Travel speed management

Abstract

A computer system (500) comprising processing circuitry (502) configured to manage travel speeds at a site (1) supporting operation of at least a first autonomous heavy-duty vehicle (2). The processing circuitry is further configured to determine slippage data indicative of wheel slippage between ground and at least a first wheel (3) of the vehicle traveling in a region of the site; obtain site-related data indicative of travel speed-affecting site conditions; derive, based on the site-related data, a wheel slippage reference value desired for the vehicle in said region; deduce, based on the wheel slippage reference value, a travel speed reference value desired for the vehicle in said region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value; and, when the determined wheel slippage deviates from the wheel slippage reference value, provide travel speed instruction data instructing the vehicle to in said region adapt travel speed to the travel speed reference value.

Description

Docket No.: [P2023-1571W001]1TRAVEL SPEED MANAGEMENTTECHNICAL FIELD

[0001] The disclosure relates generally to travel speed management. In particular aspects, the disclosure relates to managing travel speeds at a site supporting operation of at least a first autonomous heavy-duty vehicle. The disclosure can be applied to heavy-duty vehicles, such as dump trucks, haulers and construction equipment, among other vehicle types. Although the disclosure may be described with respect to a particular vehicle, the disclosure is not restricted to any particular vehicle.BACKGROUND

[0002] Operations at a construction site, such as for instance digging or blasting which may generate large amount of waste material e.g. dirt and / or rock that needs to be removed from the construction site and taken care of for instance at a landfill, crusher or other dump site, commonly involve heavy-duty vehicles such as dump trucks or other types of construction equipment and / or machines. Such operations may potentially be automated, whereupon the site may be referred to as an automated site, with one or more automated e.g. dump trucks operating the construction site - e.g. as a fleet - for instance in repeated cycles which commonly do not often change.

[0003] In order to reach effective - such as high and / or highest - site productivity, the e.g. dump trucks may be operated at a highest speed possible taking into consideration aspects such as safety aspects. Accordingly, during favourable conditions, vehicles, e.g. dump trucks, may be operated at relatively high speed(s), whereas should conditions alter and / or worsen the speed(s) of the vehicles may need to be decreased. That is, although the cycle(s) in which the e.g. dump trucks may operate commonly not often changes, the conditions of the ground surface - e.g. of predeterminable track(s) along which the e.g. dump trucks may travel - may be in continuous change. Such a change may for instance be brought about by worsened weather conditions such as rain or snow and / or by freezing temperatures which may lead to e.g. a muddy and / or icy ground surface and subsequently a potential need for decreased speed. Another - or additional - reason for such a change may be brought about by wear of the ground surface - for instance of track(s) along which the e.g. dump trucks repeatedly may be operated - and which similarly may necessitate decreased speed.Docket No.: [P2023-1571W001]2Yet another - or additional - implicating factor may be wear of tyres and / or potential load of the e.g. dump truck(s) affecting dump truck weight, which in a similar manner may implicate a potential need for decreased speed in order to e.g. keep a safety margin and / or to avoid ground wear. Still another factor that may affect travel speed may be ground inclinations at the site which have impact on slope and / or bank angle(s).

[0004] Operating at effective vehicle speeds - such as at higher or highest effective vehicle speeds - for high productivity at sites supporting operation of one or more autonomous heavy-duty vehicles, remains a challenge, and there is accordingly room for improvement.SUMMARY

[0005] According to a first aspect of the disclosure, there is provided a computer system comprising processing circuitry configured to manage travel speeds at a site supporting operation of at least a first autonomous heavy-duty vehicle.

[0006] The processing circuitry is further configured to determine slippage data indicative of wheel slippage between ground and at least a first wheel of the at least first autonomous heavy-duty vehicle traveling in a region of the site.

[0007] The processing circuitry is further configured to obtain site-related data indicative of travel speed-affecting site conditions.

[0008] Moreover, the processing circuitry is further configured to deduce, based on the wheel slippage reference value, a travel speed reference value desired for the at least first autonomous heavy-duty vehicle in said region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value.

[0009] Furthermore, the processing circuitry is further configured to provide, when the determined wheel slippage deviates from the wheel slippage reference value, travel speed instruction data instructing the at least first autonomous heavy-duty vehicle to, in the region, adapt travel speed to the travel speed reference value.

[0010] The first aspect of the disclosure may seek to manage - for instance continuously and / or iteratively - travel speed of one or more autonomous - and / or automated - heavy-duty vehicles e.g. dump trucks at a site supporting operation of autonomous heavy-duty vehicles, such that a high, maximum and / or optimal speed may be kept without a risk of theDocket No.: [P2023-1571W001]3 autonomous heavy-duty vehicle(s) going to an uncontrolled state. That is, in general, optimal and / or high site productivity may be achieved upon autonomous heavy-duty vehicles being operated at a speed, e.g., highest speed, at which friction and subsequently grip between tyre(s) and ground does not fall below a predeterminable level. That is, there may be a minimum tyre grip limit associated with each travel speed, below which limit(s) the tyre grip preferably should not fall in order to avoid a risk of losing control of the autonomous heavy- duty vehicle, potentially leading to an unwanted situation. Tyre grip is inevitably affected by slippery conditions, which - for instance along with vehicle weight conditions and / or ground slope / bank angle(s) - may implicate a need for altered - e.g. lowered - vehicle speed. With the introduced concept, the vehicle speed - at one or more sections e.g. tracks of the site - is controlled to lie at a high level deemed optimal, highest possible and / or preferred, taking into consideration wheel slippage affected by on-site circumstances - such as for instance ground surface conditions resulting e.g. from weather circumstances, freezing temperatures, moist and / or wear, and / or vehicle weight and / or vehicle tyre wear, and / or site ground inclination(s) having impact on slope / bank angle(s) - to thereby achieve high and / or improved site productivity. For instance, different regions of the site may have different travel speeds optimized.

[0011] Since the processing circuitry is configured to manage travel speeds at a site supporting operation of at least a first autonomous heavy-duty vehicle, a technical benefit may include that there for a site supporting operation of one or more autonomous heavy-duty vehicles - such as dump trucks, haulers and / or construction equipment - may be managed, set and / or controlled travel speed(s) of said vehicle(s). Moreover, said travel speeds may be managed for instance from on-board the at least first autonomous heavy-duty vehicle itself, and / or remotely such as from an optional site control tower e.g. comprising one or more servers and / or for instance from another vehicle e.g. autonomous heavy-duty vehicle operating the site, thus enabling for a flexible and / or efficient approach which potentially may apply to plural vehicles of a fleet operating the site.

