GB2552024A

GB2552024A - Improvements in vehicle speed control

Info

Publication number: GB2552024A
Application number: GB1611907.5A
Authority: GB
Inventors: Gaszczak Anna; Fairgrieve Andrew
Original assignee: Jaguar Land Rover Ltd
Current assignee: Jaguar Land Rover Ltd
Priority date: 2016-07-08
Filing date: 2016-07-08
Publication date: 2018-01-10
Anticipated expiration: 2036-07-08
Also published as: GB201611907D0; WO2018007079A1; GB2552024B

Abstract

A terrain surface roughness detection system 10, 19, 185C for a vehicle 100 with a speed control or cruise control system, the system comprising a processing means 10, 19 arranged to receive, from terrain data capture means 185C arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle. The processing means is configured to, in dependence upon a predicted path of the vehicle 100 over said terrain extending ahead of the vehicle 100, generate, for the predicted path of the vehicle 100, terrain roughness information indicative of a roughness of the terrain along the predicted path. The system is configured to output an output signal in dependence on the terrain roughness information. A machine learning regression model may be used to generate a maximum speed value for the cruise control system, based on the surface roughness information.

Description

(71) Applicant(s):

Jaguar Land Rover Limited (Incorporated in the United Kingdom)

Abbey Road, Whitley, Coventry, Warwickshire, CV3 4LF, United Kingdom (72) Inventor(s):

Anna Gaszczak

Andrew Fairgrieve (56) Documents Cited:

EP 1733913 A2 DE 102010013339A1 US 7272474 B1

EP 0412791 A2 DE 102008023135 A1 US 20040094912 A1 (58) Field of Search:

INT CL B60K, B60W, G01B, G01C Other: EPODOC, WPI (74) Agent and/or Address for Service:

Jaguar Land Rover

Patents Department W/1/073, Abbey Road, Whitley, COVENTRY, CV3 4LF, United Kingdom (54) Title of the Invention: Improvements in vehicle speed control

Abstract Title: VEHICLE SPEED CONTROL SYSTEM WITH TERRAIN ROUGHNESS DETECTION (57) A terrain surface roughness detection system 10, 19, 185C for a vehicle 100 with a speed control or cruise control system, the system comprising a processing means 10, 19 arranged to receive, from terrain data capture means 185C arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle. The processing means is configured to, in dependence upon a predicted path of the vehicle 100 over said terrain extending ahead of the vehicle 100, generate, for the predicted path of the vehicle 100, terrain roughness information indicative of a roughness of the terrain along the predicted path. The system is configured to output an output signal in dependence on the terrain roughness information. A machine learning regression model may be used to generate a maximum speed value for the cruise control system, based on the surface roughness information.

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IMPROVEMENTS IN VEHICLE SPEED CONTROL

INCORPORATION BY REFERENCE

The content of co-pending UK patent applications GB2507622 and GB2499461 are hereby incorporated by reference. The content of US patent no US7349776 and co-pending international patent applications WO2013124321 and WO2014/139875 are incorporated herein by reference. The content of UK patent applications GB2492748, GB2492655 and GB2499279 and UK patent GB2508464 are also incorporated herein by reference.

FIELD OF THE INVENTION

The invention relates to a system and method and system for detecting the surface roughness of terrain ahead of a vehicle, and to a system for controlling the speed of a landbased vehicle which is capable of driving in a variety of different and extreme terrains and conditions based on the detected surface roughness.

BACKGROUND

In known vehicle speed control systems, typically referred to as cruise control systems, the vehicle speed is maintained on-road once set by the user without further intervention by the user so as to improve the driving experience for the user by reducing workload. Cruise control speed (or cruise set-speed) is settable by the vehicle driver, typically by pressing a button when the vehicle is at the desired speed. Plus and minus buttons provide for incremental speed variation whilst the cruise control is set.

One the user has selected a speed at which the vehicle is to be maintained, the vehicle is maintained at that speed for as long as the user does not apply a brake or, in the case of a vehicle having a manual transmission, depress a clutch pedal. The cruise control system takes its speed signal from a driveshaft speed sensor or wheel speed sensors. When the brake or a clutch pedal is depressed, the cruise control system is disabled so that the user can override the cruise control system to change the vehicle speed without resistance from the system. When the cruise control system is active, if the user depresses the accelerator pedal a sufficient amount the vehicle speed will increase, but once the user removes his foot from the accelerator pedal the vehicle reverts to the pre-set cruise speed by coasting.

Such systems are usually operable only above a certain speed, typically around 15-20kph, and are ideal in circumstances in which the vehicle is travelling in steady traffic conditions, and particularly on highways or motorways. In congested traffic conditions, however, where vehicle speed tends to vary widely, cruise control systems are ineffective, and especially where the systems are inoperable because of a minimum speed requirement. A minimum speed requirement is often imposed on cruise control systems so as to reduce the likelihood of low speed collision, for example when parking. Such systems are therefore ineffective in certain driving conditions (e.g. low speed) and are set to be automatically disabled in circumstances in which a user may not consider it to be desirable to do so.

More sophisticated cruise control systems are integrated into the engine management system and may include an adaptive functionality which takes into account the distance to the vehicle in front using a radar-based system. For example, the vehicle may be provided with a forward-looking radar detection system so that the speed and distance of the vehicle in front is detected and a safe following speed and distance is maintained automatically without the need for user input. If the lead vehicle slows down, or another object is detected by the radar detection system, the system sends a signal to the engine or the braking system to slow the vehicle down accordingly, to maintain a safe following distance.

Known cruise control systems also cancel in the event that a wheel slip event is detected requiring intervention by a traction control system (TCS) or stability control system (SCS). Accordingly, they are not well suited to maintaining vehicle progress when driving in off road conditions where such events may be relatively common.

Some vehicles are adapted for off-highway use, and low-speed cruise control systems for such vehicles have been developed. In off-highway conditions low-speed cruise control systems permit a driver, particularly a novice driver, to concentrate upon activities such as steering.

Low-speed cruise control systems suitable for off-road use may be configured to cause a vehicle to travel at a speed that is below the user-determined set-speed in dependence on the roughness of the terrain over which the vehicle is travelling. Nevertheless the present applicant has recognised that there are circumstances other than driving over rough terrain in which a reduced vehicle speed would be helpful to a user endeavouring to negotiate the terrain.

It is also known to provide a control system for a motor vehicle for controlling one or more vehicle subsystems. US7349776 discloses a vehicle control system comprising a plurality of subsystem controllers including an engine management system, a transmission controller, a steering controller, a brakes controller and a suspension controller. The subsystem controllers are each operable in a plurality of subsystem function or configuration modes.

The subsystem controllers are connected to a vehicle mode controller which controls the subsystem controllers to assume a required function mode so as to provide a number of driving modes for the vehicle. Each of the driving modes corresponds to a particular driving condition or set of driving conditions, and in each mode each of the sub-systems is set to the function mode most appropriate to those conditions. Such conditions are linked to types of terrain over which the vehicle may be driven such as grass/gravel/snow, mud and ruts, rock crawl, sand and a highway mode known as ‘special programs off’ (SPO). The vehicle mode controller may be referred to as a Terrain Response (TR) (RTM) System or controller. The driving modes may also be referred to as terrain modes, terrain response modes, or control modes.

GB2492655B discloses a control system for a motor vehicle in which the most appropriate terrain mode for the prevailing terrain over which the vehicle is driving is determined automatically by the control system. The control system then causes the vehicle to operate in the terrain mode determined to be the most appropriate.

It is against this background that the present invention has been conceived. Embodiments of the invention may provide an apparatus, a method or a vehicle which addresses the above problems. Other aims and advantages of the invention will become apparent from the following description, claims and drawings.

SUMMARY OF THE INVENTION

In one aspect of the invention for which protection is sought there is provided a detection system for a vehicle, comprising: detection means for generating data indicative of the height of a plurality of notional points on a surface of terrain ahead of the vehicle with respect to a reference frame and distance of the plurality of points from the vehicle; and path prediction means for generating a predicted path of the vehicle over terrain ahead of the vehicle; the system being configured to generate, for the predicted path of the vehicle, information indicative of a roughness of the terrain along the predicted path, and the system being configured to cause vehicle speed to be controlled in dependence at least in part on the information indicative of terrain roughness along the predicted path ahead of the vehicle.

Optionally, the predicted path may be generated at least in part in dependence on the data generated by the detection means.

