WO2000031712A1 - Procede permettant de determiner un modele de manipulation des commandes pour un conducteur - Google Patents

Procede permettant de determiner un modele de manipulation des commandes pour un conducteur

Info

Publication number
WO2000031712A1
WO2000031712A1 PCT/SE1999/002207 SE9902207W WO0031712A1 WO 2000031712 A1 WO2000031712 A1 WO 2000031712A1 SE 9902207 W SE9902207 W SE 9902207W WO 0031712 A1 WO0031712 A1 WO 0031712A1
Authority
WO
WIPO (PCT)
Prior art keywords
driver
vehicle
behaviour
information
drivers
Prior art date
Application number
PCT/SE1999/002207
Other languages
English (en)
Inventor
Greger Andersson
Peter Kaufmann
Björn Eriksson
Original Assignee
Greger Andersson
Peter Kaufmann
Eriksson Hans
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Greger Andersson, Peter Kaufmann, Eriksson Hans filed Critical Greger Andersson
Priority to AU15943/00A priority Critical patent/AU1594300A/en
Publication of WO2000031712A1 publication Critical patent/WO2000031712A1/fr

Links

Classifications

    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B9/00—Simulators for teaching or training purposes
    • G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
    • G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles
    • G09B9/052—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles characterised by provision for recording or measuring trainee's performance