[0012] Furthermore, since there is determined slippage data indicative of wheel slippage between ground and at least a first wheel of the at least first autonomous heavy-duty vehicle traveling in a region of the site, a further technical benefit may include that current amount of wheel slippage may be determined, obtained and / or derived - for instance continuously orDocket No.: [P2023-1571W001]4 intermittently - for an autonomous heavy-duty vehicle operating at the site, for instance along a section of a predeterminable track of the site.

[0013] Moreover, since there is obtained site-related data indicative of travel speedaffecting site conditions, a still further technical benefit may include that there is obtained, gathered and / or derived circumstances currently or recently valid at the site - and / or in the region - affecting at which speed an autonomous heavy-duty vehicle potentially may travel.

[0014] Furthermore, since there is derived based on the site-related data, a wheel slippage reference value desired for the at least first autonomous heavy-duty vehicle in said region, a yet further technical benefit may include that there is derived, deduced and / or determined - with the site-related data used as input - a fictive level of slippage between wheel and ground deemed optimal, beneficial and / or effective for the at least first autonomous heavy-duty vehicle to strive for and maintain, to achieve high site productivity, for instance while meeting safety aspects and / or avoiding ground surface wear.

[0015] Moreover, since there based on the wheel slippage reference value is deduced a travel speed reference value desired for the at least first autonomous heavy-duty vehicle in said region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value, a further technical benefit may include that there is deduced, calculated and / or determined - with the wheel slippage reference value as input - a desired vehicle speed level - and / or speed range - in the region, at which speed level the wheel slippage reference value may be maintained. In other words, the wheel slippage reference value is translated into a travel speed reference value, indicating a preferred vehicle speed relevant in view of the at least first autonomous heavy-duty vehicle.

[0016] Furthermore, since there is provided - when the determined wheel slippage deviates from the wheel slippage reference value - travel speed instruction data instructing the at least first autonomous heavy-duty vehicle to in said region adapt travel speed to the travel speed reference value, a yet further technical benefit may include that there - upon deviation e.g. to a predeterminable extent between the determined wheel slippage of the at least first autonomous heavy-duty vehicle and the desired wheel slippage - may be provided, generated and / or initiated instructions to the at least first autonomous heavy-duty vehicle to adapt - such as decrease or increase - its travel speed to align with, come close to and / or be based on the travel speed reference value. Thereby, the speed level - and / or speed range - corresponding to the wheel slippage reference value may be applied to the at least firstDocket No.: [P2023-1571W001]5 autonomous heavy-duty vehicle, and accordingly the wheel slippage desired for the at least first autonomous heavy-duty vehicle in the region reached and maintained.

[0017] Optionally in some examples, including in at least one preferred example, the site- related data comprises environmental data indicative of environmental driving conditions of the region, wherein the deriving of a wheel slippage reference value then is based at least on said environmental data. A technical benefit may include that the obtained circumstances currently or recently valid at the site - and / or in the region - affecting at which speed an autonomous heavy-duty vehicle potentially may travel, then comprises data revealing and / or reflecting ground surface-affecting environmental driving conditions relevant for said region, i.e. information on ground surface circumstances - such as for instance a muddy and / or icy ground surface - and / or information on ground surface-affecting circumstances such as weather conditions from which ground surface conditions - such as for instance a muddy and / or icy ground surface - may be derived. Since the wheel slippage reference value then is derived based at least on this environmental data, a further technical benefit may include that the wheel slippage reference value - i.e. the fictive level of slippage between wheel and ground deemed optimal, beneficial and / or effective for the autonomous heavy-duty vehicle to strive for and maintain to achieve high site productivity - is derived taking into consideration such ground surface circumstances and / or ground surface-affecting circumstances.Accordingly, the wheel slippage reference value may vary with varying environmental driving conditions of the region, for instance decrease with worsened ground surface conditions.

[0018] Optionally in some examples, including in at least one preferred example, the site- related data comprises vehicle-specific data indicative of weight and / or tyre wear of the at least first autonomous heavy-duty vehicle, wherein the deriving a wheel slippage reference value then is based at least on said vehicle-specific data. A technical benefit may include that the obtained circumstances currently or recently valid at the site - and / or in the region - affecting at which speed an autonomous heavy-duty vehicle potentially may travel, then comprises data revealing and / or reflecting status of the weight of the at least first autonomous heavy-duty vehicle e.g. including potential load and / or degree of tyre wear of the at least first autonomous heavy-duty vehicle. Since the wheel slippage reference value then is derived based at least on this vehicle-specific data, a further technical benefit may include that the wheel slippage reference value - i.e. the fictive level of slippage between wheel and groundDocket No.: [P2023-1571W001]6 deemed optimal, beneficial and / or effective for the autonomous heavy-duty vehicle to strive for and maintain to achieve high site productivity - is derived taking into consideration such status of vehicle weight and / or tyre wear. Accordingly, the wheel slippage reference value may vary with varying vehicle weight and potential load and / or further vary with varying degree of vehicle tyre wear, for instance decrease with increased vehicle weight and / or worsened tyre wear.

[0019] Optionally in some examples, including in at least one preferred example, the site- related data comprises inclination data indicative of slope and / or bank angles in the region, wherein the deriving a wheel slippage reference value then is based at least on said inclination data. A technical benefit may include that the obtained circumstances currently or recently valid at the site - and / or in the region - affecting at which speed an autonomous heavy-duty vehicle potentially may travel, then comprises data revealing and / or reflecting slope and / or banking angles in the area, for instance along a predeterminable track which the at least first autonomous heavy-duty vehicle may operate along. Since the wheel slippage reference value then is derived based at least on this inclination data, a further technical benefit may include that the wheel slippage reference value - i.e. the Active level of slippage between wheel and ground deemed optimal, beneficial and / or effective for the autonomous heavy-duty vehicle to strive for and maintain to achieve high site productivity - is derived taking into consideration such slope and / or bank angles. Accordingly, the wheel slippage reference value may vary with varying slope and / or bank angles, for instance decrease with increased slope and / or bank angles. Additionally or alternatively, the wheel slippage reference value may for instance increase with a slope angle indicating a downward slope, a situation which may provide the ability for coasting and / or freerolling and thus translating into that an increased travel speed - and subsequently wheel slippage reference value - may be feasible.