In a further aspect of the invention for which protection is sought there is provided a terrain surface roughness detection system for a vehicle, the system comprising a processing means arranged to receive, from terrain data capture means arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle, wherein the processing means is configured to, in dependence upon a predicted path of the vehicle over said terrain extending ahead of the vehicle, generate, for the predicted path of the vehicle, terrain roughness information indicative of a roughness of the terrain along the predicted path, the system being configured to output an output signal in dependence on the terrain roughness information.

Optionally, the output signal comprises a signal indicative of the terrain roughness information.

Embodiments of the present invention have the advantage that, because the surface roughness detection system generates information indicative of terrain roughness ahead of the vehicle along the predicted path, vehicle may be controlled in a predictive manner rather than a reactive manner.

Optionally, the terrain information may comprise datapoints indicative of terrain height at a plurality of respective locations ahead of the vehicle, the processing means being configured to generate information indicative of the roughness of the terrain along the predicted path at least in part based on a vertical distance of the datapoints from a best fit line to the datapoints along the predicted path.

The terrain information may comprise stereoscopic images of terrain ahead of the vehicle, for example in the form of a stream of video images from respective left and right video cameras. The terrain data capture means may be configured to pass the images to the processing means, which may in turn be configured to generate 3D point cloud data from the stream of images.

Optionally, the processing means may be configured to predict a path of respective left and right wheels, or receive a signal indicative of the predicted path of respective left and right wheels, of the vehicle over said terrain and to calculate the information indicative of roughness of the terrain along the predicted path of the left and right wheels.

It will be understood that if the surface roughness calculation and speed adaption described herein is used in a fully autonomous vehicle the vehicle itself may determine what path it is going to take and feed this information into the processor such that the processor determines the surface roughness for the determined vehicle path. Alternatively the processor which determines surface roughness may itself determine a predicted vehicle path, or the processor which determines surface roughness may receive information of a predicted vehicle path from a separate processor which determines the predicted vehicle path.

Optionally, the processing means may be configured to receive a signal indicative of steering angle, and the processing means may be configured to determine the predicted path in dependence at least in part on the signal indicative of steering angle.

Optionally, the processing means may be configured to determine the predicted path in dependence at least in part on the terrain information.

Thus the terrain surface roughness detection system may determine a most likely route to be followed by a vehicle when traversing terrain ahead of the vehicle based at least in part on the terrain information. The terrain surface roughness detection system may take into account the presence of areas ahead of the vehicle with relatively abrupt changes in height and areas of relatively gradual increases in height, and favour a predicted path that tends to follow areas of relatively gradual increase in height. The predicted path may for example be determined from both the topography and/or appearance of the terrain. Alternatively map data could be used e.g. self-build maps and SLAM, or pre-defined high definition topographical maps as input into the path determination.

The terrain information indicative of the topography of an area extending ahead of the vehicle may comprise a 3D point cloud, or the processing means may be configured to generate, from said terrain information indicative of the topography of an area extending ahead of the vehicle, a 3D point cloud.

Optionally, the processing means may be configured to generate, from said point cloud, an elevation map of said terrain extending ahead of the vehicle.

Optionally, the terrain surface roughness detection system is configured to divide the elevation map into a cell map comprising a plurality of cells and to determine the cells through which respective left and right wheels of the vehicle will pass as the vehicle follows the predicted path. The cells of the cell map may each be representative of a sub region of the elevation map and may each contain a plurality of data points from the point cloud that fall within that sub region. In some embodiments the cell map may comprise cells of a regular size and shape.

Thus, a cell map having a reduced data set compared to the point loud data may be generated. The cell based elevation map may be a multi-level surface (MLS) map or any other suitable cell map.

The processing means may determine the cells through which respective left and right wheels of the vehicle will pass by overlaying the predicted path on the map.

Optionally, the terrain surface roughness detection system is configured to generate the information indicative of the roughness of the terrain along the predicted path in dependence at least in part on information indicative of the elevation of data points in the respective cells, or the average thereof, through which respective left and right wheels of the vehicle will pass.

Optionally, the terrain surface roughness detection system is configured to identify, in at least one of said point cloud and/or said cell map, objects overhanging terrain ahead of the vehicle and to ignore such objects in generating the information indicative of the roughness of the terrain along the predicted path.

Optionally, the information indicative of surface roughness may comprise a roughness descriptor, the roughness descriptor being generated at least in part by reference to a surface profile of terrain ahead of the vehicle along the predicted path. The roughness descriptor may be generated at least in part by a frequency calculation in the spatial domain, which may be at least one of a power spectral density, a Discreet Fourier Transform, a Fast Fourier Transform (FFT) and a Wavelet transform, of the surface profile of terrain ahead of the vehicle along the predicted path.

The system may be configured to control vehicle speed in dependence on the information indicative of terrain roughness.

Optionally, the terrain surface roughness detection system may be configured to generate a maximum speed value based on the information indicative of terrain roughness along the predicted path and to cause vehicle speed not to exceed the maximum speed value along the predicted path and wherein the output signal comprises said maximum speed value.

In some embodiments, the surface roughness detection system may determine a suitable speed for traversal of terrain ahead of the vehicle based on an estimated surface roughness of the terrain based on the topography information, and control vehicle speed (for example by increasing or decreasing vehicle speed) such that a suitable speed for traversal of a given stretch of terrain is attained before the vehicle reaches that stretch of terrain. Thus, if the vehicle is travelling over relatively smooth off-road terrain at a relatively high speed, such as 25kph, and the surface roughness detection system determines that relatively rough terrain exists ahead of the vehicle along the predicted path, the system may cause vehicle speed to be reduced before the vehicle traverses that terrain.

As noted above, the terrain surface roughness detection system may cause speed to be reduced by outputting to a speed control system a maximum speed signal indicative of a maximum advisable (or allowable) speed at a given moment in time. The maximum speed signal may be caused to indicate a reduced speed as the vehicle approaches a region of relatively rough terrain such that vehicle speed does not exceed the speed indicated by the maximum speed signal when traversing that terrain. Other arrangements may be useful in some embodiments.

Optionally, the terrain surface roughness detection system is configured to generate, for each of a plurality of portions of the predicted path ahead of the vehicle’s instant location, information indicative of terrain surface roughness over each respective portion, the system being configured to generate a corresponding maximum speed value for each respective portion, and wherein the output signal comprises said maximum speed value for each respective portion.

Optionally, the terrain surface roughness detection system may be configured to employ a machine learning regression model in order to generate the maximum speed value based at least in part on the information indicative of surface roughness.

Optionally, the terrain surface roughness detection system may be configured to employ a machine learning regression model comprising at least one of an artificial neural network (ANN) regression model or a support vector machine (SVM) regression model.

Optionally, the terrain surface roughness detection system may be configured to run the machine learning regression model substantially continuously, and to compare data in respect of measured values of surface roughness at a given location based on sensor inputs as the vehicle traverses terrain with the surface roughness values predicted based on the terrain information indicative of the topography of an area extending ahead of the vehicle, and refines the machine learning model to improve the accuracy with which future values of surface roughness are predicted.

Optionally, the regression model may be configured to take into account signals from a variety of sensors in respect of vehicle reaction to movement over terrain and to refine the maximum speed value in dependence thereon.

In some alternative embodiments the frequency calculation in the spatial domain, for example the power spectral density frequency, may be directly mapped with a use of weighted average of the frequency components to the target roughness values and/or the SR maximum speeds manually from experimental data without use of machine learning..

Optionally, the terrain surface roughness detection system may be configured to generate the maximum speed value based on the information indicative of terrain surface roughness by reference to a database of maximum speed as a function of information indicative of terrain surface roughness.

Optionally, the terrain surface roughness detection system further comprises the terrain data capture means.

Optionally, the terrain data capture means comprises one of: a stereoscopic camera system, a radar-based terrain ranging system, a laser-based terrain ranging system, a structured light camera, or a monocular camera with structure from motion.

It is to be understood that other terrain data capture means may be useful in some embodiments, such as an acoustic ranging system.

The terrain data capture means may be configured to generate 3D point cloud information for use in determining the surface roughness of the predicted path. Alternatively, the terrain data capture means may generate terrain data and provide the data to the terrain data input means, the system being configured to generate 3D point cloud information from the terrain data received by the terrain data input means.

Optionally, the processing means comprises one or more electronic processor, at least one said one or more electronic processor having an electrical input for receiving the terrain information indicative of the topography of the area extending ahead of the vehicle; and an electronic memory device electrically coupled to the electronic processor and having instructions stored therein, wherein the said one or more electronic processor is configured to access the memory device and execute the instructions stored therein such that it is operable to: determine the predicted path of the vehicle over terrain ahead of the vehicle, generate, for the predicted path of the vehicle, information indicative of the surface roughness of terrain along the predicted path, and output said output signal.

