System and method for controlling one or more vehicles

Abstract

The present disclosure relates to a computer system (100) for controlling an autonomous vehicle operation of an autonomous vehicle (10) within a confined geographical area (200), the computer system comprising processing circuitry (102) configured to be in communication with an absolute positioning system and a relative positioning system, the processing circuitry further being configured to: receive data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions; determine to use the relative positioning system in response to a detected low confidence in absolute positioning data from the absolute positioning system; use the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and adapt the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

Description

SYSTEM AND METHOD FOR CONTROLLING ONE OR MORE VEHICLESTECHNICAL FIELD

[0001] The disclosure relates generally to the field of controlling one or more vehicles operating in a confined geographical area, such as one or more autonomous heavy-duty vehicles operating in a confined area. In particular aspects, the disclosure relates to a computer system, a vehicle, and methods for controlling one or more vehicles operating in a confined geographical area. The disclosure can be applied to heavy-duty vehicles, such as trucks, buses, and construction equipment, among other vehicle types. In particular, the disclosure can be applied to autonomous vehicles, such as unmanned autonomous vehicles operating in a confined geographical area. Although the disclosure may be described with respect to a particular vehicle, the disclosure is not restricted to any particular vehicle.BACKGROUND

[0002] Autonomous vehicles have witnessed widespread adoption in various industries, transforming efficiency and safety in tasks such as material transport and handling in confined geographical areas, e.g., transportation of bulk material from a loading zone to an unloading zone. However, challenges persist when deploying autonomous vehicles during changing environmental conditions, as well as in hilly terrains in the confined geographical area.

[0003] By way of example, hilly terrains introduce complexities in navigation, requiring vehicles to adapt to varying inclines and declines while maintaining operational performance. In confined spaces, such as loading areas, the maneuverability of autonomous vehicles may also become a critical factor for avoiding collisions and ensuring the safety of both equipment and personnel. Moreover, the maneuverability of autonomous vehicles in confined spaces may occasionally experience challenges in positioning determination due to various disturbances, such as disturbances in the signal processing of the positioning data.

[0004] Thus, there is a continuing need for further improvements in the vehicle control and motion management of heavy-duty vehicles, such as autonomous vehicles operating in a confined geographical area.SUMMARY

[0005] According to a first aspect of the disclosure, there is provided a computer system for controlling an autonomous vehicle operation of an autonomous vehicle within a confined geographical area, the computer system comprising processing circuitry configured to be in communication with an absolute positioning system and a relative positioning system, the processingcircuitry further being configured to: receive data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions; determine to use the relative positioning system in response to a detected low confidence in absolute positioning data from the absolute positioning system; use the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and adapt the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

[0006] The disclosure is at least partly based on the realization that deploying and controlling autonomous vehicles, such as autonomous electric vehicles, in a confined geographical area may still be challenging in terms of providing a reliable and safe operation of the vehicle. By way of example, autonomous vehicle operations can be compromised in environments where absolute positioning data (e.g., from GNSS) is unreliable, such as in areas with obstructions that disrupt signal reception. Examples of such areas include tunnels that fully block the signal, tall walls or buildings that can lead to signal reflections causing inaccurate positioning. Autonomous vehicle operations can also be compromised in environments where absolute positioning relies on lidar technology combined with a pre-recorded map. Complications arise particularly when data loss occurs due to sensor coverage issues or changes in environmental features. Sensor coverage can be temporarily obstructed by elements such as dust or rain.

[0007] The first aspect of the disclosure may seek to enhance the resilience of autonomous vehicle operations within environments where traditional GPS-based positioning systems would fail. More specifically, the disclosure aims to maintain a high level of operational safety by enabling the proposed computer system, even in the absence of reliable absolute positioning data, to control the vehicle to continue navigating safely within the confined geographical area by utilizing data from the relative positioning system. Moreover, the proposed computer system is configured to receive data indicative of one or more geographical zones within the confined area, each one being defined by specific operational restricting conditions. When low confidence in the absolute positioning data is detected, the computer system determines to use, or switch to, the relative positioning system. The computer system then estimates the vehicle position relative to the any of these zones and adapts the vehicle operation(s) accordingly to comply with the zone-specific conditions such as speed limits. Thus, the computer system allows the vehicle to maintain adherence to safety protocols and operational restrictions dynamically, even in challenging navigation situations.