[0020] Optionally in some examples, including in at least one preferred example, the site- related data comprises ground wear data indicative of level of wear of the ground in said region, wherein the deriving a wheel slippage reference value then is based at least on said ground wear data. A technical benefit may include that the obtained circumstances currently or recently valid at the site - and / or in the region - affecting at which speed an autonomous heavy-duty vehicle potentially may travel, then comprises data revealing and / or reflecting status of wear of the ground and / or ground surface in the area - such as ruts resulting fromDocket No.: [P2023-1571W001]7 e.g. repeated passages of vehicle wheels - for instance along a predeterminable track which the at least first autonomous heavy-duty vehicle may operate along. Since the wheel slippage reference value then is derived based at least on this ground wear data, a further technical benefit may include that the wheel slippage reference value - i.e. the fictive level of slippage between wheel and ground deemed optimal, beneficial and / or effective for the autonomous heavy-duty vehicle to strive for and maintain to achieve high site productivity - is derived taking into consideration such status of wear of the ground. Accordingly, the wheel slippage reference value may vary with varying degree of ground wear, for instance decrease with increased wear of the ground.

[0021] Optionally in some examples, including in at least one preferred example, the processing circuitry is further configured to provide fleet-directed instruction data instructing at least a second heavy-duty vehicle to in the region adapt travel speed to the travel speed reference value. A technical benefit may include that there may be provided, generated and / or initiated instructions to heavy-duty vehicles other than the at least first autonomous heavy- duty vehicle - for instance a heavy-duty vehicle of similar characteristics as the at least first autonomous heavy-duty vehicle e.g. in terms of weight, potential load and / or degree of tyre wear - to adapt e.g. decrease or increase its travel speed to align with the travel speed reference value. Thereby, the speed level - and / or speed range - corresponding to the wheel slippage reference value may be applied also to heavy-duty vehicles other than the at least first autonomous heavy-duty vehicle, and accordingly the wheel slippage desired for the at least first vehicle in the region reached and maintained also for one or more other heavy-duty vehicles in the region.

[0022] According to a second aspect of the disclosure, there is provided an autonomous heavy-duty vehicle comprising and / or being controlled by the computer system according to the first aspect.

[0023] According to a third aspect of the disclosure, there is provided a computer- implemented method for managing travel speeds at a site supporting operation of at least a first autonomous heavy-duty vehicle.

[0024] The method comprises, by processing circuitry of a computer system, determining slippage data indicative of wheel slippage between ground and at least a first wheel of the at least first autonomous heavy-duty vehicle traveling in a region of the site.Docket No.: [P2023-1571W001]8

[0025] The method further comprises, by the processing circuitry, obtaining site-related data indicative of travel speed-affecting site conditions.

[0026] Furthermore, the method further comprises, by the processing circuitry, deriving based on the site-related data, a wheel slippage reference value desired for the at least first autonomous heavy-duty vehicle in the region.

[0027] Moreover, the method further comprises, by the processing circuitry, deducing based on the wheel slippage reference value, a travel speed reference value desired for the at least first autonomous heavy-duty vehicle in the region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value.

[0028] Furthermore, the method further comprises, by the processing circuitry, when the determined wheel slippage deviates from the wheel slippage reference value, providing travel speed instruction data instructing the at least first autonomous heavy-duty vehicle to in the region adapt travel speed to the travel speed reference value.

[0029] Optionally in some examples, including in at least one preferred example, the site- related data comprises environmental data indicative of environmental driving conditions of the region, wherein the deriving a wheel slippage reference value then is based at least on said environmental data.

[0030] Optionally in some examples, including in at least one preferred example, the site- related data comprises vehicle-specific data indicative of weight and / or tyre wear of the at least first autonomous heavy-duty vehicle, wherein the deriving a wheel slippage reference value then is based at least on said vehicle-specific data.

[0031] Optionally in some examples, including in at least one preferred example, the site- related data comprises inclination data indicative of slope and / or bank angles in the region, wherein the deriving a wheel slippage reference value then is based at least on said inclination data.

[0032] Optionally in some examples, including in at least one preferred example, the site- related data comprises ground wear data indicative of level of wear of the ground in the region, wherein the deriving a wheel slippage reference value then is based at least on said ground wear data.

[0033] Optionally in some examples, including in at least one preferred example, the method further comprises, by the processing circuitry, providing fleet-directed instructionDocket No.: [P2023-1571W001]9 data instructing at least a second heavy-duty vehicle to in the region adapt travel speed to the travel speed reference value.

[0034] The second and third aspects may correspond to any of the features, examples, and / or benefits of the first aspect and vice versa.

[0035] The disclosed aspects, examples (including any preferred examples), and / or accompanying claims may be suitably combined with each other as would be apparent to anyone of ordinary skill in the art. Additional features and advantages are disclosed in the following description, claims, and drawings, and in part will be readily apparent therefrom to those skilled in the art or recognized by practicing the disclosure as described herein.

[0036] There are also disclosed herein computer systems, control units, code modules, computer-implemented methods, computer readable media, and computer program products associated with the above discussed technical benefits.BRIEF DESCRIPTION OF THE DRAWINGS

[0001] Examples are described in more detail below with reference to the appended drawings.

[0002] FIG. 1 is an exemplary site supporting operation of at least a first autonomous heavy-duty vehicle according to an example.

[0003] FIG. 2 is an exemplary flow chart of a computer-implemented method for managing travel speeds at a site supporting operation of at least a first autonomous heavy- duty vehicle according to an example.

[0004] FIG. 3 is another view of FIG. 1, according to an example.

[0005] FIG. 4 is another exemplary flow chart of a computer-implemented method for managing travel speeds at a site supporting operation of at least a first autonomous heavy- duty vehicle according to an example.

[0006] FIG. 5 is a schematic diagram of an exemplary computer system for implementing examples disclosed herein, according to an example.Docket No.: [P2023-1571W001]10DETAILED DESCRIPTION

[0007] The detailed description set forth below provides information and examples of the disclosed technology with sufficient detail to enable those skilled in the art to practice the disclosure.

[0008] Examples herein may relate to improvements when it comes to operating at effective vehicle speeds - such as at higher or highest effective vehicle speeds - for high productivity at sites supporting operation of one or more autonomous heavy-duty vehicles. With the introduced concept, there may be managed travel speeds - for instance continuously and / or iteratively - of one or more autonomous - and / or automated - heavy-duty vehicles such as for instance dump trucks at a site supporting operation of autonomous heavy-duty vehicles, such that a maximum and / or optimal travel speed may be kept without a risk of the vehicle(s) going to an uncontrolled state.

