GB2571103A

GB2571103A - An autonomous vehicle system

Info

Publication number: GB2571103A
Application number: GB1802511.4A
Authority: GB
Inventors: Matteo Bianchi Gian; William Bentley Alexander; Bui Stefan; James Steight Henry
Original assignee: Jaguar Land Rover Ltd
Current assignee: Jaguar Land Rover Ltd
Priority date: 2018-02-16
Filing date: 2018-02-16
Publication date: 2019-08-21
Anticipated expiration: 2038-02-16
Also published as: GB2571103B; DE102019201865A1; GB201802511D0

Abstract

An autonomous surface measurement vehicle 100 for taking static surface measurements comprises a positioning mechanism 140 arranged to receive position information relating to a position of the surface to be measured and a localisation mechanism 130 to record a measurement position of the vehicle. The measurement position of the vehicle is altered by ground engagements 180 in dependence on the position information. First and second measurement devices 150, 160 obtain first and second measurements at first and second feature sizes of the driving surface respectively. The first measurement device may comprise one or more macro-texture optical sensors such as a LiDAR sensor or monocular or stereoscopic sensor. The second measurement device may comprise one or more micro-texture optical sensors. The localisation mechanism may comprise an inertial measurement unit such as an accelerometer, gyroscope or magnetometer. Also claimed is a controller for an autonomous vehicle and its method of operation. A method of creating a driving surface model comprises the step of receiving data from an autonomous vehicle, whilst a driving surface model representative of a driving surface derived from a combination of a plurality of measurement sets.

Description

AN AUTONOMOUS VEHICLE SYSTEM

TECHNICAL FIELD

The present disclosure relates to an autonomous surface measurement vehicle, a method of operating an autonomous surface measurement vehicle and particularly but not exclusively to a method of creating a driving surface model and a driving surface model. Aspects of the invention relate to an autonomous surface measurement vehicle, to a method, to a driving surface model.

BACKGROUND OF THE INVENTION

In modelling driving surfaces in order to virtually test vehicle dynamics, it is desirable to accurately reproduce real world driving surface conditions. Collecting information about the microtexture, macrotexture, megatexture and surface roughness features accurately is useful as each of the different feature sizes affects the vehicle dynamics in a different way. Microtexture features affect tyre wear and dry weather friction. Macrotextures affect tyreroad noise, wet weather friction and splash and spray, as well as to some extent rolling resistance and in-vehicle noise. Megatextures also affect rolling resistance and in-vehicle noise, as well as ride quality and vehicle wear. Surface roughness further affects rolling resistance, ride quality and vehicle wear.

Multiple wavelength ranges of measurements are used in order to measure different feature sizes of the driving surface. Different feature sizes of the driving surface affect different facets of a vehicle differently, and so to produce a beneficial driving surface model, accurately recording feature sizes down to 0.1 micrometres is important.

The driving surface model is representative of the microtexture, macrotexture, megatexture and surface roughness categories of driving surface as defined by the Permanent International Association of Road Congresses (PIARC). Each of the categories corresponds to a range of surface feature sizes, where microtexture comprises features from approximately 1 micrometre to approximately 1 millimetre, macrotexture comprises features from approximately 1 millimetre to approximately 100 millimetres, megatexture comprises features from approximately 100 millimetres to approximately 1 metre and surface roughness comprises features from approximately 1 metre to 100 metres.

Tyre wear is the amount of degradation that affects a tyre over its envisaged lifespan, as well as the rate at which the tyre degrades. When modelling new tyre compounds, or tyre compounds on new vehicles, the level of tyre wear needs to be understood.

Dry weather friction is the amount of friction that exists between the tyre and the driving surface, when the surface is not wet. This varies due to differing tyre compounds and tyre tread patterns, as well as from driving surface to driving surface. Modelling the behaviour of certain tyres on certain surfaces is key to choosing the correct tyre or tyre compound for a particular vehicle.

Tyre-road noise is the amount of noise that is generated by the tyre at a given speed due to its contact with the driving surface. Different driving surfaces will produce tyre-road noise at different frequencies, the understanding of which is important to the design of Noise, Vibration and Harshness (NVH) systems on the vehicle.

Wet weather friction is the amount of friction that exists between the tyre and the driving surface, when the surface is wet. This varies due to differing tyre compounds and tyre tread patterns, as well as from driving surface to driving surface. Modelling the behaviour of certain tyres on certain surfaces is key to choosing the correct tyre or tyre compound for a particular vehicle. Surface wetness affects the tyre in different ways, both as a result of potential aquaplaning or hydroplaning and as a result of a reduction in adhesion to the driving surface.

Splash and spray is the amount of water that will leave a surface as a vehicle passes over it, and the quantity of spray generated can be as a direct result of tyre vibrations and tyre centrifugal forces.

Rolling resistance, sometimes referred to as rolling friction or rolling drag, is the amount of force resisting the motion of the tyre in contact with a driving surface. Again, this varies for different tyre compounds and tread patterns, and must be accurately modelled for each driving surface in order for a model to be beneficial.

In-vehicle noise is related to tyre-road noise, in that it is an amount of noise generated as the vehicle moves over a particular driving surface. The in-vehicle noise will be reduced by NVH systems on the vehicle, but the frequency of the noise will vary in dependence on the driving surface, and as such modelling the driving surface to understand the frequency of the noise is important.

Vehicle wear and ride quality are important factors that are dependent on the larger sized features. Vehicle wear determines how long components on the vehicle will last, whilst ride quality determines the comfort level of the occupants whilst driving surfaces are traversed.

Manually positioning sensing equipment at different measurement positions is both laborious and time consuming, as well as requiring human effort to position the sensing equipment.

Potential inaccuracies in measurement alignment, recording and positioning are also likely to be introduced by utilising human measurement techniques.