In a further aspect of the invention for which protection is sought there is provided a vehicle speed control system comprises a terrain surface roughness detection system according to another aspect, the speed control system being configured to control vehicle speed at least in part in dependence at least in part on the output signal.

Optionally, the speed control system is configured to control vehicle speed by limiting vehicle speed to a maximum set-speed value, the maximum set-speed value being determined in dependence at least in part on the information indicative of surface roughness along the predicted path.

Optionally, the speed control system is configured to generate a maximum speed value based on the information indicative of terrain roughness along the predicted path and to cause vehicle speed not to exceed the maximum speed value along the predicted path.

Optionally, the speed control system causes the vehicle speed not to exceed the maximum speed value along the predicted path.

In a further aspect of the invention for which protection is sought there is provided a vehicle comprising a surface roughness detection system, or a vehicle speed control system according to another aspect.

In an aspect of the invention for which protection is sought there is provided a method of detecting terrain surface roughness ahead of the vehicle comprising: receiving, from terrain data capture means arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle; in dependence upon information in respect of a predicted path of the vehicle over said terrain extending ahead of the vehicle, generating, for the predicted path of the vehicle, terrain roughness information indicative of a roughness of the terrain along the predicted path, the method comprising providing an output signal in dependence on the terrain roughness information.

Optionally the method comprises causing vehicle speed to be controlled in dependence at least in part on the terrain roughness information.

Optionally, causing vehicle speed to be controlled in dependence at least in part on the terrain roughness information comprises controlling vehicle speed by limiting vehicle speed to a maximum set-speed value, the maximum set-speed value being determined in dependence at least in part on the information indicative of surface roughness along the predicted path.

Optionally, the method further comprises generating information in respect of a predicted path of the vehicle over said terrain extending ahead of the vehicle.

Optionally, the method comprises generating the information in respect of the predicted path in dependence at least in part on steering angle.

Optionally, generating information indicative of the terrain roughness along the predicted path comprises generating information indicative of terrain roughness along respective left and right wheel tracks.

Optionally, generating information indicative of the terrain roughness along the predicted path comprises generating information indicative of terrain roughness along the predicted path over a predetermined distance ahead of the vehicle.

In an aspect of the invention for which protection is sought there is provided a non-volatile carrier medium carrying a computer readable code for controlling a vehicle to carry out the method of another aspect.

In an aspect of the invention for which protection is sought there is provided a computer program product executable on a processor so as to implement the method of another aspect.

In an aspect of the invention for which protection is sought there is provided a non-transitory computer readable medium loaded with the computer program product of another aspect.

In an aspect of the invention for which protection is sought there is provided a processor arranged to implement the method of another aspect, or the computer program product of another aspect.

Within the scope of this application it is expressly intended 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. That is, all embodiments and/or features of any embodiment can be combined in any way and/or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and/or incorporate any feature of any other claim although not originally claimed in that manner.

BRIEF DESCRIPTION OF DRAWINGS

The present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

FIGURE 1 is a schematic illustration of a vehicle according to an embodiment of the invention in plan view;

FIGURE 2 shows the vehicle of FIG. 1 in side view;

FIGURE 3 is a high level schematic diagram of an embodiment of the vehicle speed control system of the present invention, including a cruise control system and a low-speed progress control system;

FIGURE 4 illustrates a steering wheel of a vehicle according to the embodiment of FIG. 1;

FIGURE 5 is a schematic illustration of (a) a view of terrain ahead of the vehicle as captured by a stereoscopic camera system showing predicted left and right wheel tracks, and (b) a plan view of an elevation map of the terrain generated from stereoscopic image data;

FIGURE 6 illustrates the generation of roughness information based on 3D point cloud data; and

FIGURE 7 is a flow diagram illustrating operation of a vehicle according to the embodiment of FIG. 1.

DETAILED DESCRIPTION

References herein to a block such as a function block are to be understood to include reference to software code for performing the function or action specified which may be an output that is provided responsive to one or more inputs. The code may be in the form of a software routine or function called by a main computer program, or may be code forming part of a flow of code not being a separate routine or function. Reference to function block is made for ease of explanation of the manner of operation of embodiments of the present invention.

FIG. 1 shows a vehicle 100 according to an embodiment of the present invention. The vehicle 100 has a powertrain 129 that includes an engine 121 that is connected to a driveline 130 having an automatic transmission 124. It is to be understood that embodiments of the present invention are also suitable for use in vehicles with manual transmissions, continuously variable transmissions or any other suitable transmission.

In the embodiment of FIG. 1 the transmission 124 may be set to one of a plurality of transmission operating modes, being a park mode, a reverse mode, a neutral mode, a drive mode or a sport mode, by means of a transmission mode selector dial 124S. The selector dial 124S provides an output signal to a powertrain controller 11 in response to which the powertrain controller 11 causes the transmission 124 to operate in accordance with the selected transmission mode.

The driveline 130 is arranged to drive a pair of front vehicle wheels 111,112 by means of a front differential 137 and a pair of front drive shafts 118. The driveline 130 also comprises an auxiliary driveline portion 131 arranged to drive a pair of rear wheels 114, 115 by means of an auxiliary driveshaft or prop-shaft 132, a rear differential 135 and a pair of rear driveshafts 139.

Embodiments of the invention are suitable for use with vehicles in which the transmission is arranged to drive only a pair of front wheels or only a pair of rear wheels (i.e. front wheel drive vehicles or rear wheel drive vehicles) or selectable two wheel drive/four wheel drive vehicles. In the embodiment of FIG. 1 the transmission 124 is releasably connectable to the auxiliary driveline portion 131 by means of a power transfer unit (PTU) 131P, allowing operation in a two wheel drive mode or a four wheel drive mode. It is to be understood that embodiments of the invention may be suitable for vehicles having more than four wheels or where only two wheels are driven, for example two wheels of a three wheeled vehicle or four wheeled vehicle or a vehicle with more than four wheels.

A control system for the vehicle engine 121 includes a central controller 10, referred to as a vehicle control unit (VCU) 10, the powertrain controller 11, a brake controller 13 (an anti-lock braking system (ABS) controller) and a steering controller 170C. The ABS controller 13 forms part of a braking system 22 (FIG. 3). The VCU 10 receives and outputs a plurality of signals to and from various sensors and subsystems (not shown) provided on the vehicle. The VCU 10 includes a low-speed progress (LSP) control system 12 shown in FIG. 3, a stability control system (SCS) 14, a cruise control system 16 and a hill descent control (HDC) system 12HD. The SCS 14 improves the safety of the vehicle 100 by detecting and managing loss of traction or steering control. When a reduction in traction or steering control is detected, the SCS 14 is operable automatically to command the ABS controller 13 to apply one or more brakes of the vehicle to help to steer the vehicle 100 in the direction the user wishes to travel. In the embodiment shown the SCS 14 is implemented by the VCU 10. In some alternative embodiments the SCS 14 may be implemented by the ABS controller 13.

Although not shown in detail in FIG. 3, the VCU 10 further includes a Traction Control (TC) function block. The TC function block is implemented in software code run by a computing device of the VCU 10. The ABS controller 13 and TC function block provide outputs indicative of, for example, TC activity, ABS activity, brake interventions on individual wheels and engine torque requests from the VCU 10 to the engine 121 in the event a wheel slip event occurs. Each of the aforementioned events indicate that a wheel slip event has occurred. In some embodiments the ABS controller 13 implements the TC function block. Other vehicle sub-systems such as a roll stability control system or the like may also be included.