[0009] Examples herein may relate to autonomous vehicles. Autonomous as used herein may mean that the respective vehicle is at least partly controlled without explicit control by a user, such that the vehicle may itself control steering and / or vehicle motion or the respective vehicle e.g., without a driver providing force to pedals or steering wheels of the vehicle.

[0010] FIG. 1 illustrates an exemplary site 1 supporting operation of at least a first autonomous heavy-duty vehicle 2 according to an example. The site 1 - which may be referred to as an automated site and according to an example to as a construction site - may be represented by any site situated above ground and / or underground - e.g. relating to mining - supporting operation of at least a first autonomous heavy-duty vehicle 2. The site 1 supporting operation of at least a first autonomous heavy-duty vehicle 2 may accordingly be referred to as a site where the at least first autonomous heavy-duty vehicle 2 operates and / or a site 1 arranged for the at least first autonomous heavy-duty vehicle to operate. The at least first autonomous heavy-duty vehicle 2 may potentially - but not necessarily - operate repeatedly along a predeterminable track at the site 1. Moreover, the at least first autonomous heavy-duty vehicle 2 may further be any suitable autonomous heavy-duty vehicle, such as for instance a dump truck, articulated dump truck, hauler, construction equipment, timber truck etc with autonomous capabilities. Furthermore, the at least first autonomous heavy-duty vehicle comprises in a known manner at least a first wheel 3, and may further comprise any arbitrary number of wheels feasible for the type of autonomous heavy-duty vehicle at hand. Moreover, the at least first autonomous vehicle 2 may comprise any number of - e.g.Docket No.: [P2023-1571W001]11 commonly known - on-board sensors 4, such as ground sensor(s) e.g. ground radar and / or any arbitrary sensor(s) supporting determination of actual vehicle speed, applied torque, acceleration in any direction e.g. inertial measurement unit(s) (IMU), tyre wear, weight of vehicle and potential load e.g. on-board weighing sensor(s) (OBW), determination of weather conditions e.g. rain and / or temperature sensor(s) etc.

[0011] Further depicted is an exemplifying at least second autonomous heavy-duty vehicle 5 - here of similar, same or corresponding characteristics as the at least first autonomous heavy-duty vehicle 2 - exemplified to operate the site 1.

[0012] Examples herein may be performed by a computer system 500 and / or a processing circuitry 502 therein, illustrated in Fig. 5 further on. The computer system 500 and / or the processing circuitry 502 therein may be comprised in the at least first autonomous heavy-duty vehicle 2 and / or at least partly remote from said vehicle 2 such as part of a server or cloud service, for instance at least partly situated at a control tower of the site 1, and / or at least partly comprised in an other heavy-duty vehicle operating and / or having operated at the site 1. In some examples, the computer system 500 and / or the processing circuitry 502 may be or may comprise an Electronic Control Unit (ECU).

[0013] In some examples, the computer system 500 and / or the processing circuitry 502 therein may be communicatively coupled with, and / or capable of controlling any suitable entity of the at least first autonomous heavy-duty vehicle 2. For example, the computer system 500 and / or the processing circuitry 502 may be able to obtain information about wheel slippage between ground and the at least first wheel 3 of the at least first autonomous heavy-duty vehicle 2 as said vehicle 2 is traveling in a region of the site 1. As another example, the computer system 500 and / or the processing circuitry 502 may be able to manage travel speed of the at least first autonomous heavy-duty vehicle 2.

[0014] FIG. 2 is an exemplary flow chart of a computer-implemented method - which may be continuously and / or iteratively repeated - for managing travel speeds at the site 1 supporting operation of the at least a first autonomous heavy-duty vehicle 2 according to an example. Dashed boxes in FIG. 2 may indicate optional actions. The below actions may be taken in any suitable order. The actions described below may be performed by the computer system 500 and / or the processing circuitry 502 therein.

[0015] Action 201Docket No.: [P2023-1571W001]12

[0016] The method comprises determining slippage data indicative of wheel slippage between ground and the at least first wheel 3 of the at least first autonomous heavy-duty vehicle 2 traveling in a region of the site 1. The wheel slippage may be and / or have been determined and / or obtained - e.g. continuously and / or intermittently - in any feasible manner e.g. as known in the art, such as with support from the on-board sensors 4.

[0017] For instance, wheel slippage may be determined from measuring a spinning of the at least first wheels 3 and calculating a speed of the wheel periphery and further measuring an actual vehicle speed e.g. with support from an on-board ground radar, and identify the difference therebetween. In other words, the slippage data may comprise information of a longitudinal slip of the at least first wheel 3, but according to an example, the slippage data may additionally or alternatively comprise lateral slip information as well.

[0018] According to an example, acceleration - in longitudinal and / or lateral direction - may be monitored and / or measured, e.g. with support from one or more inertial measurement units (IMUs). Moreover, additionally or alternatively, torque applied by the at least first autonomous heavy-duty vehicle 2 may be monitored and / or measured, e.g. with support from one or more on-board sensors.

[0019] The referred to region, on the other hand, may be represented by any arbitrarily sized zone or portion of the site 1, of any feasible dimensions, ranging from a mere portion of the site 1 to its entirety, and / or potentially a section or an entirety of a predeterminable track in the zone 1 along which the at least first autonomous heavy-duty vehicle 2 may operate.

[0020] Action 202

[0021] The method further comprises obtaining site-related data indicative of travel speed-affecting site conditions. The speed-affecting site conditions may be obtained in any arbitrary manner from any feasible entity holding and / or being capable of determining - e.g. with support from one or more sensors - such data. Said speed-affecting site conditions may accordingly for instance be obtained with support from on-board sensors 4 of the at least first autonomous heavy-duty vehicle 2, and / or sensors of another entity e.g. vehicle currently and / or prior present in - or in vicinity of - the region or site 1, and / or for instance be obtained from a potential site control tower and / or cloud e.g. comprising one or more servers, and / or obtained from a remote entity such as a service provider.

