WO2020193861A1 - Positionnement de véhicule - Google Patents

Positionnement de véhicule Download PDF

Info

Publication number
WO2020193861A1
WO2020193861A1 PCT/FI2020/050189 FI2020050189W WO2020193861A1 WO 2020193861 A1 WO2020193861 A1 WO 2020193861A1 FI 2020050189 W FI2020050189 W FI 2020050189W WO 2020193861 A1 WO2020193861 A1 WO 2020193861A1
Authority
WO
WIPO (PCT)
Prior art keywords
vehicle
information
dynamic model
road
data
Prior art date
Application number
PCT/FI2020/050189
Other languages
English (en)
Inventor
Kimmo ERKKILÄ
Jarmo Leino
Original Assignee
Eee Innovations Oy
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 Eee Innovations Oy filed Critical Eee Innovations Oy
Publication of WO2020193861A1 publication Critical patent/WO2020193861A1/fr

Links

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/10Estimation 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 vehicle motion
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/02Estimation 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
    • B60W40/06Road conditions
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/12Estimation 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 parameters of the vehicle itself, e.g. tyre models
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07CTIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C5/00Registering or indicating the working of vehicles
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07CTIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C5/00Registering or indicating the working of vehicles
    • G07C5/08Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
    • G07C5/0808Diagnosing performance data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network

Definitions

  • the present application relates to the field of computer systems, and more particularly to a computer-implemented method and an apparatus for determining a position of a vehicle.
  • Vehicle positioning is an important service for various users.
  • the positioning may be based on utilizing satellites that provide positioning signals for a receiver installed in a vehicle. Based on the received positioning signals it is possible to establish a current location of the vehicle and to display the location for a driver, for example, by using a map application.
  • One of the problems associated with the satellite based positioning service is that the positioning is not very accurate and the accuracy varies depending on the surrounding conditions (for example, tall buildings may reduce the accuracy). Further, satellite based positioning works well only outdoors, therefore making it unusable indoors.
  • a computer-implemented method for positioning a vehicle comprises applying a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information originating from at least one information bus of the vehicle, the status information providing real time status information about the vehicle during the use of the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information providing characteristics associated with the vehicle, obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three- dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data, the dynamic model enabling at least one of an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle; calculating, based on
  • a computer-implemented method for positioning a vehicle comprises applying a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information, obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data; calculating, based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; calculating, based on the dynamic model of the vehicle, a momentary track width; calculating, based on the effective travel distance of a wheel of the vehicle and the momentary track width, a momentary direction of the vehicle; and calculating, based on the effective travel distance
  • the status information comprises at least one of a motor power, tyre speeds, a steering wheel position, vehicle system information, traction control information, vehicle stabilization system information and anti-lock braking system information.
  • obtaining, based on vehicle identity information, vehicle dynamics information comprises obtaining initial vehicle dynamics information associated with a model or type of the vehicle from at least one external data source.
  • vehicle dynamics information comprises obtaining supplemental vehicle dynamics information based on real-time vehicle dynamics data obtained from the vehicle.
  • vehicle identity information may be the real vehicle identification number (VIN) information of the vehicle, or plain unique reference which can be used to match the vehicle history and calibration values together.
  • the road characteristics data comprises at least one of road quality data, road irregularity data and data about local deviations associated with the road.
  • the method further comprises combining the dynamic model with the road characteristics data to enhance the calculation of the position of the vehicle.
  • the three-dimensional road data comprises road inclination data
  • the method further comprises combining the dynamic model with the road inclination data to enhance the calculation of the position of the vehicle.
  • an apparatus for positioning a vehicle comprises at least one processor and at least one memory connected to the at least one processor.
  • the at least one memory stores program instructions that, when executed by the at least one processor, cause the apparatus to apply a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information originating from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle during the use of the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information providing characteristics associated with the vehicle, obtain map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data, the dynamic model enabling at least one of an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle; calculate based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; calculate, based on the dynamic model of the vehicle, a momentary track width;
  • an apparatus for positioning a vehicle comprises at least one processor and at least one memory connected to the at least one processor.
  • the at least one memory stores program instructions that, when executed by the at least one processor, cause the apparatus to apply a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information, obtain map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data; calculate based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; calculate, based on the dynamic model of the vehicle, a momentary track width; calculate, based on the effective travel distance of a wheel of
  • the status information comprises at least one of a motor power, tyre speeds, a steering wheel position, vehicle system information, traction control information, vehicle stabilization system information and anti-lock braking system information.
  • obtaining, based on vehicle identity information, vehicle dynamics information comprises obtaining initial vehicle dynamics information associated with a model or type of the vehicle from at least one external data source.
  • vehicle dynamics information comprises obtaining supplemental vehicle dynamics information based on real-time vehicle dynamics data obtained from the vehicle.
  • vehicle identity information may be the real vehicle identification number (VIN) information of the vehicle, or plain unique reference which can be used to match the vehicle history and calibration values together.
  • the road characteristics data comprises at least one of road quality data, road irregularity data and data about local deviations associated with the road.
  • the at least one memory stores program instructions that, when executed by the at least one processor, cause the apparatus to combine the dynamic model with the road characteristics data to enhance the calculation of the position of the vehicle.
  • the three-dimensional road data comprises road inclination data
  • the at least one memory stores program instructions that, when executed by the at least one processor, cause the apparatus to combine the dynamic model with the road inclination data to enhance the calculation of the position of the vehicle.
  • a computer program comprises program code which when executed by at least one processor, performs the method of the first aspect.
  • a computer-readable medium comprises a computer program comprising program code which when executed by at least one processor, performs the method of the first aspect.
  • an apparatus for positioning a vehicle comprises means for applying a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information originating from at least one information bus of the vehicle, the status information providing real time status information about the vehicle during the use of the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information providing characteristics associated with the vehicle, obtain map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three- dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data, the dynamic model enabling at least one of an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle; means for calculating based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; means for calculating, based on the dynamic model of the vehicle, a moment