As noted above the vehicle 100 also includes a cruise control system 16 which is operable to automatically maintain vehicle speed at a selected speed when the vehicle is travelling at speeds in excess of 25 kph. The cruise control system 16 is provided with a cruise control HMI (human machine interface) 18 by which means the user can input a vehicle target speed to the cruise control system 16 in a known manner. In one embodiment of the invention, cruise control system input controls are mounted to a steering wheel 171 (FIG. 4). The cruise control system 16 may be switched on by pressing a cruise control system selector button 176. When the cruise control system 16 is switched on, depression of a ‘setspeed’ control 173 sets the current value (i.e. the target soeed) of a cruise control set-speed parameter, cruise_set-speed to the current vehicle speed. Depression of a '+’ button 174 allows the value of cruise_set-speed to be increased whilst depression of a button 175 allows the value of cruise_set-speed to be decreased. A resume button 173R is provided that is operable to control the cruise control system 16 to resume speed control at the instant value of cruise_set-speed following driver over-ride. It is to be understood that known onhighway cruise control systems including the present system 16 are configured so that, in the event that the user depresses the brake or, in the case of vehicles with a manual transmission, a clutch pedal, control of vehicle speed by the cruise control system 16 is cancelled and the vehicle 100 reverts to a manual mode of operation which requires accelerator or brake pedal input by a user in order to maintain vehicle speed. In addition, detection of a wheel slip event, as may be initiated by a loss of traction, also has the effect of cancelling control of vehicle speed by the cruise control system 16. Speed control by the system 16 is resumed if the driver subsequently depresses the resume button 173R.

The cruise control system 16 monitors vehicle speed and any deviation from the target vehicle speed is adjusted automatically so that the vehicle speed is maintained at a substantially constant value, typically in excess of 25 kph. In other words, the cruise control system is ineffective at speeds lower than 25 kph. The cruise control HMI 18 may also be configured to provide an alert to the user about the status of the cruise control system 16 via a visual display of the HMI 18. In the present embodiment the cruise control system 16 is configured to allow the value of cruise_set-speed to be set to any value in the range 25150kph.

The LSP control system 12 also provides a speed-based control system for the user which enables the user to select a very low target speed at which the vehicle can progress without any pedal inputs being required by the user to maintain vehicle speed. Low-speed speed control (or progress control) functionality is not provided by the on-highway cruise control system 16 which operates only at speeds above 25 kph.

In the present embodiment, the LSP control system 12 is activated by pressing LSP control system selector button 178 mounted on steering wheel 171. The system 12 is operable to apply selective powertrain, traction control and braking actions to one or more wheels of the vehicle 100, collectively or individually.

The LSP control system 12 is configured to allow a user to input a desired value of vehicle target speed in the form of a set-speed parameter, userset-speed, via a low-speed progress control HMI (LSP HMI) 20 (FIG. 1, FIG. 3) which shares certain input buttons 17315

175 with the cruise control system 16 and HDC control system 12HD. Provided the vehicle speed is within the allowable range of operation of the LSP control system 12 (which is the range from 2 to 30kph in the present embodiment although other ranges are also useful) and no other constraint on vehicle speed exists whilst under the control of the LSP control system 12, the LSP control system 12 controls vehicle speed in accordance with a LSP control system set-speed value LSP_set-speed which is set substantially equal to user setspeed. Unlike the cruise control system 16, the LSP control system 12 is configured to operate independently of the occurrence of a traction event. That is, the LSP control system 12 does not cancel speed control upon detection of wheel slip. Rather, the LSP control system 12 actively manages vehicle behaviour when slip is detected.

The LSP control HMI 20 is provided in the vehicle cabin so as to be readily accessible to the user. The user of the vehicle 100 is able to input to the LSP control system 12, via the LSP HMI 20, the desired value of userset-speed as noted above by means of the ‘set-speed’ button 173 and the ‘+7 ‘-‘ buttons 174, 175 in a similar manner to the cruise control system 16. The LSP HMI 20 also includes a visual display by means of which information and guidance can be provided to the user about the status of the LSP control system 12.

The LSP control system 12 receives an input from the ABS controller 13 of the braking system 22 of the vehicle indicative of the extent to which the user has applied braking by means of the brake pedal 163. The LSP control system 12 also receives an input from an accelerator pedal 161 indicative of the extent to which the user has depressed the accelerator pedal 161, and an input from the transmission or gearbox 124. This latter input may include signals representative of, for example, the speed of an output shaft of the gearbox 124, an amount of torque converter slip and a gear ratio request. Other inputs to the LSP control system 12 include an input from the cruise control HMI 18 which is representative of the status (ON/OFF) of the cruise control system 16, an input from the LSP control HMI 20, and an input from a gradient sensor 45 indicative of the gradient of the driving surface over which the vehicle 100 is driving. In the present embodiment the gradient sensor 45 is a gyroscopic sensor. In some alternative embodiments the LSP control system 12 receives a signal indicative of driving surface gradient from another controller such as the ABS controller 13. The ABS controller 13 may determine gradient based on a plurality of inputs, optionally based at least in part on signals indicative of vehicle longitudinal and lateral acceleration and a signal indicative of vehicle reference speed (v actual) being a signal indicative of actual vehicle speed over ground. Methods for the calculation of vehicle reference speed based for example on vehicle wheel speeds are well known. For example in some known vehicles the vehicle reference speed may be determined to be the speed of the second slowest turning wheel, or the average speed of all the wheels. Other ways of calculating vehicle reference speed may be useful in some embodiments, including by means of a camera device or radar sensor.

The HDC system 12HD is activated by depressing button 177 comprised by HDC system HMI 20HD and mounted on the steering wheel 171. When the HDC system 12HD is active, the system 12HD controls the braking system 22 in order to limit vehicle speed to a value corresponding to that of a HDC set-speed parameter HDC_set-speed which may be controlled by a user in a similar manner to the set-speed of the cruise control system 16 and LSP control system, using the same control buttons 173, 173R, 174, 175. The HDC system 12HD is operable to allow the value of HDC_set-speed to be set to any value in the range from 2-30kph. The HDC set-speed parameter may also be referred to as an HDC target speed. Provided the user does not override the HDC system 12HD by depressing the accelerator pedal 161 when the HDC system 12HD is active, the HDC system 12HD controls the braking system 22 (FIG. 3) to prevent vehicle speed from exceeding HDC_set-speed. In the present embodiment the HDC system 12HD is not operable to apply positive drive torque. Rather, the HDC system 12HD is only operable to cause negative brake torque to be applied, via the braking system 22.

It is to be understood that the VCU 10 is configured to implement a known Terrain Response (TR) (RTM) System of the kind described above in which the VCU 10 controls settings of one or more vehicle systems or sub-systems such as the powertrain controller 11 in dependence on a selected driving mode. The driving mode may be selected by a user by means of a driving mode selector 141S (FIG. 1). The driving modes may also be referred to as terrain modes, terrain response (TR) modes, or control modes.

In the embodiment of FIG. 1 four driving modes are provided: an Όη-highway’ driving mode suitable for driving on a relatively hard, smooth driving surface where a relatively high surface coefficient of friction exists between the driving surface and wheels of the vehicle; a ‘sand’ driving mode suitable for driving over sandy terrain, being terrain characterised at least in part by relatively high drag, relatively high deformability or compliance and relatively low surface coefficient of friction; a ‘grass, gravel or snow’ (GGS) driving mode suitable for driving over grass, gravel or snow, being relatively slippery surfaces (i.e. having a relatively low coefficient of friction between surface and wheel and, typically, lower drag than sand); a ‘rock crawl’ (RC) driving mode suitable for driving slowly over a rocky surface; and a ‘mud and ruts’ (MR) driving mode suitable for driving in muddy, rutted terrain. Other driving modes may be provided in addition or instead. In the present embodiment the selector 141S also allows a user to select an ‘automatic driving mode selection condition’ of operation in which the VCU 10 selects automatically the most appropriate driving mode as described in more detail below. The on-highway driving mode may be referred to as a ‘special programs off’ (SPO) mode in some embodiments since it corresponds to a standard or default driving mode, and is not required to take account of special factors such as relatively low surface coefficient of friction, or surfaces of high roughness.

In order to prevent or at least reduce passenger discomfort due to rapid changes in acceleration rate (jerk) when the LSP control system 12 is controlling vehicle speed, the LSP control system 12 limits the rate of change of acceleration of the vehicle 100 such that it does not exceed a prescribed maximum value. The maximum allowable rate of change of acceleration or maximum allowable jerk value is provided by parameter LSP_J_MAX. The LSP control system 12 also limits the maximum value of rate of acceleration to a value LSPAMAX.

The values of LSP_A_MAX and LSP_J_MAX are set in dependence at least in part on TR mode and vehicle speed. In some embodiments, including the present embodiment, the values for TR_mode=sand are higher than the corresponding values for TR_mode=SPO, GGS or MR due to the higher drag imposed on a vehicle 100 traversing sand compared with a vehicle traversing a dry asphalt highway surface, a grass, gravel or snow surface, or a muddy or rutted surface.

The LSP control system 12 causes the vehicle 100 to operate in accordance with the value of LSP_set-speed.