[0022] According to an example, the site-related data may comprise environmental data indicative of environmental driving conditions of the region. Said environmental drivingDocket No.: [P2023-1571W001]13 conditions for the region may for instance be and / or have been obtained with support from on-board sensors 4 of the at least first autonomous heavy-duty vehicle 2 such as ground radar(s) and / or sensor(s) capable of sensing weather conditions e.g. rain and / or temperature sensor(s) commonly known in the art, and / or corresponding sensors of another entity e.g. vehicle currently and / or relatively recently present in - or in vicinity of - the region or site 1, and / or obtained for instance from the potential site control tower and / or cloud, and / or a remote entity such as a weather forecast provider.

[0023] According to an example, the site-related data may additionally or alternatively comprise vehicle-specific data indicative of weight and / or tyre wear of the at least first autonomous heavy-duty vehicle. Said weight and / or tyre wear of the at least first autonomous heavy-duty vehicle 2 may for instance be and / or have been obtained with support from onboard sensors 4 of the at least first autonomous heavy-duty vehicle 2 such as sensor(s) capable of sensing weight of the vehicle 2 and / or potential load thereof and / or capable of sensing degree of wear of the at least first tyre 3 of the at least first autonomous heavy-duty vehicle 2, and / or for instance obtained from a remote entity such as the potential site control tower and / or cloud.

[0024] According to an example, the site-related data may additionally or alternatively comprise site inclination data indicative of slope and / or bank angles in the region. Said slope and / or bank angles in the region may for instance be and / or have been obtained with support from on-board sensors 4 of the at least first autonomous heavy-duty vehicle 2 such as ground radar(s) and / or sensor(s) capable of sensing slope and / or bank angles in the region, and / or corresponding sensors of another entity e.g. vehicle prior and / or recently present in - or in vicinity of - the region or site 1, and / or obtained for instance from the potential site control tower and / or cloud, and / or from map data e.g. a high definition (HD) map covering the site 1.

[0025] According to an example, the site-related data may additionally or alternatively comprise ground wear data indicative of level of wear of the ground in the region. Said level of wear of the ground in the region may for instance be and / or have been obtained with support from on-board sensors 4 of the at least first autonomous heavy-duty vehicle 2 such as ground radar(s) and / or sensor(s) capable of sensing level of wear of the ground and / or ground surface, and / or corresponding sensors of another entity e.g. vehicle prior and / or recently present in - or in vicinity of - the region or site 1, and / or obtained for instance from the potential site control tower and / or cloud.Docket No.: [P2023-1571W001]14

[0026] Action 203

[0027] The method further comprises deriving based on the site-related data, a wheel slippage reference value desired for the at least first autonomous heavy-duty vehicle in said region. Optionally, the wheel slippage reference value may be based at least on the optional environmental data, the optional vehicle-specific data, the optional inclination data, and / or the optional ground wear data. The wheel slippage reference value - which represents a fictive level of slippage between wheel and ground deemed optimal, beneficial and / or effective for the at least first autonomous heavy-duty vehicle 2 to strive for and maintain, to achieve high site productivity, for instance while meeting safety aspects and / or avoiding ground surface wear - may be and / or have been derived and / or deduced in any feasible manner taking consideration to the site-related data, for instance ground surface conditions, potential vehicle load, degree of tyre wear, slope / bank angles in the region, and / or degree of ground wear etc.

[0028] According to an example, monitored and / or measured acceleration of the at least first autonomous heavy-duty vehicle 2 - in lateral and / or longitudinal direction - may additionally serve as input to the wheel slippage reference value.

[0029] For instance, monitored and / or measured torque applied by the at least first autonomous heavy-duty vehicle 2 to the at least first wheel 3, may be used to calculate a total longitudinal force delivered by each at least first wheel 3, which in turn may be converted to an estimation of the available tyre-road friction, for instance by dividing by the normal force e.g. derived from OBW sensor(s). Such a friction estimate may subsequently be used as input in determining a maximum achievable acceleration - longitudinal and / or lateral - preferably not to be exceeded, and which thus may be taken into consideration in deriving the wheel slippage reference value, such as in combination with travel speed-affecting site conditions.

[0030] According to an example, the wheel slippage reference value may be derived by combining input from plural autonomous heavy-duty vehicles and / or entities, and / or sensors thereof.

[0031] Moreover, the wheel slippage reference vale may be represented by a single value, or alternatively a limited range of values to indicate an interval.

[0032] Action 204

[0033] The method further comprises deducing based on the wheel slippage reference value, a travel speed reference value desired for the at least first autonomous heavy-dutyDocket No.: [P2023-1571W001]15 vehicle in the region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value. The travel speed reference value - which represents a desired vehicle speed level and / or speed range in said region, at which speed level the wheel slippage reference value may be maintained - may be deduced from the wheel slippage reference value in any feasible manner. For instance, the travel speed reference value may be deduced taking into consideration the wheel slippage reference value, subsequently taking consideration to the site-related data, for instance ground surface conditions, potential vehicle load, degree of tyre wear, slope / bank angles in the region, and / or degree of ground wear etc., while at the same time taking consideration to preferably not exceeding determined maximum achievable accelerations(s) in longitudinal and / or lateral direction.

[0034] According to an example, maximum achievable longitudinal and / or lateral acceleration - e.g. determined from friction estimates converted from total longitudinal force delivered by each at least first wheel 3 calculated from monitored and / or measured torque applied by the at least first autonomous heavy-duty vehicle 2 - may define a maximum speed, e.g. in comers where a lateral acceleration limit can be converted to a maximum speed and / or similarly a longitudinal acceleration limit can be converted to a maximum speed e.g. maximum speed profile of time / di stance, which maximum speed - in combination with taking into consideration the travel speed-affecting site conditions - then may form basis for defining the travel speed reference value.

[0035] Action 205

[0036] The method further comprises, when the determined wheel slippage deviates from the wheel slippage reference value, providing travel speed instruction data instructing the at least first autonomous heavy-duty vehicle to in the region adapt travel speed to the travel speed reference value. The travel speed instruction data - which for instance may be provided to a speed-controlling arrangement of the at least first autonomous heavy-duty vehicle 2 e.g. from and / or via the at least first autonomous heavy-duty vehicle 2 itself and / or a potential site control tower or cloud - may comprise the deduced travel speed reference value, to which a current travel speed of said vehicle 2 then subsequently preferably may be adapted. Thereby, the speed level - and / or speed range - corresponding to the wheel slippage reference value may be applied to the at least first autonomous heavy-duty vehicle, and accordingly the wheel slippage desired for the at least first autonomous heavy-duty vehicle in said region reached and maintained.Docket No.: [P2023-1571W001]16

[0037] Action 206

[0038] The method may further optionally comprise providing fleet-directed instruction data instructing at least a second heavy-duty vehicle 5 to, in the region, adapt travel speed to the travel speed reference value. The travel speed instruction data - which for instance may be provided to a speed-controlling arrangement of the at least second heavy-duty vehicle 5 e.g. from and / or via the at least first autonomous heavy-duty vehicle 2 and / or a potential site control tower or cloud - may comprise the deduced travel speed reference value, to which a current travel speed of said vehicle 5 then subsequently preferably may be adapted.

