog": "Clarivate Analytics Web of Science",
            "callNumber": "",
            "rights": "",
            "extra": "Num Pages: 12\nPlace: Hertford\nPublisher: Inst Engineering Technology-Iet\nWeb of Science ID: WOS:000382791200004",
            "tags": [
                {
                    "tag": "Pareto front",
                    "type": 1
                },
                {
                    "tag": "Pareto optimisation",
                    "type": 1
                },
                {
                    "tag": "biobjective optimisation",
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                    "tag": "cascading initialisation strategy",
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                {
                    "tag": "mechanical energy",
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                },
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                    "tag": "minimisation objectives",
                    "type": 1
                },
                {
                    "tag": "railway planning",
                    "type": 1
                },
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                    "tag": "railways",
                    "type": 1
                },
                {
                    "tag": "timetable makers",
                    "type": 1
                },
                {
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                    "type": 1
                },
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            "dateModified": "2024-04-12T13:18:09Z"
        }
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]