In order to cause application of the necessary positive or negative torque to the wheels, the VCU 10 may command that positive or negative torque is applied to the vehicle wheels by the powertrain 129 and/or that a braking force is applied to the vehicle wheels by the braking system 22, either or both of which may be used to implement the change in torque that is necessary to attain and maintain a required vehicle speed. In some embodiments torque is applied to the vehicle wheels individually, for example by powertrain torque vectoring, so as to maintain the vehicle at the required speed. Alternatively, in some embodiments torque may be applied to the wheels collectively to maintain the required speed, for example in vehicles having drivelines where torque vectoring is not possible. In some embodiments, the powertrain controller 11 may be operable to implement torque vectoring to control an amount of torque applied to one or more wheels by controlling a driveline component such as a rear drive unit, front drive unit, differential or any other suitable component. For example, one or more components of the driveline 130 may include one or more clutches operable to allow an amount of torque applied to one or more wheels to be varied. Other arrangements may also be useful.

Where a powertrain 129 includes one or more electric machines, for example one or more propulsion motors and/or generators, the powertrain controller 11 may be operable to modulate torque applied to one or more wheels in order to implement torque vectoring by means of one or more electric machines.

In some embodiments the LSP control system 12 may receive a signal wheel_slip (also labelled 48 in FIG. 3) indicative of a wheel slip event having occurred. This signal 48 is also supplied to the on-highway cruise control system 16 of the vehicle, and which in the case of the latter triggers an override or inhibit mode of operation in the on-highway cruise control system 16 so that automatic control of vehicle speed by the on-highway cruise control system 16 is suspended or cancelled. However, the LSP control system 12 is not arranged to cancel or suspend operation on receipt of wheel_slip signal 48. Rather, the system 12 is arranged to monitor and subsequently manage wheel slip so as to reduce driver workload. During a slip event, the LSP control system 12 continues to compare the measured vehicle speed with the value of LSP_set-speed, and continues to control automatically the torque applied to the vehicle wheels (by the powertrain 129 and braking system 22) so as to maintain vehicle speed at the selected value. It is to be understood therefore that the LSP control system 12 is configured differently to the cruise control system 16, for which a wheel slip event has the effect of overriding the cruise control function so that manual operation of the vehicle must be resumed, or speed control by the cruise control system 16 resumed by pressing the resume button 173R or set-speed button 173.

The vehicle 100 is also provided with additional sensors (not shown) which are representative of a variety of different parameters associated with vehicle motion and status. These may be inertial systems unique to the LSP or HDC control systems 12, 12HD or part of an occupant restraint system or any other sub-system which may provide data from sensors such as gyros and/or accelerometers that may be indicative of vehicle body movement and may provide a useful input to the LSP and/or HDC control systems 12, 12HD. The signals from the sensors provide, or are used to calculate, a plurality of driving condition indicators (also referred to as terrain indicators) which are indicative of the nature of the terrain conditions over which the vehicle 100 is travelling.

The sensors (not shown) on the vehicle 100 include, but are not limited to, sensors which provide continuous sensor outputs to the VCU 10, including wheel speed sensors, as mentioned previously, an ambient temperature sensor, an atmospheric pressure sensor, tyre pressure sensors, wheel articulation sensors, gyroscopic sensors to detect vehicular yaw, roll and pitch angle and rate, a vehicle speed sensor, a longitudinal acceleration sensor, an engine torque sensor (or engine torque estimator), a steering angle sensor, a steering wheel speed sensor, a gradient sensor (or gradient estimator), a lateral acceleration sensor which may be part of the SCS 14, a brake pedal position sensor, a brake pressure sensor, an accelerator pedal position sensor, longitudinal, lateral and vertical motion sensors, and water detection sensors forming part of a vehicle wading assistance system (not shown). In other embodiments, only a selection of the aforementioned sensors may be used.

The VCU 10 also receives a signal from the steering controller 170C. The steering controller 170C is in the form of an electronic power assisted steering unit (ePAS unit) 170C. The steering controller 170C provides a signal to the VCU 10 indicative of the steering force being applied to steerable road wheels 111, 112 of the vehicle 100. This force corresponds to that applied by a user to the steering wheel 171 in combination with steering force generated by the ePAS unit 170C. The ePAS unit 170C also provides a signal indicative of steering wheel rotational position or angle.

In the present embodiment, the VCU 10 evaluates the various sensor inputs to determine the probability that each of the plurality of different TR modes (control modes or driving modes) for the vehicle subsystems is appropriate, with each control mode corresponding to a particular terrain type over which the vehicle is travelling (for example, mud and ruts, sand, grass/gravel/snow) as described above.

If the user has selected operation of the vehicle in the automatic driving mode selection condition, the VCU 10 then selects the most appropriate one of the control modes and is configured automatically to control the subsystems according to the selected mode. This aspect of the invention is described in further detail in our co-pending patent applications GB2492748, GB2492655 and GB2499279, the contents of each of which is incorporated herein by reference as noted above.

As indicated above, the nature of the terrain over which the vehicle is travelling (as determined by reference to the selected control mode) may also be utilised in the LSP control system 12 to determine an appropriate increase or decrease in vehicle speed. If the user selects a value of userset-speed that is not suitable for the nature of the terrain over which the vehicle is travelling, the system 12 is operable to automatically adjust the value of LSP_set-speed to a value lower than userset-speed. If the system 12 selects a set-speed (a value of LSP_set-speed) that differs from the user-selected set-speed user set-speed, a visual indication of the speed constraint is provided to the user via the LSP HMI 20 to indicate that an alternative speed has been adopted.

In an embodiment of the present invention a processing unit 19 (which may be a stand-alone processing unit or one or more processing units having shared functionality with other on board control systems) determines the surface roughness as described below and outputs an output signal in dependence thereon.

In one arrangement, the VCU 10 is configured to determine an appropriate vehicle speed based on signals indicative of the terrain ahead of the vehicle 100 at a given moment in time. In the present embodiment the VCU 10 generates a ‘surface roughness (SR) maximum speed signal’ indicative of a maximum advisable value of LSP_set-speed at a given moment in time based on the output signal from the processing unit 19. This signal may, in some embodiments, be indicative of an actual speed or alternatively may be a speed metric which may for example indicate a percentage reduction of set speed, or may just be a numerical value (e.g. 1 to 5) that is indicative of a maximum speed relative to the set speed. When active, the LSP control system 12 controls vehicle speed in such a manner as to attempt to cause vehicle speed not to exceed the SR maximum speed signal at a given moment in time.

Although described in relation to a speed control system it will be appreciated that the output signal indicative of surface roughness could be used to control any vehicle setting. The processing unit 19 may output a surface roughness metric, for example a numerical value (or electrical signal representative thereof) in the range of, for example, 1 to 5 indicative of the roughness of the surface. This signal may be output to a CAN bus or other communications system on a vehicle and may be used by any on-board controller for which it may be desirable to adapt its function in dependence on the surface roughness, for example a vehicle suspension setting controller, a seat bolster position controller etc. It will be recognised that the invention lies not only in speed control dependant on surface roughness but in the determination of surface roughness. In some embodiments the processing unit 19 may output a signal indicative of surface roughness and a signal indicative of a maximum speed requirement.

In the present embodiment, the processing unit 19 is configured to calculate a value of surface roughness of the driving surface over a predicted path ahead of the vehicle 100 based at least in part on 3D terrain information captured by the vehicle 100.

In the present embodiment, the vehicle 100 is provided with a stereoscopic camera system 185C configured to generate stereo colour image pairs by means of a pair of forward-facing colour video cameras comprised by the system 185C. A stream of dual video image data is fed from the cameras to the processing unit 19 (which may also be referred to as a processing portion 19) that processes the image data received and repeatedly generates a 3D point cloud data set based on the images received. Techniques for generating 3D point cloud data sets based on stereoscopic image data are well known. Each point in the 3D point cloud data set corresponds to a 3D co-ordinate of a point on a surface of terrain ahead of the vehicle 100 viewed by each of the forward-facing video cameras of the stereoscopic camera system 185C.

It is to be understood that, in some embodiments, non-colour, grey-scale (black and white) cameras may be employed instead of colour cameras. Furthermore, in some further embodiments a different camera arrangement such as structured light cameras or a monocular camera with SFM (structure from motion) may be employed instead of a stereoscopic camera system. In some alternative embodiments a sensor system other than a camera system may be employed, such as a LIDAR (Light Detection And Ranging) system.