[0039] FIG. 3 is another view of FIG. 1, according to an example. The computer system. 500 comprising the processing circuitry 502 is configured to manage travel speeds at a site 1 supporting operation of at least a first autonomous heavy-duty vehicle 2. The processing circuitry is further configured to determine slippage data indicative of wheel slippage between ground and at least a first wheel 3 of the at least first autonomous heavy-duty vehicle 2 traveling in a region of the site 1. Moreover, the processing circuitry is configured to obtain site-related data indicative of travel speed-affecting site conditions. Furthermore, the processing circuitry is further configured to derive based on the site-related data, a wheel slippage reference value desired for the at least first autonomous heavy-duty vehicle 2 in the region. Moreover, the processing circuitry is configured to deduce based on the wheel slippage reference value, a travel speed reference value desired for the at least first autonomous heavy-duty vehicle 2 in said region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value. Furthermore, the processing circuitry is further configured to when the determined wheel slippage deviates from the wheel slippage reference value, provide travel speed instruction data instructing the at least first autonomous heavy-duty vehicle 2 to in the region adapt travel speed to the travel speed reference value.

[0040] FIG. 4 is a flow chart of a method for managing travel speeds at a site 1 supporting operation of at least a first autonomous heavy-duty vehicle 2.

[0041] . The method comprises the following actions which may be combined with any of the above-mentioned actions or examples in any suitable manner.

[0042] Action 401

[0043] The method comprises, by the processing circuitry 502 of the computer system 500, determining slippage data indicative of wheel slippage between ground and at least aDocket No.: [P2023-1571W001]17 first wheel 3 of the at least first autonomous heavy-duty vehicle 2 traveling in a region of the site 1.

[0044] Action 402

[0045] The method further comprises, by the processing circuitry 502, obtaining site- related data indicative of travel speed-affecting site conditions.

[0046] Action 403

[0047] Moreover, the method further comprises, by the processing circuitry 502, deriving based on the site-related data, a wheel slippage reference value desired for the at least first autonomous heavy-duty vehicle in the region.

[0048] Action 404

[0049] The method further comprises, by the processing circuitry 502, deducing based on the wheel slippage reference value, a travel speed reference value desired for the at least first autonomous heavy-duty vehicle 2 in said region, which travel speed reference value reflects a travel speed corresponding to the wheel slippage reference value.

[0050] Action 405

[0051] Moreover, the method further comprises, by the processing circuitry 502, when the determined wheel slippage deviates from the wheel slippage reference value, providing travel speed instruction data instructing the at least first autonomous heavy-duty vehicle to in said region adapt travel speed to the travel speed reference value.

[0052] FIG. 5 is a schematic diagram of a computer system 500 for implementing examples disclosed herein. The computer system 500 is adapted to execute instructions from a computer-readable medium to perform these and / or any of the functions or processing described herein. The computer system 500 may be connected (e.g., networked) to other machines in a LAN (Local Area Network), LIN (Local Interconnect Network), automotive network communication protocol (e.g., FlexRay), an intranet, an extranet, or the Internet. While only a single device is illustrated, the computer system 500 may include any collection of devices that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. Accordingly, any reference in the disclosure and / or claims to a computer system, computing system, computer device, computing device, control system, control unit, electronic control unit (ECU), processor device, processing circuitry, etc., includes reference to one or more such devices to individually or jointly execute a set (or multiple sets) of instructions to perform any one orDocket No.: [P2023-1571W001]18 more of the methodologies discussed herein. For example, control system may include a single control unit or a plurality of control units connected or otherwise communicatively coupled to each other, such that any performed function may be distributed between the control units as desired. Further, such devices may communicate with each other or other devices by various system architectures, such as directly or via a Controller Area Network (CAN) bus, etc.

[0053] The computer system 500 may comprise at least one computing device or electronic device capable of including firmware, hardware, and / or executing software instructions to implement the functionality described herein. The computer system 500 may include processing circuitry 502 (e.g., processing circuitry including one or more processor devices or control units), a memory 504, and a system bus 506. The computer system 500 may include at least one computing device having the processing circuitry 502. The system bus 506 provides an interface for system components including, but not limited to, the memory 504 and the processing circuitry 502. The processing circuitry 502 may include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory 504. The processing circuitry 502 may, for example, include a general-purpose processor, an application specific processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a circuit containing processing components, a group of distributed processing components, a group of distributed computers configured for processing, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processing circuitry 502 may further include computer executable code that controls operation of the programmable device.

[0054] The system bus 506 may be any of several types of bus structures that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and / or a local bus using any of a variety of bus architectures. The memory 504 may be one or more devices for storing data and / or computer code for completing or facilitating methods described herein. The memory 504 may include database components, object code components, script components, or other types of information structure for supporting the various activities herein. Any distributed or local memory device may be utilized with the systems and methods of this description. The memory 504 may be communicably connectedDocket No.: [P2023-1571W001]19 to the processing circuitry 502 (e.g., via a circuit or any other wired, wireless, or network connection) and may include computer code for executing one or more processes described herein. The memory 504 may include non-volatile memory 508 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.), and volatile memory 510 (e.g., randomaccess memory (RAM)), or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a computer or other machine with processing circuitry 502. A basic input / output system (BIOS) 512 may be stored in the non-volatile memory 508 and can include the basic routines that help to transfer information between elements within the computer system 500.

[0055] The computer system 500 may further include or be coupled to a non-transitory computer-readable storage medium such as the storage device 514, which may comprise, for example, an internal or external hard disk drive (HDD) (e.g., enhanced integrated drive electronics (EIDE) or serial advanced technology attachment (SATA)), HDD (e.g., EIDE or SATA) for storage, flash memory, or the like. The storage device 514 and other drives associated with computer-readable media and computer-usable media may provide nonvolatile storage of data, data structures, computer-executable instructions, and the like.