Definitions

  • the present invention relates to a method to map the control handling pattern of a driver by using comparing and predicative mathematic models.
  • the invention also discloses use of said map to suggest a supplementary training to develop and enhance the basic skill/control handling pattern and in that way simultaneously form the base from which a quality guarantee of the driver training can be performed regarding said basic skill/control handling pattern.
  • the invention also discloses an equipment to perform said method.
  • the invention relates, in an embodiment, to an invention to map the behaviour patterns of the driver/vehicle by using a so-called logging system where several variables are measured at the same time, e.g. acceleration/deceleration, i.e. g-forces and changes of g-forces, preferably in the horisontal plane, turning of the steering wheel, the handling of the pedals, revs of the engine, etc during different (also severe) drivning conditions, at the same time as the driver is training certain moments to build up his or hers basic skill on a reflex level.
  • acceleration/deceleration i.e. g-forces and changes of g-forces
  • changes of g-forces preferably in the horisontal plane, turning of the steering wheel, the handling of the pedals, revs of the engine, etc during different (also severe) drivning conditions
  • Each observation i.e measurement at a certain point, is a vector being a quantitative description of the behaviour of the driver at this very point.
  • these vectors can be collected to a data matrix. Such a matrix will then be a quantitative description of the behaviour of the driver during the whole training session.
  • the object of the present invention is to disclose a method to map possible weaknesses or shortages in the drivers basic skill of handling a vehicle, and with this map as a base, direct the training onto the skills needed to be there in one hand to make the driver feel comfortable and safe in the role as a vehicle driver and responsible for a safe driving, but also to make the fellow road-users feel safer together with "unexperienced" young drivers out on the roads.
  • the invention is disclosed to train elementary handling of the vehicle in a way making the skill incorp- orated in the autonomous nervous system, i.e as reflexes already in an early stage during the driver training to as far as possible decrease the risk of getting said experiences in the hard way out on the open roads among fellow road-users in close escapes maybe releasing panic reflexes.
  • the training must take place by using real vehicles. To obtain an automatic behaviour by training it is very important that g-forces and changes in g-forces can be apprehended by the driver, as changes in g- forces experienced by the brain have a very strong influence on which reflexes are going to be released to arms and legs.
  • An other important aspect of the present invention is an application where a control of the drivers fitness to safely drive a vehicle can take place during a travel in progress.
  • the handling defaults of a novis driver are of different kinds, but many defaults can be classified to a motoric or psychomotoric incapability and are principally of the same kind for many novis drivers even tough two drivers will not have an identical behaviour regarding handling defaults and panic thresholds.
  • mapping the drivers behaviour/the behaviour of the vehicle it will be simple to use - in connection to this map - an interactive computerized mapping system where the actual handling pattern of the controls and the behaviours of the vehicle in an exercise will be compared with stored "correct" handling patterns of the controls, and from a difference, if any, between these patterns it is decided if the exercise is approved or not, i.e. if the exercise is performed in a safe or in an irresolute way.
  • the method to map the handling pattern can be connected to a system for positioning in such a way that the coordinates of the vehicle is continously recorded at the same time as the driver behaviour is mapped and recorded.
  • This technique to continously decide the position of a vehicle may also be based on one or a couple of sensitive g-force recording means forming part of a computerized logging system and wherein the g-force recording means are of such a type that the position of a vehicle on a test track can be decided with a great accuracy.
  • An example of such g-force recording means with a digital output is sold by Analog Devices, Inc., USA.
  • One possibility to relate the drivers behaviour to an actual position on a track will also allow a comparision between the behaviour of a trainee and a choosen "ideal" driving behaviour on the one and same position on the track, i.e. in a way making a comparision between said behaviours meaningful.
  • the coosen ideal driving behaviours can be on different skill levels dependend upon what type of drivers education or completing training is aimed at.
  • the map coordinates, or other information of the position of the vehicle on said track, and vectors with measure data will together with the way of looking upon it as described above, form the base for the classifying system wherein the driver behaviours, mapped from the track, can be compared with the behaviour of a discerning and skilled driver as mapped at the same or at a similar track.
  • the classification can be done with different kind of multvariable-mathematic techniques as discriminating analysis or analysis of the principal components or with the aid of a neural net work.
  • the data matrix is divided in a calibrating set and in a test set, and after this the classifying modell is formed. This method is described below for an analysis of principal components and for neural networks.
  • the principal component analysis is a spiritual tool to elucide the underlaying linear structures being found in the data to be analysed.
  • the basic assumption is that each original variable cannot describe the complexibility of the problem studied, but that the substantial information is mixed in all the measure variables.
  • the goal is to perform an linear transformation of data into a sub space of a lower dimension. This calculated sub space is stretched up by the so called latent variables, i.e. the underlaying ortogonal information structures of measure data and is calculated secventially as the directions maximazing the explained covariance of measure data.
  • the cosines are used against the axis of the original coordinate system.
  • the vecor is called "loading”.
  • the positions of the separate observations in the calculated sub space will be scaled and are described afterwards as the position of the separate observation, lineary projected onto the calculated "loading" vectors. Said linear projecting onto a "loading" vector is mentioned as the “scores" values of the separate observation along each "loading" vector.
  • the principal component analysis can be used in classification by studying the positions of the separate observations in the calculated sub space. According to what is said above the separate observations describing similar behaviours will form groups in the calculated sub space.
  • the boundary aera of a group can be calculated by applying a Hotelling T2- test, provided that the separate groups can be identified, which in the precent case is secured by studying and recording the result of each separate driver.
  • Neural net work is a ceremonies outlook to describe the natural solution of learning, where the human brain is the primary prototype and consists of a number of neurons being connected into a net work. Depen- dent of the arcitecture of said net work the neural net work will gain different functionalities. In this context a so called feed-forward neural net work will be described.
  • Such a net work will consist of a number of layers. A separate neuron in a layer is connected to all the neurons in an earlier layer and to all neurons in a later layer. Said layer where measure data or preprepared measure data is introduced to the net work is called an input layer, the layer where the results is presented is an output layer and the layers in beween are called hidden layers.
  • the functionality in a separate neuron is to weight it to the incoming information to the separate neuron, to process the calculated scalar product over a transmitting function.
  • Said transmitting function commonly being not linear, e.g. the hyperbolicus or sigmod of the tangent will give the neural network its non linear properties.
  • the training of a nural network of the typ feed-forward means optimizing the arcitecture of neural network, i.e. the number of hidden layers and the amount of neurons in the separate hidden layers, and before an optimized arcitecture train said neural network to distinguish the different groups identified by measure data.
  • Measure data is preprepared with success by applying the above mentioned principal component analysis which will increase the speed of convergense at the training step of said neural network.
  • the classification for a feed-forward neural network will usually take place by "learning" the neural network to differentiate beween, in the present case, a skilful drivers behaviour and a poor drivers behaviour seen from a level of basic skill. I.e the different behaviours must be presented to the net work during the learning phase, which can be done by coding a good reflex behaviour with the value 1 (one), and a poor reflex behaviour with the value 0 (null), or vice versa.
  • the nearness of the future predictions to the coded integer will describe the class belonging of the separate observation, i.e. the separate observation will belong to the group as being closest in prediction value.
  • a method is disclosed to effectively train/map an ability of a driver to reflectively handle a vehicle.
  • the multi variate analysis of collected information from several different measure variables is the one condition to get an overview of different behaviours or series of behaviours developed and are dependent on eachother and which in ceratain constellations will lead to a risky behaviour or to an uncontrolled behaviour of the vehicle.
  • the other condition is the comparison with a "corrct" behaviour by performing the driving exercises on a certain test track where it will be a restricted amount of possible behaviours of the driver and of the vehicle.
  • the recorded information (data) of the practice drivning may be stored in a memory card, e.g. connectable to a personal computer.
  • a connection to a main computer having the capacity to "judge", i.e. a big memory with stored practice drivings of corresponding type from different kind of skilled drivers, will in infact make it possible to find out, from the recorded differences, if any, between an ideal behaviour and the actual behaviour about shortcomings in the handling of the controls and in the perception, and to suggest suitable exercises assisting the driver to overcome these shortcomings.
  • information can be transferred back to the memory card of the driver/trainee with these suggested new exercises.
  • these exercises will be automatically suggested by an interactive computer system at said training aera. Suitable exercises are determined and a suitable driving path through the training aera is settled to eliminate the discovered shorcomings of the driver.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Navigation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Business, Economics & Management (AREA)
  • Physics & Mathematics (AREA)
  • Educational Administration (AREA)
  • Educational Technology (AREA)
  • General Physics & Mathematics (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