In the present embodiment the 3D point cloud dataset is transformed such that the origin of the frame of reference of the dataset is the midpoint of a line joining the points at which the two front wheels 111, 112 of the vehicle 100 touch the ground over which the vehicle 100 is driving (also referred to herein as contact points or patches). In the present embodiment the frame of reference is defined with respect to Cartesian co-ordinates X, Y, Z where X is an axis transverse to the direction of vehicle travel, i.e. along a lateral direction with respect to the vehicle 100, Y is an axis oriented in an upward direction with respect to the vehicle 100, corresponding to a substantially vertically upward direction when the vehicle 100 is parked on level ground, and Z is parallel to or coincident with a longitudinal axis of the vehicle 100, along the direction of travel of the vehicle 100.

The processing unit 19 also receives data indicative of steering angle from the ePAS unit 170C via signal line 170L and takes this data into account in determining the predicted path. In the present embodiment the predicted path is taken to be a path of the vehicle 100 that would be followed if the steering angle remained in the instant position at a given moment in time. In some alternative embodiments the predicted path may be determined at least in part in dependence on knowledge of the topography of terrain ahead of the vehicle. Thus in the event that a predicted path based entirely on instant steering angle included a region of terrain having a steepness exceeding a predetermined value, the processing unit 19 may adjust the predicted path so as to avoid this region. It will be appreciated however that any method of determining a predicted path of a vehicle may be used. The predicted path may for example be determined from both the topography and/or appearance of the terrain. Alternatively map data could be used e.g. self-build maps and SLAM, or pre-defined high definition topographical maps.

FIG. 5(a) is a schematic representation of an image of terrain ahead of the vehicle 100 as captured by one of the two cameras of the camera system 185C. Superimposed on the image is a centreline of a predicted path PP of the vehicle 100 over the terrain as determined by the processing unit 19. The predicted tracks of respective left and right wheels over the terrain are labelled PL and PR. In the example shown, steering wheel 171 of the vehicle 100 is centred, i.e. in the ‘straight ahead’ position, and the processing unit 19 has determined that the predicted path PP lies in a straight line directly ahead of the vehicle 100.

The processing unit 19 is configured to compute a terrain elevation map populated by data points of the point cloud dataset. FIG. 5(b) is a schematic illustration in plan view of an elevation map of terrain ahead of the vehicle 100. In the present embodiment the elevation map is generated with respect to the vehicle axes X, Y, Z (i.e. in the vehicle frame of reference). Following the MLS (multi-level surface) map methodology, the elevation map is notionally considered to be composed of square cells C in the X-Z plane of predetermined size as illustrated schematically in FIG. 5(b) (see inset). In the present embodiment the cells are of side 0.25m although other sizes may be useful in some embodiments. It will be appreciated that the use of MLS maps is a means of reducing the number of data points so as to reduce the processing power that would be required to calculate the surface roughness if each individual data point of the point cloud were to be used. It will also be appreciated that the data points of the point cloud dataset can be used to create any cell based elevation mapping technique that groups point cloud data points into groups so as to reduce the processing requirement.

It will be appreciated, however, that if sufficient processing power is available that the surface roughness may be determined using the point cloud data directly, which would be filtered to remove outliers attributable to noise, without the need to convert it to an MLS map first.

In the present embodiment, each 3D point of the elevation map is assigned to a cell C according to its position with respect to the X-Z plane. A given cell may contain points that are at multiple levels or heights, i.e. having different values of Y co-ordinate. The points within a given cell are grouped into one or more respective ‘patches’ according to the value of the Y co-ordinate, points having a Y co-ordinate within a given predetermined range of values of the Y co-ordinate being assigned to a patch corresponding to that range of values of Y co-ordinate. Where patches of points having different y co-ordinates are identified in the same cell the range they may, for example, be defined by a +/- range in the y axis around an average y value of each patch. Thus, for example, although points within a given patch may have a different y co-ordinate, as they are allocated within a range they are attributable to the same surface. Each patch may be defined as being substantially parallel to the X-Z plane, for example it may be defined as an x-z pane the size of the patch having a y coordinate which is the average value of y co-ordinate for that patch. In contrast, points within the same cell that correspond to a different surface, for example a bridge passing over the driving surface, or an overhanging tree branch, would not form part of the same patch as points falling on the driving surface. It is to be understood that each patch contains information regarding the geometry of the points falling within that patch.

It is to be understood that data structures other than MLS maps may be employed, for example Voxel maps, or any other electronic surface mapping technology that reduces the number of data points to be analysed, may also be used, the purpose of the map being to reduce the number of data points.

The processing unit 19 analyses the cells and a cell is labelled as an Obstacle’ cell if the variance and range of the data points in the lowest patch of the cell exceed respective predetermined threshold values. Additionally, in some arrangements a cell is labelled as an Obstacle’ cell if an overhanging patch is detected having a height below a vehicle dependant threshold value. In some alternative embodiments, mean height may be employed instead. In some embodiments, height difference (mean height) between a current cell and neighbouring cells may be used to detect obstacles, i.e. relatively large steps in height between neighbouring cells may indicate the presence of an obstacle. Cells not labelled as obstacle cells may be labelled as a ‘horizontal patch’. If a cell does not contain any points it may be labelled an ‘empty patch’.

In addition to implementing the MLS methodology as described above, the elevation map is refined such that overhanging patches falsely labelled as horizontal patches are discarded. An overhanging patch is a patch that is at a different height to a corresponding lower patch of the same cell consistent with the presence of an object that overhangs the surface over which the vehicle 100 is driving such as a branch of a tree or bridge that the vehicle 100 is passing underneath.

Cells labelled as obstacle cells are not employed in the calculation of surface roughness. Furthermore, cells that are behind obstacles and which would be occluded from camera view (Obstacle shadows’ or ‘shadow cells’) are identified and also disregarded. This is because they may interfere with correct surface roughness calculation.

The surface roughness is calculated from the predicted path by using only those cells with confidence value greater than a specified threshold. Cells which are marked as obstacles and empty are not considered for the surface roughness calculation.

The processing unit 19 then determines the cells ahead of the vehicle 100 through which front tyres of the vehicle 100 are predicted to pass, i.e. cells through which the predicted tracks PL, PR of the left and right front wheels 111, 112 will likely pass including cells labelled as obstacle cells. The processing unit 19 employs a known value of track length T of the vehicle 100 (i.e. the distance between the centres of wheels of a given axle, which is lower than the vehicle overall width, W of the vehicle 100) in order to determine the predicted tracks PL, PR.

In the present embodiment the processing unit 19 generates a line surface height profile along each of the respective left and right wheel tracks along the predicted path. The processing unit 19 then performs a DC-offset subtraction function in which the processing unit 19 generates a modified line profile that has variations in surface height due to the presence of topographical features such as hills and valleys removed, so that terrain height variation is due to relatively short range variations in surface height, over distances of the order of 0.1 to 10m, rather than longer range variations, over distances of 10m or more. In particular The DC-offset removal is employed to remove the discontinuities at the end of the profile sample (i.e. at the end of the range of the sensor technology) which will generate high amplitude response in the frequency domain not representative of the surface roughness. This removes the impact of constant gradient as without DC removal constant gradient will generate high amplitude DC component and will also leak into other frequencies, i.e. it removes impact of the terrain variation with wavelengths exceeding 10 m.

The modified line profile is then fed into a surface roughness measurement algorithm run by the processing unit 19 that outputs a metric indicative of the roughness of terrain ahead of the vehicle 100.

In the present embodiment, the processing unit 19 calculates a power spectral density (PSD) in the spatial domain, i.e. with respect to distance, of the line profile of the respective left and right wheel tracks to generate a PSD descriptor of the roughness of the surface ahead of the vehicle 100. In some alternative embodiments another form of frequency-based roughness calculation may be performed such as a Fast Fourier Transform (FFT), Wavelet transform or any other suitable calculation.

The roughness descriptor is passed to a speed conversion algorithm that calculates a SR maximum speed value in dependence on the PSD descriptor. The VCU 10 in turn adjusts the value of LSP_set-speed when required in order to attempt to ensure that the LSP control system 12 does not allow the vehicle to exceed the SR maximum speed value generated by the speed conversion algorithm at a given moment in time.

In the present embodiment, the speed conversion algorithm takes the content generated by the roughness measurement algorithm and feeds it to a machine learning regression model in order to generate the SR maximum speed value. In the present embodiment, an artificial neural network (ANN) regression model is employed. In some alternative embodiments a different regression model may be employed, such as a support vector machine (SVM) regression model. Is described below, it is to be understood that the machine learning regression model may take into account signals from a variety of sensors in respect of vehicle reaction to movement over terrain in order to attempt to refine the maximum speed value so that vehicle speed over terrain is not excessively low or high. It is to be understood that a designed weighted function may be applied to the content generated by the roughness measurement algorithm before it is fed to the machine learning regression model.