[0056] Computer-code which is hard or soft coded may be provided in the form of one or more modules. The module(s) can be implemented as software and / or hard-coded in circuitry to implement the functionality described herein in whole or in part. The modules may be stored in the storage device 514 and / or in the volatile memory 510, which may include an operating system 516 and / or one or more program modules 518. All or a portion of the examples disclosed herein may be implemented as a computer program 520 stored on a transitory or non-transitory computer-usable or computer-readable storage medium (e.g., single medium or multiple media), such as the storage device 514, which includes complex programming instructions (e.g., complex computer-readable program code) to cause the processing circuitry 502 to carry out actions described herein. Thus, the computer-readable program code of the computer program 520 can comprise software instructions for implementing the functionality of the examples described herein when executed by the processing circuitry 502. In some examples, the storage device 514 may be a computer program product (e.g., readable storage medium) storing the computer program 520 thereon,Docket No.: [P2023-1571W001]20 where at least a portion of a computer program 520 may be loadable (e.g., into a processor) for implementing the functionality of the examples described herein when executed by the processing circuitry 502. The processing circuitry 502 may serve as a controller or control system for the computer system 500 that is to implement the functionality described herein.

[0057] The computer system 500 may include an input device interface 522 configured to receive input and selections to be communicated to the computer system 500 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, etc. Such input devices may be connected to the processing circuitry 502 through the input device interface 522 coupled to the system bus 506 but can be connected through other interfaces, such as a parallel port, an Institute of Electrical and Electronic Engineers (IEEE) 1394 serial port, a Universal Serial Bus (USB) port, an IR interface, and the like. The computer system 500 may include an output device interface 524 configured to forward output, such as to a display, a video display unit (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 500 may include a communications interface 526 suitable for communicating with a network as appropriate or desired.

[0058] The operational actions described in any of the exemplary aspects herein are described to provide examples and discussion. The actions may be performed by hardware components, may be embodied in machine-executable instructions to cause a processor to perform the actions, or may be performed by a combination of hardware and software. Although a specific order of method actions may be shown or described, the order of the actions may differ. In addition, two or more actions may be performed concurrently or with partial concurrence.

[0059] Below follow a list of Examples 1-20 which may be combined with any one or more out of the above examples or actions, in any suitable manner.Example 1. A computer system (500) comprising processing circuitry (502) configured to manage travel speeds at a site (1) supporting operation of at least a first autonomous heavy-duty vehicle (2), wherein the processing circuitry (502) is further configured to:- determine slippage data indicative of wheel slippage between ground and at least a first wheel (3) of said at least first autonomous heavy-duty vehicle (2) traveling in a region of said site (1);Docket No.: [P2023-1571W001]21- obtain site-related data indicative of travel speed-affecting site conditions;- derive based on said site-related data, a wheel slippage reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region;- deduce based on said wheel slippage reference value, a travel speed reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region, said travel speed reference value reflecting a travel speed corresponding to said wheel slippage reference value; and- when the determined wheel slippage deviates from said wheel slippage reference value, provide travel speed instruction data instructing said at least first autonomous heavy-duty vehicle (2) to, in said region, adapt travel speed to said travel speed reference value.Example 2. The computer system (500) of Example 1, wherein said site-related data comprises environmental data indicative of environmental driving conditions of said region, wherein said deriving a wheel slippage reference value then is based at least on said environmental data.Example 3. The computer system (500) of Example 1 or 2, wherein said site- related data comprises vehicle-specific data indicative of weight and / or tyre wear of said at least first autonomous heavy-duty vehicle (2), wherein said deriving a wheel slippage reference value then is based at least on said vehicle-specific data.Example 4. The computer system (500) of any one of Examples 1-3, wherein said site-related data comprises inclination data indicative of slope and / or bank angles in said region, wherein said deriving a wheel slippage reference value then is based at least on said inclination data.Docket No.: [P2023-1571W001]22Example 5. The computer system (500) of any one of Examples 1-4, wherein said site-related data comprises ground wear data indicative of level of wear of the ground in said region, wherein said deriving a wheel slippage reference value then is based at least on said ground wear data.Example 6. The computer system (500) of any of Examples 1-5, wherein said processing circuitry (502) is further configured to:- provide fleet-directed instruction data instructing at least a second heavy- duty vehicle (5) to, in said region, adapt travel speed to said travel speed reference value.Example 7. An autonomous heavy-duty vehicle (2) comprising and / or being controlled by the computer system (500) of any of Examples 1-6.Example 8. A computer-implemented method for managing travel speeds at a site (1) supporting operation of at least a first autonomous heavy-duty vehicle (2), comprising:- by processing circuitry (502) of a computer system (500), determining (201, 401) slippage data indicative of wheel slippage between ground and at least a first wheel (3) of said at least first autonomous heavy-duty vehicle (1) traveling in a region of said site (1);- by the processing circuitry (502), obtaining (202, 402) site-related data indicative of travel speed-affecting site conditions;- by the processing circuitry (502), deriving (203, 403) based on said site- related data, a wheel slippage reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region;- by the processing circuitry (502), deducing (204, 404) based on said wheel slippage reference value, a travel speed reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region, said travel speed reference value reflecting a travel speed corresponding to said wheel slippage reference value; andDocket No.: [P2023-1571W001]23- by the processing circuitry (502), when the determined wheel slippage deviates from said wheel slippage reference value, providing (205, 405) travel speed instruction data instructing said at least first autonomous heavy-duty vehicle (2) to in said region adapt travel speed to said travel speed reference value.Example 9. The method of Example 8, wherein said site-related data comprises environmental data indicative of environmental driving conditions of said region, wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said environmental data.Example 10. The method of Examples 8 or 9, wherein said site-related data comprises vehicle-specific data indicative of weight and / or tyre wear of said at least first autonomous heavy-duty vehicle (2), wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said vehicle-specific data.Example 11. The method of any one of Examples 8-10, wherein said site-related data comprises inclination data indicative of slope and / or bank angles in said region, wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said inclination data.Example 12. The method of any one of Examples 8-11, wherein said site-related data comprises ground wear data indicative of level of wear of the ground in said region, wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said ground wear data.Example 13. The method of any of Examples 8-12, further comprising:- by the processing circuitry (502), providing (206) fleet-directed instruction data instructing at least a second heavy-duty vehicle (5) to in said region adapt travel speed to said travel speed reference value.Docket No.: [P2023-1571W001]24Example 14. A computer program product comprising program code for performing, when executed by the processing circuitry (502), the method of any of Examples 8-13.Example 15. A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry (502), cause the processing circuitry (502) to perform the method of any of Examples 8-13.Example 16. The autonomous heavy-duty vehicle (2) of Example 7, wherein said at least first autonomous heavy-duty vehicle comprises a dump truck.Example 17. The computer system (500) of any one of Examples 1-6, wherein said determining slippage data comprises determining said slippage data with support from a ground radar.Example 18. The computer system (500) of any one of Examples 1-6, 17, wherein said obtaining site-related data comprises obtaining said site-related data with support from a ground radar.Example 19. The method of any one of Examples 8-13, wherein said determining slippage data comprises determining said slippage data with support from a ground radar.Example 20. The method of any one of Examples 8-13, 19, wherein said obtaining site-related data comprises obtaining said site-related data with support from ground radar.