  • an apparatus for positioning a vehicle comprises means for applying a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information, obtain map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three- dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data; means for calculating based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; means for calculating, based on the dynamic model of the vehicle, a momentary track width; means for calculating, based on the effective travel distance of a wheel of the vehicle and the momentary track width, a momentary direction of the vehicle; and means for calculating, based on the effective
  • an apparatus for positioning a vehicle comprises at least one processor configured to apply a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information originating from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle during the use of the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information providing characteristics associated with the vehicle, obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two- dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data, the dynamic model enabling at least one of an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle; calculate based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; calculate, based on the dynamic model of the vehicle, a moment
  • an apparatus for positioning a vehicle comprises at least one processor configured to apply a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information, obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data; calculate based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; calculate, based on the dynamic model of the vehicle, a momentary track width; calculate, based on the effective travel distance of a wheel of the vehicle and the momentary track width, a momentary direction of the vehicle; and calculate, based on the effective travel distance of the wheel
  • FIG. 1 illustrates a block diagram representing information based on which it is possible to determine and model behavior of a vehicle.
  • FIG. 2 illustrates a flow diagram of a method for modelling dynamics of a vehicle.
  • FIG. 3 illustrates calculation of the change of wheel normal load caused by the road longitudinal inclination in front and rear axles.
  • FIG. 4 illustrates a computer-implemented method for positioning a vehicle.
  • FIGS. 5A and 5B illustrate graphs associated with a turning vehicle.
  • FIG. 6 illustrates a system diagram depicting an exemplary apparatus according to an aspect.
  • a disclosure in connection with a described method may also hold true for a corresponding device or system configured to perform the method and vice versa.
  • a corresponding device may include a unit or other means to perform the described method step, even if such unit is not explicitly described or illustrated in the figures.
  • a corresponding method may include a step performing the described functionality, even if such step is not explicitly described or illustrated in the figures.
  • FIG. 1 illustrates a block diagram representing information based on which it is possible to determine and model behavior of a vehicle.
  • Vehicle status information 100 refers to information that can be obtained or can originate from the vehicle itself, for example, via one or more information buses of the vehicle while the vehicle is in use.
  • the vehicle status information comprises, for example, at least one of motor power, tyre speeds, a steering wheel position, vehicle system information, traction control information, vehicle stabilization system information and anti-lock braking system information.
  • Vehicle dynamics information 102 may be obtained based on vehicle identity information, for example, from one or more external data sources.
  • the vehicle dynamics information 102 may provide characteristics associated with the vehicle. The characteristics may comprise initial values, for example, for a mass of the vehicle, powertrain efficiency coefficient or map, a track width, a wheelbase, location of the center of gravity, and the moment of inertia along different axes of the vehicle and the moment of inertia associated with rotating masses. If no vehicle specific dynamics information is not available, it is possible to use vehicle dynamics information that is common for this vehicle type. When the vehicle is used, the vehicle dynamics information may be updated based on analysis of the behavior of the vehicle. Further, vehicle dynamics information determined for a specific vehicle may be used as preliminary knowledge for other similar vehicles.
  • the vehicle identity information may be the real vehicle identification number (VIN) information of the vehicle, or plain unique reference which can be used to match the vehicle history and calibration values together.
  • Map data 104 may represent road characteristics of roads of a geographical area, and the map data 104 may comprise two-dimensional road map data, three-dimensional road map data associated with the roads, and/or road characteristics data.
  • the three-dimensional road map data may comprise information, for example, about road height data and road inclination data.
  • the road characteristics data may comprise at least one of road quality data, road irregularity data and data about local deviations associated with the road.
  • the road characteristics data may comprise, for example, other typical dynamic behaviour changes that can be statistically recognized by various vehicles at the same locations. For example, if a road is rutted, a weight transfer of a vehicle can be considered as“normal” if several different vehicles experience the same weight transfer.
  • pits, rail locations or other road imperfections of a road are characteristics that have an effect on how a vehicle should behave based on a current dataset associated with the vehicle.
  • vehicle dynamics information 102 and the map data 104 it is possible to determine a dynamic model for the vehicle.
  • the dynamic model may then enable an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle.
  • updated map data may be subsequently received and the updated map data may be used in determining or updating the dynamic model of the vehicle.
  • the dynamic model may be calculated and/or updated by a vehicle-mounted apparatus.
  • the dynamic model may be calculated and/or updated by a network-based service that may receive information from one or more vehicles.
  • the illustrated solution enables a fusion of the vehicle status information 100 obtained from the vehicle and the map data.
  • the map data can be enriched based on the vehicle status information 100.
  • FIG. 2 illustrates a computer-implemented method for modelling dynamics of a vehicle.
  • the vehicle may be any vehicle travelling on a road, for example, an autonomous vehicle, a passenger car, a truck, a motorcycle etc.
  • status information is obtained from at least one information bus of the vehicle, the status information providing status information or real-time status information about the vehicle.
  • vehicle dynamics information representing vehicle dynamics is obtained based on vehicle identity information.