L'invention concerne un procédé et un équipement permettant de cartographier le modèle de manipulation des commandes pour un conducteur grâce à des modèles mathématiques comparatifs et prédicatifs. Ce procédé consiste à utiliser ces modèles mathématiques comparatifs et prédicatifs obtenus par l'analyse multidimensionnelle de données du flux d'informations enregistrées en continu associées à un comportement du véhicule correct pendant le trajet dans une piste d'essai prédéterminée et dans des conditions prédéterminées.
PCT/SE1999/002207 1998-11-26 1999-11-26 Procede permettant de determiner un modele de manipulation des commandes pour un conducteur WO2000031712A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU15943/00A AU1594300A (en) 1998-11-26 1999-11-26 Method to decide the handling pattern of the controls for a driver

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
SE9804124A SE9804124D0 (sv) 1998-11-26 1998-11-26 Förfarande för att kartlägga förarbeteenden samt anläggning för förfarandets genomförande
SE9804124-7 1998-11-26

Publications (1)

Publication Number Publication Date
WO2000031712A1 true WO2000031712A1 (fr) 2000-06-02

Family

ID=20413482

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/SE1999/002207 WO2000031712A1 (fr) 1998-11-26 1999-11-26 Procede permettant de determiner un modele de manipulation des commandes pour un conducteur

Country Status (3)

Country Link
AU (1) AU1594300A (fr)
SE (1) SE9804124D0 (fr)
WO (1) WO2000031712A1 (fr)

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001060254A1 (fr) * 2000-02-15 2001-08-23 Active Attention Ab Procede et organe permettant de surveiller la vivacite d'un conducteur
WO2002030700A2 (fr) * 2000-10-13 2002-04-18 Motorola, Inc. Procede et appareil permettant d'ameliorer la performance d'un conducteur de vehicule
WO2002033529A2 (fr) * 2000-10-14 2002-04-25 Motorola, Inc. Systeme et procede permettant d'ameliorer le comportement d'un conducteur
WO2002034571A2 (fr) * 2000-10-14 2002-05-02 Motorola, Inc. Methode d'evaluation et d'ameliorations du comportement d'un conducteur de vehicule et dispositif a cet effet
WO2003070504A1 (fr) * 2002-02-04 2003-08-28 Cesium Ab Procede et moyen pour mesurer l'interaction entre un conducteur et son vehicule
US7149653B2 (en) * 2001-11-06 2006-12-12 Daimlerchrysler Ag Information system in a motor vehicle with driving-style-dependent production of information to be outputted
US8666603B2 (en) 2011-02-11 2014-03-04 Sitting Man, Llc Methods, systems, and computer program products for providing steering-control feedback to an operator of an automotive vehicle
US8773251B2 (en) 2011-02-10 2014-07-08 Sitting Man, Llc Methods, systems, and computer program products for managing operation of an automotive vehicle
US8902054B2 (en) 2011-02-10 2014-12-02 Sitting Man, Llc Methods, systems, and computer program products for managing operation of a portable electronic device
US11999368B2 (en) 2022-03-28 2024-06-04 Bendix Commercial Vehicle Systems, Llc Systems and methods for automated vehicle fleet management according to dynamic pedagogical behavior reinforcement

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115859695B (zh) * 2023-02-27 2023-05-26 北京千种幻影科技有限公司 模拟驾驶测试数据分析方法、系统及设备

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1992003803A1 (fr) * 1990-08-15 1992-03-05 Sses Ab Procede et appareil destines a ameliorer la securite routiere
US5269687A (en) * 1990-08-01 1993-12-14 Atari Games Corporation System and method for recursive driver training
EP0633552A2 (fr) * 1993-07-05 1995-01-11 Audi Ag Système pour évaluer le mode de conduite d'un véhicule
GB2286369A (en) * 1994-02-11 1995-08-16 Solvit Scient Engineers Limite Equipment to measure driver acceleration patterns and report associated accident risks
US5573402A (en) * 1992-05-22 1996-11-12 Atari Games Corporation System and method for coloring polygon using dithering

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5269687A (en) * 1990-08-01 1993-12-14 Atari Games Corporation System and method for recursive driver training
WO1992003803A1 (fr) * 1990-08-15 1992-03-05 Sses Ab Procede et appareil destines a ameliorer la securite routiere
US5573402A (en) * 1992-05-22 1996-11-12 Atari Games Corporation System and method for coloring polygon using dithering
EP0633552A2 (fr) * 1993-07-05 1995-01-11 Audi Ag Système pour évaluer le mode de conduite d'un véhicule
GB2286369A (en) * 1994-02-11 1995-08-16 Solvit Scient Engineers Limite Equipment to measure driver acceleration patterns and report associated accident risks

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001060254A1 (fr) * 2000-02-15 2001-08-23 Active Attention Ab Procede et organe permettant de surveiller la vivacite d'un conducteur
WO2002030700A2 (fr) * 2000-10-13 2002-04-18 Motorola, Inc. Procede et appareil permettant d'ameliorer la performance d'un conducteur de vehicule
US6909947B2 (en) 2000-10-14 2005-06-21 Motorola, Inc. System and method for driver performance improvement
US6925425B2 (en) 2000-10-14 2005-08-02 Motorola, Inc. Method and apparatus for vehicle operator performance assessment and improvement
WO2002033529A3 (fr) * 2000-10-14 2002-08-15 Motorola Inc Systeme et procede permettant d'ameliorer le comportement d'un conducteur
WO2002034571A3 (fr) * 2000-10-14 2002-08-15 Motorola Inc Methode d'evaluation et d'ameliorations du comportement d'un conducteur de vehicule et dispositif a cet effet
WO2002030700A3 (fr) * 2000-10-14 2002-09-12 Motorola Inc Procede et appareil permettant d'ameliorer la performance d'un conducteur de vehicule
US7565230B2 (en) 2000-10-14 2009-07-21 Temic Automotive Of North America, Inc. Method and apparatus for improving vehicle operator performance
WO2002033529A2 (fr) * 2000-10-14 2002-04-25 Motorola, Inc. Systeme et procede permettant d'ameliorer le comportement d'un conducteur
WO2002034571A2 (fr) * 2000-10-14 2002-05-02 Motorola, Inc. Methode d'evaluation et d'ameliorations du comportement d'un conducteur de vehicule et dispositif a cet effet
US7149653B2 (en) * 2001-11-06 2006-12-12 Daimlerchrysler Ag Information system in a motor vehicle with driving-style-dependent production of information to be outputted
WO2003070504A1 (fr) * 2002-02-04 2003-08-28 Cesium Ab Procede et moyen pour mesurer l'interaction entre un conducteur et son vehicule
US8773251B2 (en) 2011-02-10 2014-07-08 Sitting Man, Llc Methods, systems, and computer program products for managing operation of an automotive vehicle
US8902054B2 (en) 2011-02-10 2014-12-02 Sitting Man, Llc Methods, systems, and computer program products for managing operation of a portable electronic device
US8666603B2 (en) 2011-02-11 2014-03-04 Sitting Man, Llc Methods, systems, and computer program products for providing steering-control feedback to an operator of an automotive vehicle
US11999368B2 (en) 2022-03-28 2024-06-04 Bendix Commercial Vehicle Systems, Llc Systems and methods for automated vehicle fleet management according to dynamic pedagogical behavior reinforcement

Also Published As

Publication number Publication date
SE9804124D0 (sv) 1998-11-26
AU1594300A (en) 2000-06-13

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