[0060] The terminology used herein is for the purpose of describing particular aspects only and is not intended to be limiting of the disclosure. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items. It will be further understood that the termsDocket No.: [P2023-1571W001]25"comprises," "comprising," "includes," and / or "including" when used herein specify the presence of stated features, integers, actions, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, actions, steps, operations, elements, components, and / or groups thereof.

[0061] It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element without departing from the scope of the present disclosure.

[0062] Relative terms such as "below" or "above" or "upper" or "lower" or "horizontal" or "vertical" may be used herein to describe a relationship of one element to another element as illustrated in the Figures. It will be understood that these terms and those discussed above are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present.

[0063] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0064] It is to be understood that the present disclosure is not limited to the aspects described above and illustrated in the drawings; rather, the skilled person will recognize that many changes and modifications may be made within the scope of the present disclosure and appended claims. In the drawings and specification, there have been disclosed aspects for purposes of illustration only and not for purposes of limitation, the scope of the disclosure being set forth in the following claims.

Claims

Docket No.: [P2023-1571W001]26ClaimsWhat is claimed is:

1. A computer system (500) comprising processing circuitry (502) configured to manage travel speeds at a site (1) supporting operation of at least a first autonomous heavy-duty vehicle (2), wherein the processing circuitry (502) is further configured to:- determine slippage data indicative of wheel slippage between ground and at least a first wheel (3) of said at least first autonomous heavy-duty vehicle (2) traveling in a region of said site (1);- obtain site-related data indicative of travel speed-affecting site conditions;- derive based on said site-related data, a wheel slippage reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region;- deduce based on said wheel slippage reference value, a travel speed reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region, said travel speed reference value reflecting a travel speed corresponding to said wheel slippage reference value; and- when the determined wheel slippage deviates from said wheel slippage reference value, provide travel speed instruction data instructing said at least first autonomous heavy-duty vehicle (2) to, in said region, adapt travel speed to said travel speed reference value.

2. The computer system (500) of claim 1, wherein said site-related data comprises environmental data indicative of environmental driving conditions of said region, wherein said deriving a wheel slippage reference value then is based at least on said environmental data.

3. The computer system (500) of claim 1 or 2, wherein said site-related data comprises vehicle-specific data indicative of weight and / or tyre wear of said at least first autonomous heavy-duty vehicle (2), wherein said deriving a wheel slippage reference value then is based at least on said vehicle-specific data.Docket No.: [P2023-1571W001]274. The computer system (500) of any one of claims 1-3, wherein said site-related data comprises inclination data indicative of slope and / or bank angles in said region, wherein said deriving a wheel slippage reference value then is based at least on said inclination data.

5. The computer system (500) of any one of claims 1-4, wherein said site-related data comprises ground wear data indicative of level of wear of the ground in said region, wherein said deriving a wheel slippage reference value then is based at least on said ground wear data.

6. The computer system (500) of any of claims 1-5, wherein said processing circuitry (502) is further configured to:- provide fleet-directed instruction data instructing at least a second heavy- duty vehicle (5) to, in said region, adapt travel speed to said travel speed reference value.

7. An autonomous heavy-duty vehicle (2) comprising and / or being controlled by the computer system (500) of any of claims 1-6.

8. A computer-implemented method for managing travel speeds at a site (1) supporting operation of at least a first autonomous heavy-duty vehicle (2), comprising:- by processing circuitry (502) of a computer system (500), determining (201, 401) slippage data indicative of wheel slippage between ground and at least a first wheel (3) of said at least first autonomous heavy-duty vehicle (2) traveling in a region of said site (1);- by the processing circuitry (502), obtaining (202, 402) site-related data indicative of travel speed-affecting site conditions;Docket No.: [P2023-1571W001]28- by the processing circuitry (502), deriving (203, 403) based on said site- related data, a wheel slippage reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region;- by the processing circuitry (502), deducing (204, 404) based on said wheel slippage reference value, a travel speed reference value desired for said at least first autonomous heavy-duty vehicle (2) in said region, said travel speed reference value reflecting a travel speed corresponding to said wheel slippage reference value; and- by the processing circuitry (502), when the determined wheel slippage deviates from said wheel slippage reference value, providing (205, 405) travel speed instruction data instructing said at least first autonomous heavy-duty vehicle (2) to in said region adapt travel speed to said travel speed reference value.

9. The method of claim 8, wherein said site-related data comprises environmental data indicative of environmental driving conditions of said region, wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said environmental data.

10. The method of claim 8 or 9, wherein said site-related data comprises vehiclespecific data indicative of weight and / or tyre wear of said at least first autonomous heavy-duty vehicle (2), wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said vehicle-specific data.

11. The method of any one of claims 8-10, wherein said site-related data comprises inclination data indicative of slope and / or bank angles in said region, wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said inclination data.

12. The method of any one of claims 8-11, wherein said site-related data comprises ground wear data indicative of level of wear of the ground in said region,Docket No.: [P2023-1571W001]29 wherein said deriving (203, 403) a wheel slippage reference value then is based at least on said ground wear data.

13. The method of any of claims 8-12, further comprising: - by the processing circuitry (502), providing (206) fleet-directed instruction data instructing at least a second heavy-duty vehicle (5) to in said region adapt travel speed to said travel speed reference value.

14. A computer program product comprising program code for performing, when executed by the processing circuitry (502), the method of any of claims 8-13.

15. A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry (502), cause the processing circuitry (502) to perform the method of any of claims 8-13.

Images