In some alternative embodiments, the PSD frequency content may be directly mapped with a use of weighted average of the frequency components to the target roughness values and/or the SR maximum speeds manually from experimental data without use of machine learning.

It is to be understood that, in the present embodiment, since the processing unit 19 analyses a stretch of surface profile ahead of the vehicle 100 and provides a single maximum speed value, the processing unit 19 assigns this value to a specific predetermined location ahead of the vehicle 100, i.e. a location a predetermined distance ahead of the current position of the vehicle 100. The VCU 10 then attempts to control the LSP control system 12 so as to ensure that the speed of the vehicle 100 does not exceed the maximum value calculated by the processing unit 19 when the vehicle 100 reaches that location. Thus the VCU 10 manages vehicle acceleration and deceleration so that the maximum speed value is not exceeded when the vehicle 100 reaches the predetermined location. The vehicle may use updated predicted path data, e.g. steering wheel data and/or information received from an inertial measurement unit (IMU) to determine if the vehicle deviated from the predicted path for which the surface roughness has been calculated and/or to determine whether the vehicle has passed an area of predicted path for which the speed controller was controlling the maximum speed.

In the present embodiment, the processing unit 19 runs the machine learning regression model substantially continuously, and compares data in respect of measured values of surface roughness at a given location based on sensor inputs as the vehicle 100 traverses terrain with the values predicted based on camera image data and refines the machine learning model to improve the accuracy with which future values of surface roughness are predicted.

The machine learning model also takes into account actual values of vehicle speed as the vehicle traverses terrain in determining a SR maximum speed value. In the present embodiment the VCU 10 monitors driver override of the LSP control system 12 in situations where the LSP control system 12 has set a maximum allowable value of LSP_set-speed, based on terrain surface roughness, that is below the value of userset-speed, such that the LSP control system 12 has caused speed to be reduced below the user set value, user setspeed. When such circumstances arise, feedback is provided to the processing unit 19 indicating that driver override to a higher speed has occurred, in response to which the machine learning model is adjusted to take into account the fact that driver override occurred, indicating a higher speed was considered acceptable when driving over that stretch of terrain. The result is that, if similar terrain is subsequently encountered, a higher value of maximum speed value may be set by the processing unit 19.

Conversely, if driver override is detected in which the driver reduces vehicle speed over a given stretch of terrain below the SR maximum speed value determined by the processing unit 19, feedback is again provided to the processing unit 19. In response to the feedback, the machine learning model is adjusted to take into account the fact that driver override occurred. The result is that, if similar terrain is subsequently encountered, a lower value of SR maximum speed value may be set by the processing unit 19.

FIG. 6 (a) shows an image of a cross-country track captured by a camera of the camera module 185C. FIG. 6(b) is graphical representation of surface line profiles of a left wheel track of a predicted path of the vehicle 100 along the track as a function of time. The vertical axis of the plot represents distance in m, over the range from 5m (at the origin) to 15m whilst the horizontal axis represents time in seconds. FIG. 6(c) is a corresponding power spectral density (PSD) plot based on the data shown in FIG. 6(b), the vertical axis representing spatial frequency (in cycles per m) from 0 to 2 cycles per m whilst the horizontal axis represents time in seconds and corresponds to the time period indicated in FIG. 6(b).

FIG. 6(d) to (f) corresponds to FIG. 6(a) to (c) but for a dirt track as opposed to a crosscountry track. The dirt track of FIG. 6(d) is relatively smooth compared with the cross-country track of FIG. 6(a) and permits travel at higher speeds for a given desired comfort level.

FIG. 7 is a schematic illustration of the manner in which vehicle speed is controlled in dependence on the roughness of terrain ahead of the vehicle 100.

At step S101 the VCU 10 receives an input indicative of instant steering wheel position and at step S103 generates data indicative of a predicted path of the vehicle 100 over terrain ahead of the vehicle in dependence on the steering angle.

At step S105 the processing unit 19 receives stereo colour image pairs from camera system 185C and calculates disparity data in respect of the image pairs. At step S107 a 3D point cloud is generated based on the disparity data. At step S109 the processing unit 19 computes a terrain elevation map populated by data points of the point cloud dataset according to the MLS map methodology, each cell of the MLS being of side 0.25m in the present embodiment.

At step S111 the processing unit 19 generates a line surface height profile along respective left and right wheel tracks along the predicted path based on the results of steps S103 and S109 and performs the DC-offset subtraction function in an attempt to remove variations in surface height due to the presence of topographical features such as hills and valleys. In some embodiments the signal may be subject to a filter function configured to filter out components of the signal of wavelength greater than around 5-10m. Other arrangements may be useful.

At step S113 the processing unit 19 calculates the PSD descriptor in respect of the surface height profiles along the respective left and right wheel tracks. At step S114 the PSD descriptors for the left and right tracks are fed to the speed conversion algorithm that generates a maximum speed value based on the descriptors. As noted above, the SR maximum speed value is a maximum recommended value of speed of the vehicle 100, based on surface roughness, when the vehicle 100 passes a location that is a predetermined distance ahead of the vehicle’s instant location. At step S115 this maximum speed value is output to the VCU 10. The VCU 10 then attempts to control the LSP control system 12 so as to ensure that the speed of the vehicle 100 does not exceed the maximum value calculated by the processing unit 19 when the vehicle 100 reaches the location that is the predetermined distance ahead of the instant location of the vehicle 100.

In the present embodiment the processing unit 19 is configured to calculate power spectral density (PSD) descriptors of the roughness of the surface ahead of the vehicle 100 over a predetermined stretch of terrain ahead of the vehicle from a distance of substantially 5m to a distance of substantially 15m ahead of the vehicle 100 along the predicted left and right wheel tracks. In some alternative embodiments, the processing unit may calculate a power spectral density (PSD) descriptor of the roughness of the surface ahead of the vehicle 100 over two or more respective predetermined stretches of terrain ahead of the vehicle, such as a distance from substantially 5 to substantially 10m, and from substantially 10m to substantially 15m ahead of the vehicle 100. The processing unit 19 may calculate maximum speed values for the respective stretches and cause the LSP control system 12 to control vehicle speed so as not to exceed the respective values when the vehicle 100 reaches those stretches of terrain.

The roughness descriptor is passed to a speed conversion algorithm that calculates a maximum speed value in dependence on the PSD descriptor. The VCU 10 in turn adjusts the value of LSP_set-speed when required in order to attempt to ensure that the LSP control system 12 does not allow the vehicle to exceed the maximum speed value generated by the speed conversion algorithm at a given moment in time.

It is to be understood that, in some embodiments, if the predicted path changes substantially, for example due to a change in steering angle, the processing unit 19 may determine that the maximum speed data that is being and has been output by the unit 19 to the LSP control system 12 is no longer valid. In such a situation the processing unit 19 may cause the LSP control system 12 to suspend causing any increase in vehicle speed until maximum speed data has been determined for the new predicted path. Other arrangements may be useful in some embodiments.

It is to be further understood that, in some embodiments, the value of SR maximum speed may be weighted at least in part in dependence on the TR mode in which the vehicle 100 is operating at a given moment in time. Thus, for a given roughness descriptor, the SR maximum speed value may be higher or lower depending on the TR mode at a given moment in time. Alternatively, the value of SR maximum speed may be weighted at least in part in dependence on a user selectable setting. In one embodiment the value of SR maximum speed may be weighted at least in part in dependence on a user set comfort requirement in which the vehicle 100 is operating at a given moment in time. Thus, for a given roughness descriptor, the SR maximum speed value may be higher or lower depending on the user comfort requirement at a given moment in time. Other arrangements may be useful in some embodiments.

Some embodiments of the present invention enable vehicle operation with enhanced composure when traversing terrain. This is at least in part due to a reduction in driver workload when operating with the LSP control system 12 active. This is because a driver is not required manually to decrease the value of userset-speed in order to reduce vehicle speed when approaching terrain having a roughness for which the current vehicle speed may be too high, or manually increase the value of user set-speed when approaching terrain that is relatively smooth. Rather, the vehicle 100 anticipates changes in surface roughness and adjusts vehicle speed accordingly.

It will be understood that the embodiments described above are given by way of example only and are not intended to limit the invention, the scope of which is defined in the appended claims.

Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of the words, for example “comprising” and “comprises”, means “including but not limited to”, and is not intended to (and does not) exclude other moieties, additives, components, integers or steps.

Throughout the description and claims of this specification, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

Features, integers, characteristics, compounds, chemical moieties or groups described in conjunction with a particular aspect, embodiment or example of the invention are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith.

Claims

CLAIMS:

1. A terrain surface roughness detection system for a vehicle, the system comprising a processing means arranged to receive, from terrain data capture means arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle, wherein the processing means is configured to, in dependence upon a predicted path of the vehicle over said terrain extending ahead of the vehicle, generate, for the predicted path of the vehicle, terrain roughness information indicative of a roughness of the terrain along the predicted path, the system being configured to output an output signal in dependence on the terrain roughness information.

2. A terrain surface roughness detection system according to claim 1 wherein the output signal comprises a signal indicative of the terrain roughness information.

3. A terrain surface roughness detection system according to claim 1 or claim 2 wherein the terrain information comprises data points indicative of terrain height at a plurality of respective locations ahead of the vehicle, the processing means being configured to generate information indicative of the roughness of the terrain along the predicted path at least in part based on a vertical distance of the data points from a best fit line to the data points along the predicted path.

4. A terrain surface roughness detection system according to any preceding claim wherein the processing means is configured to predict a path of respective left and right wheels, or receive a signal indicative of the predicted path of respective left and right wheels, of the vehicle over said terrain and to calculate the information indicative of roughness of the terrain along the predicted path of the left and right wheels.

5. A terrain surface roughness detection system according to any preceding claim wherein the processing means is configured to receive a signal indicative of steering angle, and wherein the processing means is configured to determine the predicted path in dependence at least in part on the signal indicative of steering angle.

6. A terrain surface roughness detection system according to any preceding claim wherein the processing means is configured to determine the predicted path in dependence at least in part on the terrain information.

7. A terrain surface roughness detection system according to any preceding claim wherein said terrain information indicative of the topography of an area extending ahead of the vehicle comprises a 3D point cloud, or wherein the processing means is configured to generate, from said terrain information indicative of the topography of an area extending ahead of the vehicle, a 3D point cloud.

8. A terrain surface roughness detection system according to claim 6 or claim 7 wherein the processing means is configured to generate, from said point cloud, an elevation map of said terrain extending ahead of the vehicle.

9. A terrain surface roughness detection system according to claim 8 configured to divide the elevation map into cell map comprising a plurality of cells and to determine the cells through which respective left and right wheels of the vehicle will pass as the vehicle follows the predicted path.

10. A terrain surface roughness detection system according to claim 9 configured to generate the information indicative of the roughness of the terrain along the predicted path in dependence at least in part on information indicative of the elevation of data points in the respective cells, or the average thereof, through which respective left and right wheels of the vehicle will pass.

11. A terrain surface roughness detection system according to any one of claims 7 to 10 configured to identify, in at least one of said point cloud and/or said cell map, objects overhanging terrain ahead of the vehicle and to ignore such objects in generating the information indicative of the roughness of the terrain along the predicted path.

12. A terrain surface roughness detection system according to any preceding claim wherein the information indicative of surface roughness comprises a roughness descriptor, the roughness descriptor being generated at least in part by reference to a surface profile of terrain ahead of the vehicle along the predicted path, and wherein the roughness descriptor is generated at least in part by a frequency calculation in the spatial domain, which may be at least one of a power spectral density, a Discreet Fourier Transform, a Fast Fourier Transform and a Wavelet transform, of the surface profile of terrain ahead of the vehicle along the predicted path.

13. A terrain surface roughness detection system according to claim 1 to 12 further configured to generate a maximum speed value based on the information indicative of terrain roughness along the predicted path and wherein the output signal comprises said maximum speed value.

14. A terrain surface roughness detection system according to claim 13 configured to generate, for each of a plurality of portions of the predicted path ahead of the vehicle’s instant location, information indicative of terrain surface roughness over each respective portion, the system being configured to generate a corresponding maximum speed value for each respective portion, and wherein the output signal comprises said maximum speed value for each respective portion.

15. A terrain surface roughness detection system according to claim 13 or 14 configured to employ a machine learning regression model in order to generate the maximum speed value based at least in part on the information indicative of surface roughness.

16. A terrain surface roughness detection system according to claim 15 configured to employ a machine learning regression model comprising at least one of an artificial neural network regression model or a support vector machine regression model.

17. A terrain surface roughness detection system according to claim 16 wherein configured to run the machine learning regression model substantially continuously, and to compare data in respect of measured values of surface roughness at a given location based on sensor inputs as the vehicle traverses terrain with the surface roughness values predicted based on the terrain information indicative of the topography of an area extending ahead of the vehicle, and refines the machine learning model to improve the accuracy with which future values of surface roughness are predicted.

18. A terrain surface roughness detection system according to any one of claims 15 to 17 configured wherein the regression model is configured to take into account signals from a variety of sensors in respect of vehicle reaction to movement over terrain and to refine the maximum speed value in dependence thereon.

19. A terrain surface roughness detection system according to claim 13 or claim 14 configured to generated the maximum speed value based on the information indicative of terrain surface roughness by reference to a database of maximum speed as a function of information indicative of terrain surface roughness.

20. A terrain surface roughness detection system according to any preceding claim further comprising the terrain data capture means.

21. A terrain surface roughness according to claim 20 wherein the terrain data capture means comprises one of: a stereoscopic camera system, a radar-based terrain ranging system, a laser-based terrain ranging system, a structured light camera, or a monocular camera with structure from motion.

22. A terrain surface roughness detection system according to any preceding claim, wherein the processing means comprises one or more electronic processor, at least one said one or more electronic processor having an electrical input for receiving the terrain information indicative of the topography of the area extending ahead of the vehicle; and an electronic memory device electrically coupled to the electronic processor and having instructions stored therein, wherein the said one or more electronic processor is configured to access the memory device and execute the instructions stored therein such that it is operable to:

determine the predicted path of the vehicle over terrain ahead of the vehicle, generate, for the predicted path of the vehicle, information indicative of the surface roughness of terrain along the predicted path, and output said output signal.

23. A vehicle speed control system comprising a terrain surface roughness detection system according to any preceding claim, the speed control system being configured to control vehicle speed at least in part in dependence at least in part on the output signal.

24. A vehicle speed control system according to claim 23 wherein the speed control system is configured to control vehicle speed by limiting vehicle speed to a maximum setspeed value, the maximum set-speed value being determined in dependence at least in part on the information indicative of surface roughness along the predicted path.

25. A speed control system according to claim 24, depending through any one of claims 1 to 14, configured to generate a maximum speed value based on the information indicative of terrain roughness along the predicted path and to cause vehicle speed not to exceed the maximum speed value along the predicted path.

26. A speed control system according to claim 24, depending through any one of claims 13 to 18, wherein the speed control system causes the vehicle speed not to exceed the maximum speed value along the predicted path.

27. A vehicle comprising a surface roughness detection system, or a vehicle speed control system according to any preceding claim.

28. A method of detecting terrain surface roughness ahead of the vehicle comprising: receiving, from terrain data capture means arranged to capture data in respect of terrain ahead of the vehicle by means of one or more sensors, terrain information indicative of the topography of an area extending ahead of the vehicle;

in dependence upon information in respect of a predicted path of the vehicle over said terrain extending ahead of the vehicle, generating, for the predicted path of the vehicle, terrain roughness information indicative of a roughness of the terrain along the predicted path, the method comprising providing an output signal in dependence on the terrain roughness information.

29. A method as claimed in claim 28 further comprising causing vehicle speed to be controlled in dependence at least in part on the terrain roughness.

30. A method as claimed in claim 29 wherein causing vehicle speed to be controlled in dependence at least in part on the terrain roughness information comprises controlling vehicle speed by limiting vehicle speed to a maximum set-speed value, the maximum setspeed value being determined in dependence at least in part on the information indicative of surface roughness along the predicted path.

31. A computer program product executable on a processor so as to implement the method of any one of claims 28 to 30.

32. A non-transitory computer readable medium carrying computer readable code which when executed causes a vehicle to carry out the method of any one of claims 28 to 30.

33. A controller arranged to implement the method of any one of claims 28 to 30.

34. A system, vehicle, method, carrier medium, computer program product, computer readable medium or controller substantially as hereinbefore described with reference to the accompanying drawings.

Intellectual

Property

Office

GB1611907.5

1-34

Application No: Claims searched: