EP3717326A1 - Procédé pour faire fonctionner un dispositif de commande d'un véhicule automobile pour prédire un prochain arrêt, dispositif de commande et véhicule automobile - Google Patents

Procédé pour faire fonctionner un dispositif de commande d'un véhicule automobile pour prédire un prochain arrêt, dispositif de commande et véhicule automobile

Info

Publication number
EP3717326A1
EP3717326A1 EP18814826.6A EP18814826A EP3717326A1 EP 3717326 A1 EP3717326 A1 EP 3717326A1 EP 18814826 A EP18814826 A EP 18814826A EP 3717326 A1 EP3717326 A1 EP 3717326A1
Authority
EP
European Patent Office
Prior art keywords
motor vehicle
stopping
model
control device
determined
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
EP18814826.6A
Other languages
German (de)
English (en)
Inventor
Stefan Grubwinkler
Friedrich Graf
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Vitesco Technologies GmbH
Original Assignee
Vitesco Technologies GmbH
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 Vitesco Technologies GmbH filed Critical Vitesco Technologies GmbH
Publication of EP3717326A1 publication Critical patent/EP3717326A1/fr
Pending legal-status Critical Current

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/181—Preparing for stopping
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18109—Braking
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18018—Start-stop drive, e.g. in a traffic jam
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18072—Coasting
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18109—Braking
    • B60W30/18127—Regenerative braking
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18154—Approaching an intersection
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/04—Traffic conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0097—Predicting future conditions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/36—Input/output arrangements for on-board computers
    • G01C21/3605—Destination input or retrieval
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/095—Traffic lights
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/18—Braking system
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
    • B60W2555/60—Traffic rules, e.g. speed limits or right of way
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/10—Historical data
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/55—External transmission of data to or from the vehicle using telemetry
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/65—Data transmitted between vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect

Definitions

  • the invention relates to a method for operating a control device of a motor vehicle while driving along a route. By means of the method it is checked whether the motor vehicle will actually stop at a preceding, potential stop point during the current journey.
  • the invention also includes the tax advantage direction as well as a motor vehicle with the control device.
  • Predicting or predicting a stall may be used in a motor vehicle to tune its operation prior to commencement of the stall so as to prevent, for example, unnecessary engagement of friction brakes to decelerate the motor vehicle when the motor vehicle is in a known stall. could also roll out.
  • a model is not currently synchronized with the associated traffic light, the model can not be used.
  • a motor vehicle is dependent on a preceding vehicle for synchronizing its model of a traffic light, which reports the switching operation, which is used for synchronization.
  • the method is limited to the forecast of switching times at traffic lights.
  • the invention has for its object to adapt the operation of a motor vehicle with respect to an imminent possible stopping process.
  • the object is achieved by the subjects of the independent Pa tenta.
  • the invention also includes developments as disclosed by the dependent claims, the following description and the figures.
  • the invention provides a method for operating a control device of a motor vehicle.
  • a control device may be designed, for example, as a control unit of the motor vehicle.
  • the method provides for the operation of the control device during a drive of the motor vehicle along a route.
  • the route may lead along a road network.
  • the route can be a planned route that has been read from a navigation system of the motor vehicle or an estimated route.
  • at least one potential stop point lying ahead along the route is now determined, at which point there is the possibility that the motor vehicle stops.
  • a potential stopping point can be stored or mapped, for example, in a digital map of the motor vehicle.
  • the control device determines a probability value for a probability that the motor vehicle will carry out a stopping process at the stopping point, ie actually stops or comes to a standstill.
  • the probability value is determined on the basis of a holding model.
  • the control device operates as a holding model a statistical model, which also provides intermediate values between 0% and 100% for the probability value. If the probability value then lies within a predetermined time interval, at least one predetermined operating measure is triggered by the control device.
  • the at least one predetermined operational measure is in each case adapted to adjust an operation of the motor vehicle to the Anhal tevorgang. For example, such a loading operation measure may be set up to reduce a fuel consumption of the motor vehicle caused by the stopping process and preferably to minimize it.
  • Another operational measure may be the targeted control of at least one secondary consumer. For example, the power of an electric refrigerant compressor can be increased to efficiently use the energy available by a recuperation operation.
  • the predicted stalling operation may be used for any function and / or vehicle component to enhance comfort or efficiency.
  • the said checked value interval thus defines the anticipated occurrence of the stopping process, ie it indicates all those probability values at which it is assumed that the stopping process will actually occur. In other words, it is assumed that the stopping process actually occurs if the probability value determined by the holding model lies within the predetermined value interval. For this case, then at least one operational measure is triggered, which prevents unnecessary consumption of fuel in the motor vehicle. For example, a coasting of the motor vehicle can be provided towards the breakpoint, instead of further driving the motor vehicle with engine power to then decelerate it with a friction brake.
  • the value interval preferably has an upper limit of 100% and a lower limit that is in a range of 50% to 90%.
  • the invention provides the advantage that fuel can be made possible in a stopping process at such stopping points, which are not connected for example by a traffic light, but are forced by, for example, a traffic or due to a confusing situation. If a motor vehicle also regularly stops here, this can be reproduced or simulated in the statistical model which is used as a holding model. In this case, a variance or irregularity can be compensated by the holding model in that no binary statement (stop yes or no) is generated, but a probability value is determined.
  • the Hal temodell can specify, for example, for at least one potential breakpoint a single probability value. The probability value can be determined by observing the driving behavior at the stopping point and indicating the ratio of actual stopping operations to the total number of observations.
  • the holding model can also provide a probability distribution for at least one potential stopping point, which can each indicate a probability value for different arrival times at the stopping point. But even with deterministic predetermined Abhaltevor courses, such as at a traffic light or on a
  • the holding model can still be used or adapted in the same way, so that such a holding point of the holding model can be considered.
  • the at least one operating measure is initiated, ie the operation of the motor vehicle is adapted to the stopping process, for example by reducing the fuel consumption resulting during the stopping process by means of the at least one operating measure is (as compared to a failure of the operating measure), so that the operation of the motor vehicle can run efficiently despite stopping process.
  • the invention also includes embodiments that provide additional benefits.
  • the method according to the invention can be applied to a large number of different stopping points.
  • An embodiment provides that as at least one potential stopping point in each case an intersection with right of way regulation and / or a roundabout and / or a stop sign and / or a traffic light and / or a driveway (for example on a fast road) and / or a barrier and / or a parking garage entrance is determined.
  • This list is only to be considered as an example.
  • the holding model may provide a statistical description indicating or providing a probability value for a stopping operation at the respective stopping point. If the motor vehicle then approaches the respective stopping point, the probability value for a stopping process can be determined for the stopping point by means of the holding model.
  • a stopping point where it depends on a circuit (for example a traffic light circuit or a barrier circuit) whether a stopping process will actually occur, it may be advantageous for the holding model to be connected to the circuit is synchronized at this stopping point. Unlike in the prior art, but this is not an attempt to observe the stopping point itself, so for example, the traffic light or barrier provided there. Rather, an embodiment provides that by the control device to a stopping point along the
  • Driving distance at least one of the arrival of the stopping point temporally preceding reference event is detected.
  • the Holding model is then the probability value concerning the stopping process at the stop point in question then determined as a function of the at least one detected reference event.
  • the reference event thus does not take place at the stopping point in question itself, but along the route before this stopping point.
  • the motor vehicle first passes the at least one reference event and only then reaches the stopping point.
  • the reference event is preferably correlated in time with the circuit at the stopping point, that is, for example, with the traffic light circuit or the barrier circuit. If the reference event occurs or is observed, it is known in which switching phase the circuit is at the stopping point, without the circuit at the stopping point itself having to be observed by a preceding other motor vehicle.
  • the holding model can determine the switching phase of the preceding stop in question itself (eg, the traffic light switching phase) and determine a probability value of a stopping process for the expected arrival time at the stopping point.
  • This embodiment provides the advantage that the Hal temodell can be adapted or adapted by recognizing the at least one reference event to the current driving situation.
  • Another example of a reference event is entering or exiting a garage. When moving out of the garage, the user of the motor vehicle may have the habit of first driving out of the garage and then stopping the motor vehicle at a stopping point in front of the garage once more to close the garage door. For this holding point can then be triggered at least one operating measure.
  • the user of the motor vehicle may have a habit of stopping in front of the garage to get out and open the garage.
  • the subsequent stopping point is then in the garage, for the at least one operating measure can be triggered during the entry into the garage ever.
  • a particularly considered by the invention reference event is to be seen according to an embodiment in that the at least one reference event is a starting process at a previous stopping point with a traffic light.
  • the Refe rence event represents the start of the motor vehicle when switching to the traffic light on the green phase.
  • a traffic light can be provided, so the holding model be synchronized with this traffic light of the next stop, if the two traffic lights have correlated switching phases. For example, a so-called green wave along the route can be used.
  • the holding model uses the respective probability value for the at least one potential stopping point as a function of traffic information and / or a respective indication of a time and / or a time of day (for example mornings, lunchtimes, afternoons, evenings, at night). and / or a day of the week (for example, Monday, Tuesday, ... Saturday, Sunday) and / or a season (for example, winter or spring or summer or fall) and / or a change of plan of a traffic light (main traffic, Mau horrszeit) is determined ,
  • the holding model is designed dynamically and is adapted to the respective prevailing or existing boundary condition
  • the retention model is preferably trained or adjusted over time by using observation data or training data to train or adapt the retention model.
  • the holding model at least partially trained or adapted by a driving condition of the motor vehicle is detected during at least one previous trip for at least one potential stopping point respectively in the motor vehicle upon reaching the respective stopping point.
  • the driving state un distinguishes between the stopping of the motor vehicle at the stopping point and a passage of the motor vehicle at the stopping point.
  • the passage means that the motor vehicle does not have to stop but remains in motion.
  • the holding model is then trained or adapted based on the detected driving condition. If the stopping of the motor vehicle is detected in the described embodiment, this increases the chance of likelihood in the holding model. If a passage is detected, the stop probability is correspondingly reduced in the holding model.
  • This embodiment is particularly advantageous for a motor vehicle, which is used by a commuter on a commute, that is, on a regularly or multiply traveled route.
  • the described embodiment has the particular advantage that the holding model can be locally trained or adapted by using only observation data from the motor vehicle itself and one of these after-image processing can be dispensed with, since only the driving condition of the motor vehicle has to be observed., Of course, also on the basis of image data of a camera, for example, a current switching state of a traffic light can be determined.
  • One embodiment provides that a driving operating state determined at a stopping point and determined in a traffic jam situation is discarded.
  • the training or adaptation of the holding model takes place more effectively, since the exception "congestion situation" implements the adaptation process or training. ning procedure of the holding model is not falsified or adversely affected.
  • a traffic jam situation can at a
  • the holding model is at least partially trained or adapted that the control device is coupled with at least one external vehicle data source and from the at least one data source model data of a respective holding model of at least one other motor vehicle and / or model data of an overall model of a Server receives and adapts or configures the holding model with the model data received.
  • the server can be a server of the Internet.
  • the control device of the motor vehicle is thus coupled for example via a radio link with the server and / or with at least one other motor vehicle and receives each model data.
  • the Hal temodell of the motor vehicle can be improved or expanded, for example, on the basis of a holding model of another motor vehicle.
  • Model data of the overall model, in which the observation data or training data of several motor vehicles are combined, can be received from the server.
  • This embodiment has the advantage that in the motor vehicle, the holding model can also be trained or adapted for such routes, which were not or at least rarely traveled by the motor vehicle itself.
  • the said, at least one operational measure comprises that a drive train of the motor vehicle in a sailing operation (coasting with disengaged engine) and / or in a towing operation (coasting with a coupled engine) and / or a recuperation (implementing the kinetic energy of the motor vehicle into electrical energy) is operated. Additionally or alternatively, the at least one operational measure may include turning off a combustion engine of the motor vehicle. Another possible operational measure is the targeted control of auxiliary consumers of the electrical system during the expected stopping process. Thus, for example, the power of at least one electrified secondary consumer can be increased and / or the power of at least one non-electrified secondary consumer (eg by belt drive on the internal combustion engine) can be reduced.
  • the at least one operational measure has the advantage that the fuel consumption of the motor vehicle is reduced in comparison to a journey to the stopping point with a propulsion of the motor vehicle by the combus- tion engine and subsequent braking by friction brake.
  • the energy balance of the motor vehicle is improved by the at least one operational measure.
  • each operational measure provides that the operation of the motor vehicle is changed by triggering the operating measure.
  • at least one operating measure to increase the efficiency and / or to increase the comfort and / or to reduce emissions and / or increase the safety (eg, premature activation of a brake light) is performed.
  • a confidence value is also determined by the holding model in addition to the probability value itself.
  • the confidence value indicates a degree of agreement of the holding model with a current driving situation.
  • the at least one operational measure is only initiated if the confidence value lies within a predetermined confidence interval.
  • the hold model indicate a likelihood value of how likely a stop operation is, it also expresses by the confidence value whether the hold model is properly configured for the current traffic situation. If, for example, the probability value is determined by the holding model as a function of a current traffic situation, it can be expressed by the confidence value how many statistical data or observations have already been collected in the holding model for the current traffic situation, that is to what extent the training data in Reference to the current traffic situation and / or time of day.
  • the confidence value can therefore be the extent or the amount of that in the Holding model considered enter training data.
  • the confidence value thus expresses the reliability of the statistical basis on which the holding model is formed. Due to the embodiment, there is the advantage that an unreliable for the current driving situation holding model can not lead to the at least one operating measure is triggered.
  • An embodiment provides that by the holding model to the respective stopping process additionally a time duration value is he averages, indicating how long the vehicle is expected to be in the stopping process.
  • a time duration value is he averages, indicating how long the vehicle is expected to be in the stopping process.
  • the control device is then started depending on the duration value at least a predetermined start-up measure. For example, at a stopping point with a traffic light, the duration value may indicate how long the current red phase, which has forced the vehicle to stop, will still take.
  • a starting measure prepares the starting process of the motor vehicle.
  • the Anfahrzel provides that for driving operation on a drive power in the motor vehicle be ready stands, which is greater than a predetermined minimum value.
  • the at least one driving measure comprises that a switched-off internal combustion engine of the motor vehicle is started.
  • the combus- tion engine is already started before the stopping process is completed.
  • a potential stopping point may be stored or mapped in a digital road map.
  • the respective position of at least one traffic light can be stored in such a digital road map.
  • An embodiment therefore provides that during at least one previous trip of the motor vehicle itself and / or at least one other motor vehicle at least one potential stopping point is respectively determined where the respective motor vehicle has already carried out at least a predetermined minimum number of stopping operations.
  • at least one stop point is defined by the fact that at least one motor vehicle has already observed or carried out a predetermined minimum number of stopping operations there.
  • relevant stopping points are automatically detected by means of the method. This is also possible if, for example, there is no traffic light and / or no stop sign installed.
  • the invention also includes a control device for a motor vehicle.
  • the control device according to the invention has a computing device which is set up to carry out an embodiment of the method according to the invention.
  • the computing device may be based on a microprocessor or microcontroller.
  • a program code can be provided, by means of which, when executed by the computing device, the method steps of the method according to the invention are carried out.
  • the control device may be configured as a control unit for the motor vehicle or as a composite of multiple controllers or as a server of the Internet. As a server, the control device can be coupled via a radio link with the motor vehicle.
  • the invention also includes a motor vehicle which has an embodiment of the control device according to the invention.
  • the motor vehicle according to the invention can be configured, for example, as a motor vehicle, that is, for example, as a passenger car or truck.
  • the invention also includes the combinations of the described embodiments.
  • FIG. 1 is a schematic representation of an embodiment of the motor vehicle according to the invention.
  • FIG. 2 is a flowchart showing an embodiment of the method according to the invention
  • Fig. 3 is a sketch for illustrating a Ausch
  • Fig. 4 is a sketch for illustrating a Ausity
  • a server determines an overall model for multiple vehicles
  • Fig. 6 is a sketch for illustrating a Ausity
  • the exemplary embodiment explained below is a preferred embodiment of the invention.