It is known to provide a vehicle mounted LiDAR scanner suitable for measuring driving surfaces. It is also known to provide a rolling surface profiler for measure surface profile and roughness characteristics. Such devices may be positioned manually across a driving surface to be modelled, enabling measurements to be taken at particular feature sizes of the driving surface. These devices will take measurements at a single feature size, and will require a further device suitable for taking a measurement at a further feature size. Using multiple measurement devices, inaccuracies in the recorded data will be introduced, due to the unknown offset of the measurement positions. Further to this, requiring an operator to manually position the plurality of measurement devices is time-consuming and challenging.

Road profiling devices known in the art are operated by a user, l.e. not self-propelled, and take measurements whilst traversing the driving surface to be measured. Taking measurements whilst the road profiling device is moving reduces the accuracy of the measurements, giving an accuracy in the order of several millimetres.

It is an aim of the present invention to address disadvantages associated with the prior art.

SUMMARY OF THE INVENTION

Aspects of the present invention relate to a controller for an autonomous surface measurement vehicle; an autonomous surface measurement vehicle, a method of operating an autonomous surface measurement vehicle, a method of creating a driving surface model and a driving surface model.

According to an aspect of the present invention there is provided an autonomous surface measurement vehicle for taking static driving surface measurements, the autonomous surface measurement vehicle comprising: positioning means arranged to receive position information relating to a position of the surface to be measured; localisation means arranged to record a measurement position of the autonomous surface measurement vehicle; ground engagement means for altering the measurement position of the autonomous surface measurement vehicle in dependence on the position information; a first measurement device for obtaining a first measurement at a first feature size of a driving surface; and storage means configured to associate the first measurement and the measurement position of the autonomous surface measurement vehicle to give driving surface data.

According to an aspect of the present invention there is provided an autonomous surface measurement vehicle for taking static driving surface measurements, the autonomous surface measurement vehicle comprising: positioning means arranged to receive position information relating to a position of the surface to be measured; localisation means arranged to record a measurement position of the autonomous surface measurement vehicle; ground engagement means for altering the measurement position of the autonomous surface measurement vehicle in dependence on the position information; a first measurement device for obtaining a first measurement at a first feature size of a driving surface; a second measurement device for obtaining a second measurement at a second feature size of the driving surface; and storage means configured to associate the first measurement and the second measurement and the measurement position of the autonomous surface measurement vehicle to give driving surface data.

Taking a plurality of measurements at multiple wavelength ranges, can be a time consuming and laborious process. An autonomous surface measurement vehicle is capable of manoeuvring from measurement position to measurement position, to take measurements at a plurality of measurement wavelengths, suitable for measuring driving surface feature sizes. The autonomous nature of the autonomous surface measurement vehicle enables the autonomous surface measurement vehicle to operate without necessarily requiring an operator to monitor the autonomous surface measurement vehicle.

The first measurement device may be a LiDAR sensor, such as a Faro® Focus 3D Laser Scanner or a Velodyne® LiDAR or any camera based technology. The first measurement device is operable to record driving surface features sized from approximately 1 millimetre to 100 metres.

At least one of the first measurement device and the second measurement device may comprise one or more optical measurement sensors. The first measurement device may comprise one or more macrotexture optical sensors and/or one more driving surface texture optical sensors. At least one of the one or more macrotexture optical sensors may comprise a LiDAR sensor. At least one of the one or more macrotexture optical sensors may comprise a monocular camera or a stereoscopic camera. The second measurement device may comprise one or more microtexture optical sensors. At least one of the one or more microtexture optical sensors may comprise a sensor for sensing feature sizes below 100 mm. At least one of the one or more microtexture optical sensors may, for example, comprise a structured light or laser pseudo-random pattern generation stereo camera system.

Having a plurality of optical measurement sensors operable at the first measurement or the second measurement range allows for a greater amount of measurement data to be collected from each measurement position. Further to this, having overlapping fields of view allows for a higher resolution measurements to be recorded, giving more accurate data and allowing smaller feature sizes to be measured. Non-static measurement techniques cannot give the level of accuracy that a static measurement gives. Macrotexture optical sensors are suitable for taking measurements in the macrotexture feature size range, that is features of 1 millimetre to 100 millimetres in size. LiDAR (Light Detection and Ranging) sensors are sensors suitable for taking measurements in the appropriate range. Microtexture optical sensors are suitable for taking measurements in the microtexture feature size range, that is features of approximately 1 micrometre to 1 millimetre in size.

The autonomous surface measurement vehicle may further comprise communication means for transmitting communications between the autonomous surface measurement vehicle and a remote controller. The communication means may comprise a cellular (such as 3G, 4G or 5G), WiFi or Bluetooth® transceiver.

Communication means are operable to allow communication between a remote computing means and the autonomous surface measurement vehicle. Remote computing means, such as a server or remote controller, may be operable to control the position of the autonomous surface measurement vehicle, by way of providing measurement positions to the autonomous surface measurement vehicle, or position data that can allow measurement positions to be determined by the autonomous surface measurement vehicle. The communication means may comprise a wired or wireless communication means. The wired communication means may be a USB or Ethernet connection. The wireless communication means may be a transceiver suitable for sending and receiving communications.

The localisation means may comprise an inertial measurement unit (IMU). The inertial measurement unit may comprise one or more accelerometers, gyroscopes or magnetometers, suitable for measuring one or more of lateral acceleration, longitudinal acceleration, vertical acceleration, pitch, roll or yaw.

Precise recording of the measurement position allows the multiple sets of driving surface data to be overlaid to give a single driving surface model. Due to the inaccuracy of standard GNSS systems, augmenting the GNSS data with data from on-board relative sensors allows the autonomous surface measurement vehicle to ensure the precise spacing of the measurement positions is recorded. Overlapping the multiple sets of driving surface data is then possible, even if the GNSS or GPS co-ordinates of the measurement position are not known, as the driving surface model can be determined from relative measurement position, as well as from absolute measurement positions.

The first measurement device or the second measurement device may comprise height alteration means configured to enable the first measurement device or the second measurement device to move in a substantially vertical direction. The height alteration means may comprise a pantograph mechanism, a scissor lift or a linear guide rail system.

Altering the vertical spacing between the first measurement device and the driving surface to be measured increases the incident angle of the radiation emitted by the first measurement device and reduces the signal to noise ratio of the received radiation.

The positioning means may comprise a GNSS receiver for receiving location information indicative of the current position of the autonomous surface measurement vehicle. The GNSS receiver may be a Global Positioning System, GPS, a Global Navigation Satellite System, GLONASS, or similar GNSS receiving device.

In order for the autonomous surface measurement vehicle to relocate to the measurement position, the current position needs to be known. A GNSS receiver allows the autonomous surface measurement vehicle to receive a GNSS signal indicative of the current position of the autonomous surface measurement vehicle.

The ground engagement means may be are configured to move the autonomous surface measurement vehicle from the current position to the measurement position.

If the autonomous surface measurement vehicle is not at the measurement position, the ground engagement means, which may comprise one or more wheels and/or one or more tracks, are controlled to alter the position of the autonomous surface measurement vehicle to be the measurement position. The ground engagement means further comprise one or more electric motors suitable for providing torque to the plurality of wheels in order to alter the current position of the autonomous surface measurement vehicle.

The autonomous surface measurement vehicle may be configured to obtain the first measurement and to obtain the second measurement whilst stationary.

The position information may be indicative of a measurement path for the autonomous surface measurement vehicle to follow, the autonomous surface measurement vehicle may be operable to determine a plurality of measurement positions corresponding to the measurement path.

The measurement path may comprise a series of measurement positions along which the autonomous surface measurement vehicle should establish measurement positions and take measurements. Having a series of measurement positions to be followed allows the autonomous surface measurement vehicle to work autonomously for longer periods of time. Transmitting a measurement path to the autonomous surface measurement vehicle allows the same path to be sent to multiple autonomous surface measurement vehicles, or a single autonomous surface measurement vehicle in different configurations, whereby the measurement spacing will be known to the autonomous surface measurement vehicle and can be factored in to the calculation of the plurality of measurement positions.

The first measurement and the second measurement may be measured at substantially the same time. The first measurement or the second measurement may comprise a plurality of measurements taken by a plurality of measurement sensors.

Obtaining the first measurement and the second measurement at substantially the same time ensures that any changes in driving surface conditions do not cause discrepancies between the first measurement and the second measurement. Some driving surface features will span the measurement range of both the first measurement sensor and the second measurement sensor, and as such discrepancies in data collected may be problematic. Overlapping measurements from a plurality of measurement sensors increases the accuracy of the measurements. A plurality of measurement sensors operable in the same measurement range enable a greater field of view for the measurements from the autonomous surface measurement vehicle.

The positioning means may comprise a correction signal receiver, for example a real time kinematic (RTK) receiver for receiving a correction signal for providing differential correction to the location information.

RTK data is used to correct a received GNSS signal to account for drift in GNSS signal. Using measurements of the phase of the signals carrier wave, centimetre level accuracy is attainable.

According to a further aspect of the present invention there is provided a method of operating an autonomous surface measurement vehicle for taking static driving surface measurements, the method comprising: receiving position information relating to a position of a surface to be measured; altering a current position of the autonomous surface measurement vehicle to a measurement position in dependence on the position information; recording the measurement position of the autonomous surface measurement vehicle; obtaining a first measurement at a first feature size of a driving surface; obtaining a second measurement at a second feature size of the driving surface; and processing the first measurement, the second measurement and the measurement position of the autonomous surface measurement vehicle to give driving surface data.

The first measurement and the second measurement may comprise one or more optical measurements. The first measurement may comprise one or more macrotexture optical measurements and/or one or more driving surface texture optical measurements. The one or more macrotexture optical measurements may comprise a LiDAR measurement. The macrotexture optical measurements may comprise image data collected by a monocular camera or a stereoscopic camera. The second measurement may comprise one or more microtexture optical measurements. The one or more microtexture optical measurements may comprise a measurement for measuring feature sizes below 100 mm.

The method may further comprise receiving a signal from a remote computing means for controlling the autonomous surface measurement vehicle. The method may comprise sending the driving surface data to a remote computing means. The method may comprise altering the vertical height of a first measurement device suitable for obtaining the first measurement. The method may comprise receiving location information indicative of the current position of the autonomous surface measurement vehicle. The altering the position of the autonomous surface measurement vehicle may comprise using a ground engagement means to move the autonomous surface measurement vehicle from the current position to the measurement position.

The first measurement and the second measurement may be measured whilst the autonomous surface measurement vehicle is substantially stationary. The position information may be indicative of a measurement path for the autonomous surface measurement vehicle to follow.

The method may comprise determining a plurality of measurement positions corresponding to the measurement path. The determination may be carried out by the autonomous surface measurement vehicle after the autonomous surface measurement vehicle has moved to each measurement position.

According to a further aspect of the present invention there is provided a method of creating a driving surface model, the method comprising: selecting position information indicative of a driving surface to be modelled, transmitting the position information indicative of the driving surface to be modelled to an autonomous surface measurement vehicle; receiving driving surface data from the autonomous surface measurement vehicle; and creating the driving surface model from the received driving surface data.

Selecting the position information may comprise generating the position information by recording the position of the surface to be measured.

The driving surface data may be received from the autonomous surface measurement vehicle.

According to a further aspect of the present invention there is provided a driving surface model representative of a driving surface, the driving surface model comprising a plurality of measurement sets, each of the plurality of measurement sets comprising: a first measurement at a first feature size of a driving surface; a second measurement at a second feature size of the driving surface; and a measurement position representative of the position at which the first measurement and the second measurement are measured.

One or more of the first measurement, the second measurement and the measurement position may be collected by the autonomous surface measurement vehicle.

According to a further aspect of the present invention there is provided a driving surface model where created by the method of creating the driving surface model representative of a driving surface.

According to a further aspect of the present invention there is provided a method of generating a driving surface model representative of a driving surface from a plurality of static measurements, the driving surface model generation method comprising: receiving a plurality of measurement sets, each measurement set comprising: a first measurement at a first feature size of a driving surface; a second measurement at a second feature size of a driving surface; and a measurement position indicative of a position at which the first measurement and the second measurement were measured; deriving a driving surface characteristic in dependence on the first measurement and the second measurement; and combining the plurality of measurement sets in dependence on the measurement positions to generate a driving surface model.

A driving surface characteristic may be indicative of one or more particular characteristics of a driving surface. These driving surface characteristics may, for example, be indicative of: a coefficient of friction of a particular driving surface; a level of friction of a driving surface; a roughness of a driving surface; a wetness of a driving surface and/or a deformability of a driving surface. Deriving a driving surface characteristic from the measurement data will reduce the size of the data to be stored and/or transferred and will enable a smaller driving surface model to be derived.

The first measurement, second measurement and measurement position may be received from the autonomous surface measurement vehicle.

Within the scope of this application it is expressly envisaged that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and/or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. Features described in connection with one embodiment are applicable to all embodiments, unless such features are incompatible.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

Figure 1 shows a schematic representation of an autonomous surface measurement vehicle according to embodiments of the invention;

Figure 2 shows a first block diagram illustrating a method of collecting driving surface data according to embodiments of the invention;

Figure 3 shows a second block diagram illustrating a method of measuring a surface according to embodiments of the invention;

Figure 4 shows a third block diagram illustrating a method of controlling an autonomous surface measurement vehicle to collect driving surface data according to embodiments of the invention;

Figure 5 shows a fourth block diagram illustrating a method of determining position information suitable for sending to an autonomous surface measurement vehicle to allow the autonomous surface measurement vehicle to collect driving surface data according to embodiments of the invention;

Figure 6 shows a fifth block diagram illustrating a method of generating a driving surface model from measurement sets collected by an autonomous surface measurement vehicle according to embodiments of the invention;

Figure 7 shows a driving surface model produced from measurement sets collected by an autonomous surface measurement vehicle according to embodiments of the invention; and

Figure 8 shows a schematic representation of a system used for controlling an autonomous surface measurement vehicle.

DETAILED DESCRIPTION

An autonomous surface measurement vehicle in accordance with an embodiment of the present invention is described herein with reference to the accompanying Figures. The autonomous surface measurement vehicle 100 is operable to measure driving surface data for creating a driving surface model.

With reference to Figure 1, an autonomous surface measurement vehicle 100 is shown comprising a platform 110 suitable for supporting the measurement devices. The autonomous surface measurement vehicle 100 comprises a first measurement device 150 and a second measurement device 160.

In the described embodiment, the autonomous surface measurement vehicle 100 further comprises a height alteration means 120. In the present embodiment, the height alteration means 120 is a scissor lift. The scissor lift is used to alter the vertical position of the first measurement device 150, such that a first measurement taken at the first feature size of the driving surface can be taken at a high incident light angle, whilst maintaining stability during movement of the autonomous surface measurement vehicle 100. Taking the first measurement at a high incident light angle increases the signal to noise ratio, allowing for a more accurate first measurement to be taken. The scissor lift is actuated by a motor controlled through the autonomous surface measurement vehicle 100 controller.

The autonomous surface measurement vehicle 100 further comprises localisation means 130 suitable for providing position, heading and stability information to support the autonomous driving functionality of the autonomous surface measurement vehicle 100 and to record a measurement position at which the autonomous surface measurement vehicle 100 records the first measurement and the second measurement. In the present embodiment the localisation means 130 comprises an Inertial Measurement Unit, IMU, and a Global Navigation Satellite System receiver, GNSS, suitable for receiving the position of the autonomous surface measurement vehicle 100 in relation to the global reference system. The combination of the IMU and GNSS data allows for greater accuracy in the location of the measurement position to be determined.

Further to this, the GNSS antennae 140 improve the heading accuracy and the position accuracy. The heading accuracy and the position accuracy are further improved by laterally offsetting the GNSS antennae 140 at opposing ends of the autonomous surface measurement vehicle 100. The GNSS antennae 140 are also foldable, allowing the lateral offset in the position of the GNSS antennae 140 to be further increased by moving the GNSS antennae 140 from a folded position to an unfolded position. In the unfolded position, the GNSS antennae 140, may interfere with measurements taken by the first measurement device 150 and/or the second measurement device 160, so the GNSS antennae 140 can be moved to the folded position after receiving the GNSS position of the autonomous surface measurement vehicle 100, and before the first measurement and/or the second measurement are taken by the first measurement device 150 and/or the second measurement device 160.

The first measurement device 150 is suitable for taking measurements at a first feature size of a driving surface. In the present embodiment, the first measurement device is a LiDAR sensor. The first feature size corresponds to a first wavelength of the radiation emitted by the first measurement device 150. The first measurement device 150 comprises two rotational movement axes to allow the first measurement device position to be altered in the azimuth direction and the elevation direction. This rotational movement allows the first measurement device 150 to take measurements on uneven surfaces that are corrected to ensure that the measurements are comparable with measurement taken on other uneven surfaces or flat surfaces. The first measurement device 150 is capable of taking measurements in all directions from the autonomous surface measurement vehicle 100 without needing to alter the position of the autonomous surface measurement vehicle 100. This allows the measurements taken by the first measurement device and the second measurement device to be combined to give driving surface data.

The second measurement device 160 is suitable for taking measurements at a second feature size of a driving surface. The second feature size corresponds to a second wavelength of the radiation emitted by the second measurement device 160. The second measurement device 160 may comprise a plurality of measurement sensors, each of which will have a different field of view to one another, a different planar resolution to one another and a different vertical resolution to one another. Having multiple measurement sensors with overlapping fields of view will improve the resolution of the final measurement. The plurality of measurement sensors that make up the second measurement device 160 are mounted a fixed distance apart, and therefore the measurement taken by each of the plurality of measurement sensors can be overlapped, to improve the resolution of the final measurement. The Power Spectral Density can be extracted from the measurements can be extracted and filtered to cover a broad range of feature sizes. Microtexture data relating to a driving surface can be used to extract the surface power spectral density that can be mathematically modelled to provide an estimation of the driving surface friction. The first measurement device may be a microtexture optical sensors and may, for example, comprise a sensor for sensing feature sizes below 100 mm. At least one of the one or more microtexture optical sensors may, for example, comprise a structured light or laser pseudorandom pattern generation stereo camera system.

Macrotexture optical sensors are suitable for taking measurements in the macrotexture feature size range, that is features of 1 millimetre to 100 millimetres in size. LiDAR (Light Detection and Ranging) sensors are sensors suitable for taking measurements in the appropriate range. Microtexture optical sensors are suitable for taking measurements in the microtexture feature size range, that is features of approximately 1 micrometre to 1 millimetre in size.

A correction signal receiver, in the present embodiment a Real Time Kinematic, RTK, receiver 170 is used to provide a correction to the GNSS signal received at the localisation means 130. RTK uses measurements of the phase of the reference signal’s carrier wave from a localised base station in order to improve the accuracy of the position determination.

Ground engagement means 180 are suitable for altering the current position of the autonomous surface measurement vehicle 100. The ground engagement means according to the present embodiment comprises a plurality of wheels. The ground engagement means 180 further comprise an electric motor suitable for providing torque to the plurality of wheels in order to alter the current position of the autonomous surface measurement vehicle 100. By providing differing amounts of torque to different wheels of the autonomous surface measurement vehicle 100 or the other, the heading of the autonomous surface measurement vehicle 100 may also be altered.

Storage means 190 are arranged to receive the first measurement from the first measurement device 150, the second measurement from the second measurement device 160, and the measurement position from the localisation means 130. Combining the first measurement, the second measurement, and the measurement position gives driving surface data.

Combining the first measurement at a first driving surface feature size and the second measurement at a second driving surface feature gives a model of the driving surface over which the autonomous surface measurement vehicle 100 is being driven. Using the measurement position at which each of the first measurements and each of the second measurements have been taken allows multiple sets of driving surface data, each comprising a first measurement and a second measurement taken at a plurality of measurement positions, to be combined to give a driving surface model. Utilising the GNSS, IMU and RTK data relating to the measurement positions allows for the combination of multiple sets of driving surface data, with overlapping measurement data. The overlap of measurement data also further improves the accuracy of the driving surface model that is created. The first measurement and the second measurement are taken at a first measurement spacing and a second measurement spacing respectively which may be the same as or different to one another.

Referring now to Figure 2, a method 200 of operating the autonomous surface measurement vehicle 100 is shown. In step 210, the autonomous surface measurement vehicle 100 receives position information from a remote computing means. In the present embodiment, the remote computing means is an internet based server. The position information is indicative of the measurement position, or a series of measurement positions, at which the autonomous surface measurement vehicle 100 should move to in order to take the first measurement and the second measurement. If the position information is indicative of a plurality of measurement positions, the autonomous surface measurement vehicle 100 will move to each of the measurement positions in turn.

In step 220, the autonomous surface measurement vehicle 100 determines the current position of the autonomous surface measurement vehicle 100 and the measurement position, and if necessary, alters the current position of the autonomous surface measurement vehicle 100 to be the measurement position by sending a signal to the ground engagement means 180.

In step 230, the autonomous surface measurement vehicle 100 will accurately record the measurement position of the autonomous surface measurement vehicle 100. This is because due to the inaccuracy of GNSS, the error in which is several orders of magnitude greater than the smallest surface feature size to be measured, the actual measurement position may not align precisely with the measurement position calculated from the position information. The measurement position comprises data obtained from IMU, GNSS Receiver and the RTK antenna, where available.

In step 240, the first measurement is measured by the first measurement device 150. The first measurement may comprise a plurality of first measurements, all of which are taken by the first measurement device 150 at substantially the same measurement position.

In step 250, the second measurement is measured by the second measurement device 160. The second measurement may comprise a plurality of second measurements, all of which are taken by the second measurement device 160 at substantially the same measurement position. As the second measurement device 160 may comprise a plurality of second measurement sensors, the plurality of second measurement may be measured from any one or more of the plurality of second measurement sensors. Each of the plurality of second measurement sensors will be rigidly mounted to the autonomous surface measurement vehicle 100 at a known distance from one another. This distance may be set such that any interference between each of the plurality of second measurement sensors is improved, be that as constructive or destructive interference. Having a set distance between each of the plurality of second measurement sensors allows for the second measurements collected by the second measurement device 160 to be overlapped to give more detailed driving surface data.

Step 240 and step 250 occur at substantially the same time, whilst the autonomous surface measurement vehicle 100 is stationary and at the recorded measurement position. In order for the first measurement and the second measurement to be recorded without blind spots, the foldable GNSS antennae 140 may be folded into the folded position such that they do not block any part of the field of view of the first measurement device 150 or the second measurement device 160. Further to this, the height alteration means 120 can alter the position of the first measurement device 150 such that the angle of incident light between the first measurement device 150 and the surface to be measured is increased, improving the accuracy of the first measurement.

In step 260, the first measurement, second measurement and measurement position data are associated with one another and stored in the storage means 190 of the autonomous surface measurement vehicle 100. Associating each of the first measurement and second measurements with the measurement position to give driving surface data that is associated with a measurement position allows the plurality of driving surface data sets to be collated into a single driving surface model.

In step 270, the driving surface data is output from the autonomous surface measurement vehicle 100 to a remote computing means suitable for storing and processing the driving surface data. The output of the driving surface data may be via a wired connection, such as USB or Ethernet, or a wireless connection such as cellular (such as 3G, 4G or 5G), Wi-Fi® or Bluetooth®.

Referring now to Figure 3, a further method 300 of operation the autonomous surface measurement vehicle 100 is shown. The method comprises like process steps to the method shown in figure 2, but further comprises a loop..

Step 310, step 320, step 330, step 340, step 350 and step 360 are equivalent to step 210, step 220, step 230, step 240, step 250 and step 260 respectively as shown in figure 2.

After step 360, the method loops back to step 320, and the autonomous surface measurement vehicle 100 moves to the next measurement position, to record the next set of driving surface data.

Referring now to Figure 4, there is shown a method 400 as performed by the remote computing means configured to control the autonomous surface measurement vehicle 100.

In step 410, the position information relating to the position, or a series of positions, at which the autonomous surface measurement vehicle 100 should move to in order to take the first measurement and the second measurement is selected. The selection of the position information is carried out in accordance with the method outlined in Figure 5.

In step 420, the position information is transmitted via a wired connection, such as USB or Ethernet, or a wireless connection such as cellular, Wi-Fi® or Bluetooth® from the remote computing means to the autonomous surface measurement vehicle 100.

In step 430 the driving surface data, or multiple sets of driving surface data, is received by the remote computing means from the autonomous surface measurement vehicle 100 via a wired connection, such as USB or Ethernet, or a wireless connection such as cellular, WiFi® or Bluetooth®.

Referring now to Figure 5, there is shown a method 500 performed to determine the position information to be transmitted to the autonomous surface measurement vehicle 100. GNSS data is collected relating to a surface to be measured, and a measurement route determined from the GNSS data.

In step 530, vehicle GNSS data 510 is collected by a vehicle or GNSS survey device, fitted with a suitable advanced GNSS solution. This vehicle GNSS data comprises a GPS point cloud, a set of coordinates that can be utilised to create the route. Alternatively, satellite GNSS antenna 520 may be used to create the route. Satellite GNSS antenna are manually operated devices used to measure positions, primarily in the civil engineering field, for example a Leica® Viva GS16.

In step 560, the first measurement spacing 540 and the second measurement spacing 550 are determined, using the measurement range, resolution and accuracy of the first measurement device 150 and the second measurement device 160, and combined with the GNSS point cloud to give a route for the autonomous surface measurement vehicle 100 to follow. From this route, in step 570, position information, comprising a plurality of measurement positions is determined.

Referring now to figure 6, a method 600 of generating the driving surface model is shown from the measurement sets collected by the autonomous surface measurement vehicle 100.

In step 610 the measurement sets collected by the autonomous surface measurement vehicle 100 are received by the remote computing means. The measurement sets comprise a plurality of first measurements, second measurements and measurement positions, associated accordingly.

In step 620, the measurement sets received from the autonomous surface measurement vehicle 100 are combined and driving surface data sets are derived from the received measurement sets. The combination of the received measurement sets and derivation of the road surface characteristics together generate a driving surface model that is output in step 630. In order to generate the driving surface model the measurement position information is utilised to align the plurality driving surface data sets, comprising the plurality of first measurements and the plurality of second measurement, allowing point cloud to point cloud alignment of the driving surface data sets. Mathematical modelling techniques, such as the Persson Model of Surface Roughness, are utilised to model the driving surface friction from the received second measurement data, and the resulting driving surface friction is used as an input to a tyre-driving surface interaction model. First measurement data is processed as discussed to give a uniform 3D model. The driving surface friction derived from the second measurement data is grouped into patches to give a local average driving surface friction value and combined with the uniform 3D model to give a more detailed driving surface model.

Figure 7 shows a driving surface model representative of a driving surface as formed from data collected by the autonomous surface measurement vehicle 100. A plurality of measurement positions 710 are shown, spaced apart by the second measurement spacing 550. The first measurement spacing 540 is larger than the second measurement spacing 550, so the second measurement spacing is chosen to ensure full coverage of the driving surface across both the first measurement and the second measurement.

Figure 8 illustrates a system 800 used for controlling an autonomous surface measurement vehicle 810. Communication between the autonomous surface measurement vehicle 810, remote computing means 820 and a remote controller 830 allows for data storage and data transmission between each of the autonomous surface measurement vehicle 810, the remote computing means 820 and the remote controller 830. The autonomous surface measurement vehicle 810 may further comprise storage means 815 suitable for storing a plurality of data sets 817. The remote computing means 820 may further comprise storage means 825 suitable for storing a plurality of data sets 827. The remote controller 830 may further comprise storage means 835 suitable for storing a plurality of data sets 837. Data sets 817, 827, 837 may comprise one or more of measurement data, position information, first measurement data or second measurement data. Any processing, control or storage may occur at any one or more of the autonomous surface measurement vehicle 810, the remote computing means 820 or the remote controller 830.

By taking multiple measurements from a static, recorded position it enables the recording of driving surface data at a high level of accuracy. An autonomous surface measurement vehicle is capable of manoeuvring from measurement position to measurement position, to take measurements at a plurality of measurement wavelengths, suitable for measuring driving surface feature sizes. The autonomous nature of the autonomous surface measurement vehicle enables the autonomous surface measurement vehicle to operate without necessarily requiring an operator to monitor the autonomous surface measurement vehicle. The first measurement device may be a LiDAR sensor, such as a Faro® Focus 3D Laser Scanner or a Velodyne® LiDAR or any camera based technology.

The first measurement device is operable to record driving surface features sized from approximately 1 millimetre to 100 metres. Having a plurality of optical measurement sensors operable at the first measurement or the second measurement range allows for a greater amount of measurement data to be collected from each measurement position. Further to this, having overlapping fields of view allows for a higher resolution measurements to be recorded, giving more accurate data and allowing smaller feature sizes to be measured. Non-static measurement techniques cannot give the level of accuracy that a static measurement gives. Macrotexture optical sensors are suitable for taking measurements in the macrotexture feature size range, that is features of 1 millimetre to 100 millimetres in size. LiDAR (Light Detection and Ranging) sensors are sensors suitable for taking measurements in the appropriate range. Microtexture optical sensors are suitable for taking measurements in the microtexture feature size range, that is features of approximately 1 micrometre to 1 millimetre in size.

Precise recording of the measurement position allows the multiple sets of driving surface data can be overlaid to give a single driving surface model. Due to the inaccuracy of standard GNSS systems, augmenting the GNSS data with data from on-board relative sensors allows the autonomous surface measurement vehicle to ensure the precise spacing of the measurement positions is recorded. Overlapping the multiple sets of driving surface data is then possible, even if the GNSS or GPS co-ordinates of the measurement position are not known, as the driving surface model can be determined from relative measurement position, as well as from absolute measurement positions.

Stationary measurements have the ability to record a greater level of accuracy, as the frame of reference for the measurements that are taken is static in three dimensions. The accuracy of a roving measurement will be affected by movement in the measurement device relative to the driving surface over which the measurement vehicle is moving. Stationary measurements prevent unexpected displacement of the measurement device introduces large measurement errors, reducing the accuracy of the obtained driving surface model.

Any controller or controllers described herein may suitably comprise a control unit or computational device having one or more electronic processors. Thus the system may comprise a single control unit or electronic controller or alternatively different functions of the controller may be embodied in, or hosted in, different control units or controllers. As used herein the term “controller” or “control unit” will be understood to include both a single control unit or controller and a plurality of control units or controllers collectively operating to provide 5 any stated control functionality. To configure a controller, a suitable set of instructions may be provided which, when executed, cause said control unit or computational device to implement the control techniques specified herein. The set of instructions may suitably be embedded in said one or more electronic processors. Alternatively, the set of instructions may be provided as software saved on one or more memory associated with said controller 10 to be executed on said computational device. A first controller may be implemented in software run on one or more processors. One or more other controllers may be implemented in software run on one or more processors, optionally the same one or more processors as the first controller. Other suitable arrangements may also be used. Any one or more of the controllers may be located in or on the autonomous surface measurement vehicle.

It will be appreciated that various changes and modifications can be made to the present invention without departing from the scope of the present application.

Claims

1. An autonomous surface measurement vehicle for taking static driving surface measurements, the autonomous surface measurement vehicle comprising:

positioning means arranged to receive position information relating to a position of the surface to be measured;

localisation means arranged to record a measurement position of the autonomous surface measurement vehicle;

ground engagement means for altering the measurement position of the autonomous surface measurement vehicle in dependence on the position information;

a first measurement device for obtaining a first measurement at a first feature size of a driving surface; and a second measurement device for obtaining a second measurement at a second feature size of the driving surface.

2. The autonomous surface measurement vehicle of claim 1 further comprising storage means configured to associate the first measurement and the second measurement and the measurement position of the autonomous surface measurement vehicle to give driving surface data.

3. The autonomous surface measurement vehicle of claim 1 or claim 2 wherein the autonomous surface measurement vehicle derives one or more driving surface characteristics from at least one of the first measurement or the second measurement.

4. The autonomous surface measurement vehicle of any preceding claim wherein at least one of the first measurement device and the second measurement device comprise one or more optical measurement sensors.

5. The autonomous surface measurement vehicle of any preceding claim wherein the first measurement device comprises one or more macrotexture optical sensors.

6. The autonomous surface measurement vehicle of claim 5 wherein at least one of the one or more macrotexture optical sensors comprises a LiDAR sensor.

7. The autonomous surface measurement vehicle of claim 5 or claim 6 wherein at least one of the one or more macrotexture optical sensors comprises a monocular camera or a stereoscopic camera.

8. The autonomous surface measurement vehicle of any preceding claim wherein the second measurement device comprises one or more microtexture optical sensors.

9. The autonomous surface measurement vehicle of claim 8 wherein at least one of the one or more microtexture optical sensors comprises a sensor for sensing feature sizes below 100 mm.

10. The autonomous surface measurement vehicle of any preceding claim wherein the autonomous surface measurement vehicle further comprises communication means for transmitting communications between the autonomous surface measurement vehicle and a remote controller.

11. The autonomous surface measurement vehicle of any preceding claim wherein the localisation means comprises an inertial measurement unit.

12. The autonomous surface measurement vehicle of claim 11 wherein the inertial measurement unit comprises one or more accelerometers, gyroscopes or magnetometers, and wherein the inertial measurement unit is suitable for measuring one or more of lateral acceleration, longitudinal acceleration, vertical acceleration, pitch, roll or yaw.

13. The autonomous surface measurement vehicle of any preceding claim wherein at least the first measurement device comprises height alteration means configured to enable the first measurement device to move in a substantially vertical direction.

14. The autonomous surface measurement vehicle of any preceding claim wherein the height alteration means comprises a scissor lift or linear guide rail system.

15. The autonomous surface measurement vehicle of any preceding claim wherein the positioning means comprises a GNSS receiver for receiving location information indicative of the current position of the autonomous surface measurement vehicle.

16. The autonomous surface measurement vehicle of any preceding claim wherein the ground engagement means are configured to move the autonomous surface measurement vehicle from the current position to the measurement position.

17. The autonomous surface measurement vehicle of any preceding claim wherein the autonomous surface measurement vehicle is configured to obtain the first measurement and to obtain the second measurement whilst stationary.

18. The autonomous surface measurement vehicle of any preceding claim wherein the position information is indicative of a measurement path for the autonomous surface measurement vehicle to follow.

19. The autonomous surface measurement vehicle of any preceding claim wherein the autonomous surface measurement vehicle is operable to determine a plurality of measurement positions corresponding to the measurement path.

20. The autonomous surface measurement vehicle of any preceding claim wherein the first measurement and the second measurement are measured at substantially the same time.

21. The autonomous surface measurement vehicle of any preceding claim wherein the first measurement or the second measurement may comprise a plurality of measurements taken by a plurality of measurement sensors.

22. The autonomous surface measurement vehicle of any preceding claim wherein the positioning means further comprises a correction signal receiver for receiving a correction signal for providing differential correction to the location information.

23. A controller for an autonomous surface measurement vehicle for taking static driving surface measurements, the controller configured to:

receive position information relating to a position of a surface to be measured; control a ground engagement means to alter a current position of the autonomous surface measurement vehicle to a measurement position in dependence on the position information;

control a localisation means to record the measurement position of the autonomous surface measurement vehicle;

control a first measurement device to obtain a first measurement at a first feature size of a driving surface; and control a second measurement device to obtain a second measurement at a second feature size of the driving surface.

24. The controller of claim 23 configured to control the autonomous surface measurement vehicle of any one of claim 1 to claim 22.

25. The controller of claim 23 or claim 24 wherein the controller is further configure to derive one or more driving surface characteristics from at least one of the first measurement or the second measurement.

26. A method of operating an autonomous surface measurement vehicle for taking static driving surface measurements, the method of operating an autonomous surface measurement vehicle comprising:

receiving position information relating to a position of a surface to be measured;

altering a current position of the autonomous surface measurement vehicle to a measurement position in dependence on the position information;

recording the measurement position of the autonomous surface measurement vehicle;

obtaining a first measurement at a first feature size of a driving surface; and obtaining a second measurement at a second feature size of the driving surface.

27. The method of claim 26 wherein the method further comprises deriving one or more driving surface characteristics from at least one of the first measurement or the second measurement.

28. The method of claim 26 or claim 27 wherein the method further comprises processing the first measurement, the second measurement and the measurement position of the autonomous surface measurement vehicle to give driving surface data.

29. The method of any of one claim 26 to claim 28 wherein the first measurement and the second measurement comprise one or more optical measurements.

30. The method of any one of claim 26 to claim 29 wherein the first measurement comprises one or more macrotexture optical measurements.

31. The method of claim 30 wherein at least one of the one or more macrotexture optical measurements comprises a LiDAR measurement.

32. The method of claim 30 or claim 31 wherein at least one of the one or more macrotexture optical measurements comprises image data collected by a monocular camera or a stereoscopic camera.

33. The method of any one of claims 26 to 32 wherein the second measurement comprises one or more microtexture optical measurements.

34. The method of claim 33 wherein at least one of the one or more microtexture optical measurements comprises a measurement for measuring feature sizes below 100 mm.

35. The method of any one of claims 26 to 34 wherein the method further comprises receiving a signal from a remote computing means for controlling the autonomous surface measurement vehicle.

36. The method of any one of claims 26 to 35 wherein the method comprises sending the driving surface data to a remote computing means.

37. The method of any one of claims 26 to 36 comprising altering the vertical height of a first measurement device suitable for obtaining the first measurement.

38. The method of any one of claims 26 to 37 comprising receiving location information indicative of the current position of the autonomous surface measurement vehicle.

39. The method of any one of claims 26 to 38 wherein the altering the position of the autonomous surface measurement vehicle comprises using a ground engagement means to move the autonomous surface measurement vehicle from the current position to the measurement position.

40. The method of any one of claims 26 to 39 wherein the first measurement and the second measurement are measured whilst the autonomous surface measurement vehicle is substantially stationary.

41. The method of any one of claims 26 to 40 wherein the position information is indicative of a measurement path for the autonomous surface measurement vehicle to follow.

42. The method of any one of claims 26 to 41 wherein the method comprises determining a plurality of measurement positions corresponding to the measurement path.

43. A method as claimed any one of claims 26 to 42, wherein the determination is carried out by the autonomous surface measurement vehicle after the autonomous surface measurement vehicle has moved to each measurement position.

44. The method of one of claims 26 to 43 wherein the first measurement and the second measurement are measured at substantially the same time.

45. The method of any one of claims 26 to 44 wherein the first measurement or the second measurement may comprise a plurality of measurements taken by a plurality of measurement sensors.

46. A method of creating a driving surface model, the method comprising:

selecting position information indicative of a driving surface to be modelled, transmitting the position information indicative of the driving surface to be modelled to an autonomous surface measurement vehicle;

receiving driving surface data from the autonomous surface measurement vehicle; and creating the driving surface model from the received driving surface data.

47. The method as claimed in claim 46 wherein selecting the position information comprises generating the position information by recording the position of the surface to be measured.

48. The method as claimed in claim 46 or claim 47 wherein the driving surface data is received from the autonomous surface measurement vehicle according to any one of claims 1 to claim 22.

49. A driving surface model representative of a driving surface, the driving surface model derived from a combination of a plurality of measurement sets, each of the plurality of measurement sets comprising:

a first measurement at a first feature size of a driving surface;

a second measurement at a second feature size of the driving surface; and a measurement position representative of the position at which the first measurement and the second measurement are measured.

50. The driving surface model of claim 49 wherein the driving surface model further comprises one or more driving surface characteristics derived from at least one of the first measurement or the second measurement.

51. The driving surface model of claim 49 or claim 50 wherein one or more of the first measurement, the second measurement and the measurement position are collected by an autonomous surface measurement vehicle according to any one of claim 1 to claim 22, by an autonomous surface measurement vehicle controlled by a controller according to any one of claim 23 to claim 25 or by the method of any one of claim 26 to claim 45.

52. The driving surface model of claim 49 or claim 50 wherein the driving surface model is created by the method of claims 46 to claim 48.

53. A method of generating a driving surface model representative of a driving surface from a plurality of static measurements, the driving surface model generation method comprising:

receiving a plurality of measurement sets, each measurement set comprising: a first measurement at a first feature size of a driving surface;

a second measurement at a second feature size of a driving surface; and a measurement position indicative of a position at which the first measurement and the second measurement were measured;

deriving a driving surface characteristic in dependence on the first measurement and the second measurement for each of the plurality of measurement sets; and combining the driving surface characteristics in dependence on the measurement positions to generate a driving surface model.

54. The method of claim 53, wherein the first measurement, second measurement and measurement position are received from an autonomous surface measurement vehicle according to any one of claim 1 to claim 22, received from an autonomous surface measurement vehicle controlled by a controller according to any one of

5 claim 23 to claim 25 or measured by the method of any one of claim 26 to claim 45.

55. A non-transitory computer readable storage medium comprising computer readable instructions for a computer processor to carry out the method of any of claims 26 to 48, or claims 53 to 54.