  • map data representing road characteristics of roads of a geographical area comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data is obtained.
  • behavior of the vehicle is analyzed based on the status information and the vehicle dynamics information.
  • a dynamic model for the vehicle is calculated by comparing the behavior of the vehicle to the map data.
  • the dynamic model of the vehicle can be used in various applications in which an accurate vehicle representation is needed. For example, based on the dynamic model, it is possible to calculate a presumed behavior of the vehicle in various driving conditions. If an actual behavior of the vehicle deviates from the presumed behavior of the vehicle, this is caused either by changes in driving conditions or changes in the vehicle.
  • the dynamic model of the vehicle may define a set of vehicle-specific calibration parameters. These calibration parameters may represent how the vehicle behaves in various driving situations.
  • the dynamic model of the vehicle may involve a set of various parameters or calibration parameters, for example, one or more of the following: 1) a mass of the vehicle, 2) powertrain efficiency coefficient or map, 3) a track width, 4) a wheelbase, 5) location of the center of gravity, 6) the moment of inertia along different axes of the vehicle and the moment of inertia associated with rotating masses, 7) effective rolling circumferences of the wheels, 8) an effect of the circumferential force of a wheel to the rolling circumferences, and 9) overall flexibility in longitudinal and lateral directions in weight of the transition situations caused, for example, by the wheels, the car chassis structure and the car body.
  • various parameters or calibration parameters for example, one or more of the following: 1) a mass of the vehicle, 2) powertrain efficiency coefficient or map, 3) a track width, 4) a wheelbase, 5) location of the center of gravity, 6) the moment of inertia along different axes of the vehicle and the moment of inertia associated with rotating masses,
  • the mass of the vehicle may be obtained from an external data source, it can be manually input or a mass estimation may be used based on the vehicle type.
  • the mass of the vehicle can be made more accurate by comparing the effect of the energy produced by a motor of the vehicle to state of motion of the vehicle, taking into account also, for example, at least one of changes in vehicle speed, altitude changes, the amount of work performed by the motor of the vehicle, efficiencies, driving resistances and road quality factors.
  • A frontal area
  • the mass of the vehicle may be estimated as follows:
  • Powertrain efficiency information may be obtained from one or more external data sources, manually or based on the vehicle type. Later, the information may be made more accurate by multivariate analysis or statistical analysis. Track width information may be obtained from one or more external data sources, manually or based on the vehicle type. Later, the information may be made more accurate by multivariate analysis or statistical analysis.
  • Wheelbase information may be obtained from one or more external data sources, manually or based on the vehicle type. Later, the information may be made more accurate by multivariate analysis or statistical analysis.
  • Information about the location of the center of gravity may be obtained from one or more external data sources, manually or based on the vehicle type. Later, the information may be made more accurate by multivariate analysis or statistical analysis.
  • Information about the moment of inertia along different axes of the vehicle and the moment of inertia associated with rotating masses may be obtained from one or more external data sources, manually or based on the vehicle type. Later, the information may be made more accurate by multivariate analysis or statistical analysis.
  • Effective rolling circumferences of the wheels may be calculated for each wheel by comparing the travelled distance to each other and to map data in chosen periods. For each wheel a computational dependency tied to the normal force of the wheel is generated. A momentary normal force of the wheel takes into account a dynamic mass shift of the vehicle, also taking into account road characteristics, for example, road inclinations to different directions. The effect of speed may also be taken into account.
  • the effect of the circumferential force of a wheel to the rolling circumferences of the wheels is estimated by comparing speed of rotation differences with each other with different tractive forces.
  • the estimation may also take into account road quality characteristics and friction.
  • Flexibility of the wheels and the chassis in longitudinal and lateral directions in weight transition situations may be determined for each and for each wheel type by using initial values or by searching the values from a library for a similar vehicle and wheel type.
  • the effects of the weight transition in longitudinal and lateral directions are estimated separately because a wheel of the vehicle and chassis structures act differently with forces having different directions.
  • Coefficients representing the dynamics indicate both the change caused by the weight shift to the effective travelling device of each wheel and changes caused by the flexibility to the effective travelling distance of the wheel.
  • the location of the effective contact point affects, for example, to the track width and wheelbase.
  • the map data is utilized, for example, by comparing a turning degree of the vehicle according to the dynamic model in a curve to an expected turning degree based on the map data.
  • FIG. 3 illustrates calculation of the change of wheel normal load caused by the road longitudinal inclination in front and rear axles. Based on FIG. 3, the following equations can be formed:
  • lateral inclination and longitudal and lateral accelerations ay be calculated similarly.
  • FIG. 4 illustrates a computer-implemented method for positioning a vehicle.
  • the vehicle may be any vehicle travelling on a road, for example, an autonomous vehicle, a passenger car, a truck, a motorcycle etc.
  • a dynamic model associated with a vehicle discussed above is applied.
  • the dynamic model has been determined by obtaining status information originating from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle during the use of the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information providing characteristics associated with the vehicle, obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data, the dynamic model enabling at least one of an estimation of the performance of the vehicle, observation of changes associated with the vehicle and observation of changes in driving conditions of the vehicle.
  • an effective travel distance of a wheel of the vehicle is calculated based on the dynamic model of the vehicle.
  • a momentary track width is calculated based on the dynamic model of the vehicle.
  • a momentary direction of the vehicle is calculated based on the effective travel distance of a wheel of the vehicle and the momentary track width.
  • a position of the vehicle is calculated based on the effective travel distance of the wheel and the momentary direction of the vehicle.
  • the three-dimensional map data may comprise also road inclination.
  • the position determination can be made more accurate. For example, an effect of the road inclination to a projection of the track width can be taken into account.
  • exemplary equations are presented for the rear axle. Equations for the front axle may be formed similarly.
  • a starting value for a wheel speed difference between left and right sides by a wheel travel is
  • a starting value for wheel speed change per speed can be represented as follows:
  • the mass detection may be performed using the previously presented equations for the mass of the vehicle.
  • TFC type and suspension flex in z direction (compression flex)
  • TW dyn dynamic track width
  • the illustrated solution for determining the position accurately may be used in vehicle navigation and especially in real-time navigation and in real-time three-dimensional navigation.
  • the illustrated solution can also be utilized in locations where a satellite position based signal, for example, a GPS signal, is weak on non-existent. These locations may include, for example, closed parking lots, blind spots due to buildings, tunnels and quarries. Further, the illustrated solution may provide a location service in applications in which a single location signal is not sufficient, for example, in autonomous vehicles, metros and trains.
  • FIG. 6 illustrates a system diagram depicting an exemplary apparatus 600 including a variety of optional hardware and software components, shown generally at 612. Any components 612 in the apparatus can communicate with any other component, although not all connections are shown, for ease of illustration.
  • the apparatus 600 can be any of a variety of computing devices (for example, a computer, a cloud based server etc.) and can allow two-way communications with one or more communications networks, such as the Internet.
  • the illustrated apparatus 600 can include one or more controllers or processors 602 (e.g., signal processor, microprocessor, ASIC, or other control and processing logic circuitry) for performing such tasks as signal coding, data processing, input/output processing, power control, and/or other functions.
  • An operating system 608 can control the allocation and usage of the components 612 and support for one or more application programs 610.
  • the application programs can include common computing applications (e.g., server software), or any other computing application.
  • the illustrated apparatus 600 can include a memory 604.
  • the memory 604 can include non-removable memory and/or removable memory.
  • the non-removable memory can include RAM, ROM, flash memory, a hard disk, or other well-known memory storage technologies.
  • the removable memory can include flash memory or other well-known memory storage technologies.
  • the memory 604 can be used for storing data and/or code for running the operating system 608 and the applications 610.
  • Example data can include web pages, text, images, sound files, video data, or other data sets to be sent to and/or received from one or more network servers or other devices via one or more wired or wireless networks.
  • the apparatus 600 can further include at least one physical connector, which can be a USB port, IEEE 1394 (FireWire) port, and/or RS-232 port etc.
  • at least one physical connector can be a USB port, IEEE 1394 (FireWire) port, and/or RS-232 port etc.
  • the illustrated components 612 are not required or all-inclusive, as any components can deleted and other components can be added.
  • the apparatus 600 may be configured to implement the various features, examples and embodiments illustrated in FIGS. 1-4 partially or completely.
  • the functionality described herein can be performed, at least in part, by one or more computer program product components such as software components.
  • the processor 602 may be configured by the program code which when executed performs the examples and embodiments of the operations and functionality described.
  • the functionality described herein can be performed, at least in part, by one or more hardware logic components.
  • illustrative types of hardware logic components include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Program-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), Graphics Processing Units (GPUs).
  • FPGAs Field-programmable Gate Arrays
  • ASICs Program-specific Integrated Circuits
  • ASSPs Program-specific Standard Products
  • SOCs System-on-a-chip systems
  • CPLDs Complex Programmable Logic Devices
  • GPUs Graphics Processing Units
  • one or more of the disclosed elements or components of the apparatus 600 may constitute means for applying a dynamic model associated with the vehicle, the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle, obtaining, based on vehicle identity information, vehicle dynamics information, obtain map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three- dimensional road map associated with the roads, and road characteristics data, analyzing behavior of the vehicle based on the status information and the vehicle dynamics information, and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data; means for calculating based on the dynamic model of the vehicle, an effective travel distance of a wheel of the vehicle; means for calculating, based on the dynamic model of the vehicle, a momentary track width; means for calculating, based on the effective travel distance of a wheel of the vehicle and the momentary track width, a momentary direction of the vehicle; and means for calculating, based on the effective travel distance
  • the functionality of the apparatus 600 may be implemented by program instructions stored on a computer readable medium.
  • the program instructions when executed, cause the computer, processor or the like, to perform the disclosed steps or functionality.
  • the computer readable medium can be any medium, including non-transitory storage media, on which the program is stored such as a Blu-Ray disc, DVD, CD, USB (flash) drive, hard disc, server storage available via a network, a ROM, a PROM, an EPROM, an EEPROM or a Flash memory having electronically readable control signals stored thereon which cooperate or are capable of cooperating with a programmable computer system such that an embodiment of at least one of the inventive methods is performed.
  • An embodiment of the invention comprises or is a computer program comprising program code for performing any of the methods described herein, when executed on a computer.
  • Another example of the invention comprises or is a computer readable medium comprising a program code that, when executed by a processor, causes an apparatus to perform any of the methods described herein.
  • the apparatus 600 comprises a vehicle navigator apparatus.
  • the vehicle navigator device may receive the status information from at least one information bus of the vehicle. Then, the vehicle navigator device may comprise the dynamical model of the vehicle, and the dynamical model may calculate the actual direction and speed of the vehicle based on the vehicle dynamics information and the map data.
  • the vehicle navigator apparatus always stays on a correct driving lane. Further, the illustrated solution may also remove the problem of determining of a correct direction, for example, when driving in cities.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Navigation (AREA)
  • Traffic Control Systems (AREA)