  • the described components of the embodiment each represent individual features of the invention that are to be considered independently of one another, which also each independently further develop the invention and thus also individually or in a different combination than the one shown as part of the invention.
  • the described embodiment can also be supplemented by further features of the invention already described.
  • Fig. 1 shows a motor vehicle 10.
  • the motor vehicle 10 may be, for example, a passenger car or a truck.
  • the motor vehicle 10 may have a control device 11, which may, for example, control an internal combustion engine 12 of the motor vehicle 10 in such a way that it can switch off and / or start the internal combustion engine 12 with a control signal 13.
  • the control device 11 can furthermore be coupled to at least one vehicle component 14, via which the control device 11 can determine, for example, a current driving operating state 15 of the motor vehicle 10 and / or can read or call up a current driving route 16 of the motor vehicle 10.
  • the route 16 may be estimated or planned.
  • the at least one vehicle component 14 may include, for example, a navigation system and / or a motor control device of the motor vehicle 10.
  • the control device 11 may further be coupled to a communication device 17 of the motor vehicle 10.
  • the communication device 17 may for example comprise a mobile radio module (for example 4G or 5G or UMTS) and / or a WLAN radio module (WLAN - wireless local area network).
  • a mobile radio module for example 4G or 5G or UMTS
  • WLAN radio module WLAN - wireless local area network
  • the control device 11 via a radio link 18 and, for example, a mobile network 19 with a server 20 at example, a server of the Internet, coupled.
  • a server can be a computer or a computer network.
  • the server 20 thus represents a data source in the sense of the invention.
  • the control device 11 can operate a holding model 21.
  • the holding model 21 may, for example, be a digital model which is operated on the basis of or by means of a computing device 22 of the control device 11; the holding model 21 is in particular a statistical model.
  • the control device 11 may for example provide a control unit of the motor vehicle 10 or a composite of a plurality of control units of the motor vehicle 10.
  • FIG. 2 illustrates how a method 23 is executed by the control device 11 on the basis of the holding model 21 or can be performed, on the basis of which, for example, the internal combustion engine 12 of the motor vehicle 10 can be switched to make operation of the motor vehicle 10 more efficient than without the controller.
  • the method 23 provides in a step S10 that, for example, on the basis of a digital road map 24 along the route 16, a preceding potential stopping point 25 is detected, at which it can come to a stopping operation of the motor vehicle 10.
  • the stopping point 25 may have a traffic light 26, at which the motor vehicle 10 would have to hold 26 during a red phase of the traffic light.
  • the traffic light 26 may be at an intersection 27.
  • the control device 11 can determine a probability value 28 by means of the holding model 21 to the stopping point 25, which indicates how great the likelihood probability is that at the stopping point 25 actually comes to a stopping process.
  • the holding model provides that the probability value 28 is a probability indication, which means that it can also have intermediate values between 0% and 100%.
  • it can be checked by the control device 11 whether the probability value lies within a predetermined value interval 29, for which it is assumed that this means that an actual occurrence of the stopping process takes place at the stopping point 25.
  • a stopping process is a stopping or stopping of the motor vehicle at a driving speed of 0 km / h.
  • the stopping process includes a stop of more than 5 seconds, preferably more than 10 seconds.
  • a predetermined operational measure 30 may be triggered by the control device 11 in a step S13
  • the operational measure 30 may comprise, for example, that the control signal 13 is generated to switch off the internal combustion engine 12. After the triggering the operational measure can be returned to step S10 again and another potential stop point can be determined.
  • the holding model 21 in addition to the probability value 28, the holding model 21 also outputs a confidence value 28 'which indicates to what degree or to what extent the probability value 28 describes the current driving situation correctly. For example, for a probability distribution stored in the holding model, it can be determined how large its database is. The size of the database can then be described by the confidence value 28 '. If the confidence value 28 'is not above a predetermined threshold value, it may be provided that the at least one operating measure 30 is omitted.
  • FIG. 3 illustrates how the holding model 21 can be configured or trained.
  • FIG. 3 shows the motor vehicle 10 during a preceding journey 31 that took place before the journey on which the description of the method 23 of FIG. 2 is based.
  • the motor vehicle 10 can pass several po tentielle stopping points 32, 33, 34, at each of which by the control device 11 observation data or Trai ningswill 35 can be determined, which indicate the driving state 15 at the respective potential stopping point 32, 33, 34 .
  • a traffic light 36 can be located at the respective stopping points 32, 33, 34.
  • a stop sign or a driveway trigger or cause a potential stop instead of a traffic light 36 but also, for example, a stop sign or a driveway trigger or cause a potential stop.
  • Fig. 3 illustrates how at the stopping point 32 a traffic light 36 in red phase causes a stopping process.
  • the training data 35 describe accordingly a driving state 15 in which the motor vehicle 10 stops.
  • This training data 35 can thus be used for the stopping point 32 in the holding model 21 in order to increase the probability of a stopping process at the stopping point 32, so that the probability value 28 is greater in the event of future travel of the motor vehicle 10 in the direction of the stopping point 32.
  • the control device 11 can recognize that the driving state of the motor vehicle 10 signals a passage without stopping at the stopping point 33.
  • the stopping model 21 may be adapted or confi gured for the stopping point 33, for a future passage past the stop point 33, the probability value 28 is smaller.
  • a traffic light 36 is again assumed in red phase.
  • the holding model 21 can be configured again based on the training data 25.
  • the holding model 21 may have further input parameters.
  • the holding model 21 may include the observation of a reference event 37 as an input parameter.
  • the stopping point 34 which is a start at the stopping point 32, that is a greening of the traffic light 36 at the stopping point 32, as a reference event 37 is taken as a basis and depending on a travel time T0 from the stopping point 32 to the stopping point 34 in the holding model 21, the probability value 28 for the stopping point 34 is determined.
  • the holding model 21 assumes that a reference event 37 is observed at the stopping point 32 or generally at a preceding stopping point, for example starting up after switching to a green phase at a traffic light 36, and then for a subsequent stopping point 34 the probability value 28 is determined as a function of how long ago it is that the approaching point of the motor vehicle 10 is located at the previous stopping point, so long as the vehicle T0 has lasted.
  • a so-called green wave which results along several traffic lights 36, can be modeled.
  • Stop 34 no synchronization of the holding model 21 with the traffic light 36 on Stop 34 itself forces, but the synchronization is done by observing a reference event 37 at a forward stopping point 32 or 33.
  • FIG. 4 illustrates how, in addition to the motor vehicle 10, further motor vehicles 38 can each update or train a local holding model 21 in an update or training 39, as described with reference to FIG. 3.
  • Each of the motor vehicles 10, 38 can then by means of a respective Kommuni kations worn 17 (see Fig. 1), the training data 35 and / or model data 40, which described the current holding model 21 itself, transmit to the server 20 or transmit or send out.
  • the motor vehicles 10, 38 can ride on different routes 41, 42.
  • an overall model 44 may be formed, which may represent a holding model for all routes 42, 43.
  • the overall model 44 may be updated or configured in an update or training 45, such as a local stop model in one of the vehicles 10, 38, based on the training data 35 and / or model data 40.
  • prognosis data 46 based on the global model 44 can be sent to the motor vehicles 10, 38, so that for each motor vehicle 10, 38 a prediction or prediction of a stop operation by the server 20 itself can be carried out.
  • Forecast data 46 may indicate, for example, a respective probability value 28.
  • model data 47 of the overall model 44 can be transmitted to the motor vehicles 10, 38. Based on the model data
  • the holding models 21 in the motor vehicles 10, 38 can be updated or adjusted. Then, in each motor vehicle 10, 38 independent of the server 20 is a local forecast
  • FIG. 5 illustrates once again how the motor vehicle 10 can also receive a holding model 21 in which such roads 43 are taken into account that have never been traveled by the motor vehicle 10.
  • Fig. 5 assumes that the motor vehicle 10 only the road 42 has traveled by the illustrated roads 42, 43.
  • the motor vehicle 10 and the other motor vehicles 38 in Fig. 5, for example, only one
  • Motor vehicle 38 shown transmit their training data 35 and / or model data 40 to the server 20, the server 20, the information on all roads 42, 43 combine.
  • FIG. 6 illustrates how, by sending the model data 47 of the model 44 to the motor vehicles 10, 38, the motor vehicle 10 is supplied with such model data 47 which also describe the roads 43.
  • the holding model 21 of the motor vehicle 10 may generate a probability value 28 (see FIG. 2) in step S11 even when the motor vehicle 10 is traveling on the corresponding road 43 for the first time.
  • Traffic light phases predicts a vehicle moving towards a traffic light (local system).
  • Several learning systems of different vehicles can be linked via a backend server or server for short (global system), so that the forecast availability and quality can be increased.
  • the drivetrain can be influenced during stopping processes in such a way that the lowest possible fuel consumption is achieved, ie. Sailing and recuperation phases are controlled in such a way that the vehicle comes to a standstill with as little fuel consumption as possible.
  • the stopping operations must be initiated in good time (provided that the driver cooperates), which in turn is only possible with a forecast of the traffic light phase.
  • the startup can be improved if it is known how long the vehicle is or when it can continue driving. This allows the engine start and start process to be initiated in good time.
  • the proposed concept is based on a minimized vehicle-implemented solution (local system), with maximum use of a server-based global solution as a basis for data collection and knowledge generation in the sense of a prognosis.
  • the system preferably does not learn the absolute time of a traffic light phase (eg traffic light phase on Mondays at 08:15:35), but learns the expected traffic light phase as a function of the previous traffic light phases and a reference event observed there (see Fig. 3). For example, it is learned how in a traffic light row A, B, C is the traffic light phase at the subsequent traffic lights B and C, which follow the traffic light A along a route. The system simply learns the red and green waves and stores how long to stop at the red lights.
  • a traffic light phase eg traffic light phase on Mondays at 08:15:35
  • the information is necessary as to whether the previous traffic lights have been held and how long the travel time T0 has been between the traffic lights A and B or A and C.
  • the forecasting system can be trained continuously, i. be continuously supplied with the training data. It needs to know if it is approaching an intersection and if the vehicle needs to stop. From this a probability of stopping can be calculated. Points of reference are a map with recorded traffic lights and stop signs. It is possible to use a track-accurate GPS / a localization, since each direction can have its own signaling.
  • the stops and connected amp colors are not necessarily detectable only with a camera and set such as to be anticipated (traffic light color detected), but also more easily e.g. can be detected on the basis of the driving condition. This not only red, but also green traffic lights learn.
  • the individual local vehicle-based solutions in the server can be linked and thus a global forecast can be made available for all routes.
  • different forecasting models can be trained and used depending on the traffic flow or time (time of day, day of the week).
  • Another advantage of the global forecast is that the forecast can also be made available for vehicles that have not yet created a local forecast model or for vehicles such as rental vehicles that are not moved on repeatedly traveled routes. It is a further advantage of the invention that arrest probabilities are generally calculated, not just limited

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Mathematical Physics (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Vehicle Engines Or Engines For Specific Uses (AREA)

Abstract

L'invention concerne un procédé (23) pour faire fonctionner un dispositif de commande (11) d'un véhicule automobile (10) pendant un trajet le long d'un itinéraire (16), au moins un point d'arrêt potentiel (25, 32, 33) situé devant l'itinéraire (16), 34) étant utilisé et, à l'approche du point d'arrêt (25, 32, 33, 34) potentiel respectivement déterminé, une valeur de probabilité (28) pour une probabilité d'une opération d'arrêt du véhicule automobile (10) au point d'arrêt (25, 32, 33, 34) étant déterminée à partir d'un modèle d'arrêt (21). Selon l'invention, un modèle statistique est exploité par le dispositif de commande (11) comme modèle d'arrêt (11), qui fournit également des valeurs intermédiaires entre 0% et 100% pour la valeur de probabilité (28), et, si la valeur de probabilité (28) se situe dans un intervalle de valeurs prédéterminé (29), qui définit l'occurrence probable du processus d'arrêt, au moins une mesure de fonctionnement prédéterminée (30) est effectuée, qui est prévue pour adapter une opération du véhicule automobile (10) au processus d'arrêt à chaque fois.
EP18814826.6A 2017-12-01 2018-11-29 Procédé pour faire fonctionner un dispositif de commande d'un véhicule automobile pour prédire un prochain arrêt, dispositif de commande et véhicule automobile Pending EP3717326A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102017221633.6A DE102017221633A1 (de) 2017-12-01 2017-12-01 Verfahren zum Betreiben einer Steuervorrichtung eines Kraftfahrzeugs, um einen nächsten Anhaltevorgang vorauszusagen, sowie Steuervorrichtung und Kraftfahrzeug
PCT/EP2018/083033 WO2019106100A1 (fr) 2017-12-01 2018-11-29 Procédé pour faire fonctionner un dispositif de commande d'un véhicule automobile pour prédire un prochain arrêt, dispositif de commande et véhicule automobile

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EP3717326A1 true EP3717326A1 (fr) 2020-10-07

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US (1) US11787406B2 (fr)
EP (1) EP3717326A1 (fr)
CN (1) CN111511624B (fr)
DE (1) DE102017221633A1 (fr)
WO (1) WO2019106100A1 (fr)

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US11565722B2 (en) * 2020-01-15 2023-01-31 The Regents Of The University Of Michigan Vehicle trajectory prediction near or at traffic signal
CN112092822B (zh) * 2020-09-07 2021-11-12 中国第一汽车股份有限公司 一种提示方法、装置、设备及存储介质
US11654913B2 (en) * 2021-03-04 2023-05-23 Southwest Research Institute Vehicle control based on infrastructure and other vehicles
DE102023201884B3 (de) 2023-03-02 2024-05-29 Volkswagen Aktiengesellschaft Verfahren zum Betreiben eines autonomen Fahrzeugs und autonomes Fahrzeug

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Publication number Priority date Publication date Assignee Title
EP1890110A3 (fr) * 2006-08-18 2013-04-24 Volkswagen Aktiengesellschaft Procédé de détermination d'une stratégie de conduite optimale d'un véhicule automobile et dispositif équipé de manière correspondante tout comme affichage associé ainsi que véhicule automobile associé
WO2008113836A1 (fr) 2007-03-20 2008-09-25 Continental Teves Ag & Co. Ohg Procédé et dispositif de commande et/ou de régulation prédictive d'un entraînement hybride dans un véhicule automobile et véhicule automobile hybride
JP5071464B2 (ja) 2009-11-04 2012-11-14 株式会社デンソー 車両制御装置
DE102011004425A1 (de) * 2011-02-18 2012-08-23 Bayerische Motoren Werke Aktiengesellschaft Schätzen des Status einer Ampelanlage
EP2781722B1 (fr) * 2011-11-14 2018-06-13 Toyota Jidosha Kabushiki Kaisha Appareil d' aide a la conduite
US9759573B2 (en) * 2014-08-29 2017-09-12 Ford Global Technologies, Llc Route based energy consumption estimation using physical models
DE102015212027A1 (de) * 2015-06-29 2016-12-29 Bayerische Motoren Werke Aktiengesellschaft Verfahren und Vorrichtung zum automatischen Ermitteln von Verkehrsregelungen an Straßenkreuzungen
DE102015008423B4 (de) 2015-06-30 2018-11-22 Audi Ag Verfahren zum Betrieb eines Fahrzeugeffizenzsystems eines Kraftfahrzeugs und Kraftfahrzeug
DE102015219232B3 (de) 2015-10-06 2017-04-06 Continental Automotive Gmbh Verfahren zur Steuerung von Fahrzeugfunktionen eines Linienfahrzeugs, Computerprogrammprodukt und Linienfahrzeug
GB2545261A (en) * 2015-12-11 2017-06-14 Jaguar Land Rover Ltd Control system and method of controlling a driveline
DE102016204144A1 (de) 2016-03-14 2017-09-14 Robert Bosch Gmbh Verfahren und Steuereinrichtung zur Steuerung und/oder Regelung eines Funktionssystems in einem Kraftfahrzeug
DE102017208646A1 (de) * 2017-05-22 2018-11-22 Audi Ag Verfahren zum Betreiben eines Kraftfahrzeugs sowie ein Kraftfahrzeug

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US20210171040A1 (en) 2021-06-10
WO2019106100A1 (fr) 2019-06-06
CN111511624B (zh) 2024-05-24
CN111511624A (zh) 2020-08-07
DE102017221633A1 (de) 2019-06-06
US11787406B2 (en) 2023-10-17

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