Abstract

Selon un aspect, l'invention concerne un procédé mis en œuvre par ordinateur pour le positionnement d'un véhicule. Le procédé comprend l'application d'un modèle dynamique associé au véhicule (400), le modèle dynamique ayant été déterminé par obtention d'informations d'état à partir d'au moins un bus d'informations du véhicule, les informations d'état fournissant des informations d'état en temps réel concernant le véhicule (200), obtention, sur la base d'informations d'identité de véhicule, des informations de dynamique de véhicule (202), obtention des données de carte représentant des caractéristiques de routes d'une zone géographique, les données de carte comprenant des données de carte routière bidimensionnelle, une carte routière tridimensionnelle associée aux routes, et des données de caractéristiques de route (204), analyse du comportement du véhicule sur la base des informations d'état et des informations de dynamique de véhicule (206), et calcul d'un modèle dynamique pour le véhicule en comparant le comportement du véhicule aux données de carte (208) ; calcul, sur la base du modèle dynamique du véhicule, d'une distance de déplacement effective d'une roue du véhicule (402) ; calcul, sur la base du modèle de dynamique de véhicule, d'une largeur de piste momentanée (404) ; calcul, sur la base de la distance de déplacement effective d'une roue du véhicule et de la largeur de piste momentanée, d'une direction momentanée du véhicule (406) ; et calcul, sur la base de la distance de déplacement effective de la roue et de la direction momentanée du véhicule, d'une position du véhicule (408).
PCT/FI2020/050189 2019-03-25 2020-03-25 Positionnement de véhicule WO2020193861A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20195222A FI129920B (en) 2019-03-25 2019-03-25 Positioning of a vehicle
FI20195222 2019-03-25

Publications (1)

Publication Number Publication Date
WO2020193861A1 true WO2020193861A1 (fr) 2020-10-01

Family

ID=72611112

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/FI2020/050189 WO2020193861A1 (fr) 2019-03-25 2020-03-25 Positionnement de véhicule

Country Status (2)

Country Link
FI (1) FI129920B (fr)
WO (1) WO2020193861A1 (fr)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2541203A1 (fr) * 2011-06-30 2013-01-02 Furuno Electric Company Limited Serveur de retours d'expérience de carte routière pour navigation de véhicule avec modes à l'estime et GPS étroitement liés
US20150266455A1 (en) * 2013-12-06 2015-09-24 Christopher Kenneth Wilson Systems and Methods for Building Road Models, Driver Models, and Vehicle Models and Making Predictions Therefrom
US20180154723A1 (en) * 2013-03-15 2018-06-07 ClearMotion, Inc. Self-driving vehicle with integrated active suspension

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2541203A1 (fr) * 2011-06-30 2013-01-02 Furuno Electric Company Limited Serveur de retours d'expérience de carte routière pour navigation de véhicule avec modes à l'estime et GPS étroitement liés
US20180154723A1 (en) * 2013-03-15 2018-06-07 ClearMotion, Inc. Self-driving vehicle with integrated active suspension
US20150266455A1 (en) * 2013-12-06 2015-09-24 Christopher Kenneth Wilson Systems and Methods for Building Road Models, Driver Models, and Vehicle Models and Making Predictions Therefrom

Also Published As

Publication number Publication date
FI20195222A1 (en) 2020-09-26
FI129920B (en) 2022-10-31

Similar Documents

Publication Publication Date Title
Viehweger et al. Vehicle state and tyre force estimation: demonstrations and guidelines
Singh et al. Literature review and fundamental approaches for vehicle and tire state estimation
FI129919B (en) Control of the condition of the vehicle
CN108820042B (zh) 一种自动驾驶方法及装置
Wang et al. Tire–road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation
Tin Leung et al. A review of ground vehicle dynamic state estimations utilising GPS/INS
CN102529976B (zh) 一种基于滑模观测器的车辆运行状态非线性鲁棒估计方法
Li et al. Comparative study of vehicle tyre–road friction coefficient estimation with a novel cost-effective method
CN103434511A (zh) 一种车速与道路附着系数的联合估计方法
US10684622B2 (en) Vehicle dynamics monitor for autonomous vehicle
Beal Rapid road friction estimation using independent left/right steering torque measurements
Van Gennip et al. Parameter identification and validation for combined slip tire models using a vehicle measurement system
Jiang et al. Real-time estimation and prediction of tire forces using digital map for driving risk assessment
WO2020193860A1 (fr) Modélisation de la dynamique d'un véhicule
EP4327052A1 (fr) Systèmes et procédés d'assurance de qualité de carte assistée par simulation dans un contexte de véhicule autonome
US20220072954A1 (en) Animation to visualize wheel slip
Herzfeld et al. Collision avoidance by utilizing dynamic road friction information
WO2020193861A1 (fr) Positionnement de véhicule
Coyte et al. Decision tree assisted EKF for vehicle slip angle estimation using inertial motion sensors
Kissai et al. Importance of vertical dynamics for accurate modelling, friction estimation and vehicle motion control
FI129942B (en) Improvement of map data
Caldas et al. Eco-cruise NMPC control for autonomous vehicles
US10414409B2 (en) Method for determining a dangerous driving indicator of a vehicle
Jiang et al. Estimation and prediction of vehicle dynamics states based on fusion of OpenStreetMap and vehicle dynamics models
Wang et al. Nonlinear observers of tire forces and sideslip angle estimation applied to road safety: Simulation and experimental validation

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20778809

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20778809

Country of ref document: EP

Kind code of ref document: A1