[0008] A technical benefit may include enhanced reliability and safety of autonomous vehicle operations in confined areas and across diverse environmental conditions where traditional GPS data may be intermittent or unavailable. Moreover, the proposed computer system may not only allow formitigating the risk associated with signal loss but also increasing the likelihood of compliance with operational constraints, thereby ensuring safer navigation and adherence to predefined geographical restrictions within the confined area.

[0009] Furthermore, an additional technical advantage is the ability to maintain productivity while enhancing safety, which is achieved through the configuration of the computer system. This configuration increases the likelihood that, in the event of a system failure, the vehicle(s) will continue to operate and execute their designated missions without compromising safety.

[0010] To this end, the proposed computer system allows for improving the control of an autonomous vehicle in a confined geographical area containing one or more geographical zones having one or more operational restricting conditions. Moreover, the proposed computer system allows for a more sustainable and cost-effective utilization of vehicle fleets in confined geographical areas.

[0011] Optionally, in some examples, including in at least one preferred example, the processing circuitry may further be configured to determine proximity to a nearest geographical zone of a group of geographical zones based on the last-received absolute positioning data from the absolute positioning system, predict entrance of the nearest geographical zone, and adapt the operation of the vehicle based on the predicted vehicle entrance of the nearest geographical zone. A technical benefit may include further reducing the risk of breaching the predefined geographical restrictions or reducing the risk of collision by ensuring that the operation of the vehicle is adapted with safety margin.

[0012] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to assume that the vehicle is heading toward the nearest geographical zone in response to only receiving travel distance data from the relative positioning system. A technical benefit may include the ability to maintain operational integrity in minimal data situations. Such configuration may further allow the computer system to make technically informed decisions about vehicle trajectory and potential entry into restricted zones even when detailed positional data is unavailable, ensuring continuous compliance with operational safety standards.

[0013] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to receive data indicative of multiple geographical zones within the confined geographical area, and further configured to determine shortest travel distance to each one of the geographical zones of the multiple geographical zones. A technical benefit may include enhanced route planning that reduces unnecessary detours. By calculating the shortest paths to multiple zones, the computer system can better navigate the vehicle, avoiding areas with potential restrictions or hazards preemptively.

[0014] Optionally in some examples, including in at least one preferred example, the processing circuitry is configured to receive data indicative of multiple geographical zones having different operational restricting conditions.

[0015] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to identify the occurrence of one or more non-drivable areas and refine the determined shortest travel distance to any one of the multiple geographical zones based on the identified one or more non-drivable areas. A technical benefit may include increased precision in determining the shortest possible path for the vehicle, thus further improving the productivity as it may become possible to maintain a higher speed for longer time. Such configuration may also reduce the risk of experience potentially hazardous or inaccessible areas, maintaining smooth and safe operation.

[0016] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to determine one or more vehicle restriction criteria based on the duration and / or distance travelled since the last-received absolute positioning data from the absolute positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria. A technical benefit may include the implementation of precautionary measures based on the duration or distance that has elapsed without reliable GPS data (absolute positioning data). Such configuration may further enhance safety by adjusting vehicle operations to a relatively conservative mode under uncertain positioning conditions, thereby mitigating risks associated with outdated or missing data.

[0017] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to determine one or more vehicle restriction criteria based on an estimated error of the relative positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria. A technical benefit may include enhanced error management which allows the vehicle to adjust its operational parameters based on the accuracy of the fallback (relative) positioning system. By calibrating operations to the reliability of the positioning data, the computer system may provide for higher safety margins and more precise adherence to geofencing restrictions.

[0018] Optionally in some examples, including in at least one preferred example, the processing circuitry may be configured to determine one or more vehicle restriction criteria based on an uncertainty in estimating a vehicle position relative to the at least one geographical zone, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria. A technical benefit may include proactive safety measures that prepare the vehicle for uncertain geofence crossings, such as automatically slowing down or adjusting other operational parameters preemptively.

[0019] Optionally in some examples, including in at least one preferred example, the relative positioning system may be configured to estimate the vehicle position relative to the at least one geographical zone over time based on odometry data. A technical benefit may include an even more improved reliability in tracking the position of the vehicle without reliance on external signals, enabling continuous operation under conditions where e.g. GPS is unavailable or unreliable, such as in tunnels.

[0020] Optionally in some examples, including in at least one preferred example, the odometry data may contain any one of vehicle speed data, vehicle acceleration data, turning rate data, wheel rotation data, vehicle orientation data, and relative distance traveled data.

[0021] Optionally in some examples, including in at least one preferred example, the odometry data may contain the vehicle speed data, the vehicle acceleration data, the turning rate data, the wheel rotation data, the vehicle orientation data, and the relative distance traveled data. A technical benefit may include the ability to utilize a comprehensive set of vehicle dynamics data to enhance the accuracy of the relative positioning system. This multifaceted approach allows for a more nuanced understanding of vehicle movement, contributing to safer and more efficient navigation decisions.

[0022] Optionally in some examples, including in at least one preferred example, the relative positioning system may comprise any one of an inertial measurement unit, lidar, radar, ultrasonic sensor, mono camera, stereo camera, wheel speed sensor, steering angle sensor, and gyroscope. Optionally in some examples, including in at least one preferred example, the relative positioning system may comprise the inertial measurement unit, lidar, radar, ultrasonic sensor, mono camera, stereo camera, wheel speed sensor, steering angle sensor, and the gyroscope. A technical benefit may include providing a robust and versatile systematic approach to vehicle positioning and environmental perception, enabling the autonomous vehicle to adapt to a wide range of operational environments by leveraging different sensor technologies.

[0023] Optionally in some examples, including in at least one preferred example, the processing circuitry is configured to determine that the vehicle is within the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone. In this manner, the computer system allows for determining the occurrence of the vehicle entrance into the geographical zone.

[0024] Optionally in some examples, including in at least one preferred example, the processing circuitry is configured to predict a vehicle entrance in the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone. In this manner, the computer system allows for predicting future / upcoming vehicle entrance in the geographical zone so as to apply an even more proactive adaptation of the operation of the vehicle ahead of the geographical zone.

[0025] Optionally in some examples, including in at least one preferred example, the processing circuitry is configured to determine a distance between the vehicle and a destination location in the confined geographical area.

[0026] Optionally in some examples, including in at least one preferred example, the processing circuitry is configured to determine the distance from pre-recorded trajectories corresponding to roads within the confined geographical area.

[0027] According to a second aspect of the disclosure, there is provided a vehicle comprising the computer system according to the first aspect. The second aspect of the disclosure may seek to solve the same problem as described for the first aspect of the disclosure. Thus, effects and features of the second aspect of the disclosure are largely analogous to those described above in connection with the first aspect of the disclosure.

[0028] According to a third aspect of the disclosure, there is provided a computer-implemented method for controlling an autonomous vehicle operation of an autonomous vehicle within a confined geographical area, the method comprising: receiving, by processing circuitry of a computer system, data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions; determining, by the processing circuitry of the computer system, to use a relative positioning system in response to a detected low confidence in absolute positioning data from an absolute positioning system; using, by the processing circuitry of the computer system, the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and adapting, by the processing circuitry of the computer system, the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

[0029] The third aspect of the disclosure may seek to solve the same problem(s) as described for the first to second aspects of the disclosure. Thus, effects and features of the third aspect of the disclosure are largely analogous to those described above in connection with the first and second aspects of the disclosure.

[0030] According to a fourth aspect of the disclosure, there is provided a computer program product comprising program code for performing, when executed by the processing circuitry comprised in the computer system of the first aspect, the method of the third aspect.

[0031] According to a fifth aspect of the disclosure, there is provided a non-transitory computer- readable storage medium comprising instructions, which when executed by the processing circuitry of the first aspect, cause the processing circuitry to perform the method of the third aspect.

[0032] 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.

[0033] 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 and / or technical improvements.BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Examples are described in more detail below with reference to the appended drawings.

[0035] FIGS. 1A - IB illustrate exemplary views of vehicles and vehicle powertrain systems, comprising a computer system having a processing circuitry configured to control traction force and brake force distribution of the vehicle according to an example.

[0036] FIG. 2 illustrates an exemplary overview of a confined geographical area with a number of autonomous vehicles, according to examples.

[0037] FIG. 3 illustrates another exemplary overview of a confined geographical area with a number of autonomous vehicles, according to examples.

[0038] FIG. 4 is a flow chart of an exemplary method to control a vehicle according to an example.

[0039] FIG. 5 is a schematic diagram of an exemplary computer system for implementing examples disclosed herein, according to an example.DETAILED DESCRIPTION

[0040] 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.

[0041] The present disclosure is at least partly based on the realization that deploying and controlling autonomous vehicles, such as autonomous electric vehicles, in a confined geographical area may still be challenging in terms of providing a reliable and safe operation of the vehicle. By way of example, autonomous vehicle operations can be compromised in environments where absolute positioning data (e.g., from GNSS) is unreliable, such as in areas with obstructions that disrupt signal reception. Examples of such areas include tunnels that fully block the signal, tall walls or buildings that can lead to signal reflections causing inaccurate positioning. Autonomous vehicle operations can also be compromised in environments where absolute positioning relies on lidar technology combinedwith a pre-recorded map. Complications arise particularly when data loss occurs due to sensor coverage issues or changes in environmental features. Sensor coverage can be temporarily obstructed by elements such as dust or rain.

[0042] Moreover, for autonomous operation zones in confined areas, there is typically a need for maintaining prescribed speed thresholds to mitigate collision risks involving autonomous vehicles (AVs), interactions between AVs and manually operated vehicles, and occasionally, encounters between AVs and vulnerable road users (VRUs). One approach to enforce such regulations is through geofencing technology, whereby specific geographical zones are delineated and associated with predefined operational conditions, such as speed limits. Upon an entry of an AV into a designated geographical zone, the corresponding operational condition may be automatically enforced, for instance, adjusting the vehicle speed to comply with the speed limit in the geographical zone. Additionally, geofencing allows for the integration of various other functional mandates related to vehicle operation within these zones. For example, to enhance VRU safety, certain areas can be configured to initiate emergency halting of the AV. Such safety protocol can be activated when the AV either enters or is on the verge of entering such zones, thereby ensuring immediate cessation of the vehicle to prevent potential harm to VRUs present within these the geographical zones.

[0043] Geofencing is a recognized technology that typically depends on the precise positioning of a vehicle in conjunction with pre-established geographical zones and their associated operational directives. However, there is a challenge in controlling AVs in environments where consistent positioning may be challenging, such as areas with tunnels or substantial structures that obstruct GPS signals.

[0044] For these and other reasons, there is still a need for improving the operations of autonomous vehicles in confined geographical areas.

[0045] To remedy this, the present disclosure provides a computer system, a vehicle including the computer system, and methods for controlling at least one of the vehicles in the confined geographical area.

[0046] Thus, the disclosure seeks to enhance the resilience of autonomous vehicle operations within environments where traditional GPS-based positioning systems would fail. More specifically, the disclosure aims to maintain a high level of operational safety by enabling the proposed computer system, even in the absence of reliable absolute positioning data, to control the vehicle to continue navigating safely within the confined geographical area by utilizing data from the relative positioning system. Moreover, the proposed computer system is configured to receive data indicative of one or more geographical zones within the confined area, each one being defined by specific operational restricting conditions. When low confidence in the absolute positioning data is detected, the computer system determines to rely less on the absolute positioning data and rather use, or sometimescompletely switch to, the relative positioning system in determining positions of the vehicle relative to the zones. The computer system then estimates the vehicle position relative to the at least one geographical zone and adapts the operation(s) of the vehicle accordingly to comply with the zone specific conditions such as speed limits. Thus, the computer system allows the vehicle to maintain adherence to safety protocols and operational restrictions dynamically, even in challenging navigation situations.

[0047] A technical benefit may include enhanced reliability and safety of autonomous vehicle operations in confined areas and across diverse environmental conditions where traditional GPS data may be intermittent or unavailable. Moreover, the proposed computer system may not only allow for mitigating the risk associated with signal loss but also increasing the likelihood of compliance with operational constraints, thereby ensuring safer navigation and adherence to predefined geographical restrictions within the confined area.

[0048] By minimizing, or at least reducing, dependency on absolute positioning systems such as satellite-based GPS, the proposed computer system enables geofencing to remain effective as a safety mechanism, even in locations where GPS connectivity is compromised.

[0049] To this end, the proposed computer system allows for improving the control of one or more autonomous electric vehicles in a confined geographical area containing one or more operating restricting conditions.

[0050] Examples of such computer systems and vehicles will now be described in relation to FIGS. 1A to IB, in combination with FIGS. 2 to 5.

[0051] In FIG. 1A, there is illustrated one example of a vehicle 10. The vehicle 10 is here a heavy-duty vehicle, such as a truck. While the vehicle 10 in FIG. 1A is illustrated as a truck, the vehicle 10 may be of any type of vehicle suitable for transporting people and / or goods, such as bulk material from one location to another. For example, the vehicle may be an excavator, loader, articulated hauler, dump truck, truck or any other suitable vehicle known in the art. In some examples, the vehicle 10 may be driven by an operator. The vehicle 10 is an autonomous vehicle that is controlled by a vehicle motion management (VMM) unit configured to individually control vehicle units and / or vehicle axles and / or wheels of the vehicle.

[0052] In FIG. 1A, the vehicle 10 is also an electric vehicle. Accordingly, the vehicle 10 is an autonomous electric vehicle. The vehicle 10 comprises a powertrain system 14. The powertrain system 14 comprises a propulsion unit 20. The propulsion unit may be provided by one or more electrical machines. In other types of arrangement, the propulsion unit 20 may include a tractionsupporting internal combustion engine. The propulsion unit is 20 typically an energy converting unit configured to provide a torque. In this example, the propulsion unit 20 is an electric machine.

[0053] The electric machine 20 is further powered by a battery system and / or a fuel cell system. Hence, the powertrain system 14 here also comprises any one of a battery system 21 and a fuel cell system 22. In other words, the powertrain system 14 is an electric powertrain system and the vehicle 10 is a fully electrical vehicle. However, in some examples, the vehicle 10 may also include a supporting internal combustion.

[0054] Accordingly, the powertrain system 14 in FIG. 1A comprises at least one propulsion unit in the form of one or more electric machines 20, the battery system 21 and the fuel cell system 22.

[0055] The powertrain system 14 is configured to provide traction power for the vehicle 10. The traction power is delivered to one or more ground engaging members 15, 16, 17, e.g. one or more wheels of the vehicle 10. By way of examples, the traction power is delivered to the wheels, such as the wheels 15 by any one of the battery system 21 and the fuel cell system 22 in cooperation with one or more electric machines 20.

[0056] Electric machines 20 are responsible for converting electrical energy from the battery system 21 or fuel cell system 22 into mechanical power to drive the vehicle's wheels. The electric machine 20 is thus configured to provide traction power to the vehicle 10. The electric machine 20 is configured to be connected to the battery system 21 and the fuel cell system 22. It should be noted that the powertrain system 14 may be provided with a plurality of electric machines 20.

[0057] The powertrain system 14 may further comprise additional components as is readily known in the field of electrical propulsions systems, such as a transmission for transmitting a rotational movement from the electric machine(s) to a propulsion shaft, sometimes denoted as the drive shaft (not shown). The propulsion shaft connects the transmission to the wheels. Some vehicles may use a traditional multi-speed transmission, while others employ single-speed transmissions or direct-drive configurations for simplicity and efficiency. Furthermore, although not shown, the electrical machine 20 is typically coupled to the transmission by a clutch. The electric machine 20 is arranged to receive electric power from any one of the battery system and the fuel cell system. The electric machine 20 is here also arranged specifically as a traction electric machine for the vehicle. The traction electric machine is configured to provide traction power to the vehicle 10.

[0058] Moreover, as illustrated in FIG. 1A, the vehicle 10 comprises a chassis 30 and a load carrying container 31 connected to the chassis 30. The chassis 30 is configured to support the load carrying container 31. The load carrying container 31 is configured to carry materials, such as mining shovel or the like.

[0059] As depicted in FIG. 1A, the vehicle 10 is supported by wheels 15, 16, 17, where each wheel comprises a tire. The vehicle 10 comprises multiple axles, including a front axle 11 and a number of rear axles 12, 13. The front axle 11 is here considered as a first wheel axle. Moreover, one of the rear axles, such as the rear axle 12, is considered as the second wheel axle. The tractor unit hasfront wheels 15 which are normally steered, and rear wheels 16, 17 of which at least one pair are driven wheels. Any one of the front axle 11 and the rear axles 12, 13 may be configured to be driven by the powertrain system 14. In some examples, only the front axle is driven by the powertrain system 14. In other examples, only one of the rear axles, such as the rear axle 12, is driven by the powertrain system 14. In yet other examples, all axles 11, 12, 13 are driven by the powertrain system 14.

[0060] FIG. IB schematically illustrates another example of an autonomous electric vehicle 10. The vehicle 10 of FIG. 10 is a load carrying vehicle in the form of a hauler. The load carrying vehicle 10 comprises the chassis 30, the load carrying container 31 connected to the chassis 30, and a plurality of wheels 15, 16. The vehicle 10 of FIG. IB further comprises the front axle 11. The front axle 11 is provided with the pair of wheels 15. Moreover, the vehicle 10 of FIG. IB comprises the rear axle 12. The rear axle 12 is provided with the corresponding set of pair of wheels 16. The vehicle 10 of FIG. IB is also an example of an autonomous electric vehicle comprising front wheel and rear wheel steering. Hence, the vehicle 10 here comprises a front wheel steering device 24 and a rear wheel steering device 26. Each one of the front wheel steering device 24 and the rear wheel steering device 26 is configured to control steering of the respective axle and its corresponding wheels. Each one of the front wheel steering device 24 and the rear wheel steering device 26 is connected to the computer system 100. Hence, the computer system 100 is configured to control steering of the front axle 11 and the rear axle 12. The steering of the front axle 11 and the rear axle 12 can be performed either individually, or in combination. As such, the computer system 100 is configured to control steering of the front axle 11 and the rear axle 12 by means of the front wheel steering device 24 and the rear wheel steering device 26, respectively. Such steering is automatically controlled by the computer system 100, as is commonly known within the field of autonomous vehicles.

[0061] The vehicles 10 in FIGS. 1A and lb further comprise one or more brakes, which are provided e.g. in the form of one or more service brakes. The first (left) and second (right) driven wheels are typically arranged to be braked by respective first and second service brakes. Each one of the service brakes may, e.g., be a pneumatically actuated disc brake or drum brake. The wheel service brakes are controlled by corresponding brake controllers (not illustrated). Each one of the wheel brake controllers is here communicatively coupled to the computer system 100, allowing the computer system 100 to communicate with the brake controllers, and thereby control vehicle braking. These parts of the powertrain system 14 are conventional parts in an electric powertrain system, and thus not further described herein.

[0062] The computer system 100 may also be configured to control the transfer of torque from the electric machine 20, i.e. from the powertrain system 14, to the wheels, such as the front wheels 15. The computer system 100 may also be configured to control the transfer of torque from the electric machine 20, i.e. from the powertrain system 14, to plurality of set of wheel, such as the front wheels15 and the rear wheels 16. By way of example, the computer system 100 is configured to feed torque transfer command to the electric machine 20 to transfer torque to the wheels via the driven axle(s) of the vehicle 10.

[0063] The autonomous vehicle 10 of any one of FIGS. 1A to IB may be configured to autonomously navigate in a confined geographical area 200 as illustrated in FIGS. 2 and 3. By way of example, the vehicles 10 in the confined geographical area 200 are controlled along one or more vehicle pathways 220 in the form of a routes comprising a set of route segments, as illustrated in e.g. FIGS. 2 and 3. To navigate each respective route segment out of the set of segments, the autonomous vehicle 10 needs to know its location with respect to the route. To locate the autonomous vehicle 10 with respect to the route 220, a localization service may be used. In this example, the computer system 100 is configured to be in communication with an absolute positioning system 50 and a relative positioning system 60, as depicted in e.g. FIG. 2.

[0064] The absolute positioning system 50 is configured to determine a geographic location of the vehicle 10 in the confined geographical area 200. The absolute positioning system 10 is configured to determine the geographic location based on a global reference frame, typically latitude, longitude, and sometimes altitude. One example of an absolute positioning system is the Global Navigation Satellite System (GNSS). The GNSS is configured to find the location of the vehicle 10 based on communication with satellites. The GNSS may for example be GPS or any other alternatives, e.g. BeiDou, Galileo, GLONASS, or any other suitable satellite positioning system. GPS utilizes a constellation of satellites orbiting the Earth to provide location information to receivers on the ground.

[0065] The absolute positioning system 50 typically comprises one or more satellites, an antenna 51, a signal receiver 53, such as a GPS receiver, arranged in the vehicle 10, and a communication link 52 configured to transfer positioning data streams (positioning signal) between the antenna 51, the signal receiver 53 and the computer system 100.

[0066] Moreover, the absolute positioning system 50 is a wireless communication system, which may comprise any suitable wireless device configured to communicate with any number of suitable network entities in a wireless network forming the communication link 52. Based on a signal from the wireless device, such as the GPS receiver 50, the network entities may be able to triangulate the position of the wireless device, and thereby also locate the autonomous vehicle 10, and report the location back to the wireless device. Any other suitable methodology for locating the autonomous vehicle 10 with the use of the wireless network may also apply. For example, this may be any suitable telecommunications positioning methodology, e.g. by using ultra-wide band positioning and triangulation.

[0067] Moreover, while GNSS may typically represent the most appropriate technology for the computer system 100, it may also be possible to incorporate RTK (Real-Time Kinematic) to enhance the GNSS system by providing real-time corrections, thereby improving positioning accuracy. Furthermore, the feasibility of employing an absolute positioning system utilizing lidar technology in conjunction with a pre-recorded map may also be conceivable. Such map could be developed using a SLAM (Simultaneous Localization and Mapping) algorithm.

[0068] Further, the autonomous vehicle 10 comprises a relative positioning system 60, as depicted in e.g. FIG. 2. The relative positioning system 60 is configured to determine a position of the vehicle 10 in relation to other objects, such as other vehicles, or points of reference (without necessarily knowing its exact geographic coordinates). As such, the relative positioning system 60 is configured to determine a relative position of the vehicle 10 in relation to other objects, such as other vehicles, or points of reference, in the confined geographical area 200.

[0069] In one example, the relative positioning system 60 is configured to estimate the vehicle position relative to the at least one geographical zone over time based on odometry data. Accordingly, the relative positioning system 60 here comprises one or more odometry acquiring devices. The odometry data contains any one of vehicle speed data, vehicle acceleration data, turning rate data, wheel rotation data, vehicle orientation data, and relative distance traveled data. By way of example, the relative positioning system 60 comprises any one of an inertial measurement unit, lidar, radar, ultrasonic sensor, mono camera, stereo camera, wheel speed sensor, steering angle sensor, and gyroscope. Typically, the relative positioning system 60 comprises plurality of units and sensors, such as a set of sensors including lidar, radar, camera, and ultrasonic sensors. In this manner, the relative positioning system 60 is configured to measure the distance and angle between the vehicle 10 and surrounding objects, allowing the vehicle to navigate its environment, avoid obstacles, and maintain a safe distance from other vehicles. Any sensor in the set of sensors may be mounted at any suitable location of the autonomous vehicle 10. In one example, the set of sensors comprises at least one 2D Lidar sensor 60a, at least one 3D Lidar sensor 60b, at least one camera unit 60c, or any other suitable sensor. In some examples, the at least one 2D Lidar sensor may be arranged on multiple or all sides of the autonomous vehicle 10, e.g. such that the at least one 2D Lidar sensor is capable of scanning all surroundings of the autonomous vehicle 10. The at least one 3D Lidar sensor may be arranged on the roof of the autonomous vehicle 10 to be able to scan 360 degrees around the autonomous vehicle 10 and / or in the comers of the vehicle 10 to provide about 270 degrees of field of view. The at least one camera unit may comprise one or more different types of camera units arranged in one or more places of the autonomous vehicle 10. The at least one camera unit may comprise a Red, Green, Blue and Depth (RGBD) sensor camera unit which can record the surroundings and account for depth. The at least one camera unit may additionally, or alternatively, comprise any one of one or more infraredcameras, heat cameras, stereo cameras. It should be noted that the relative positioning system 60 is typically also configured to be in communication with the absolute positioning system 50.

[0070] The relative positioning system 50 has a lower accuracy than the absolute position data from the absolute positioning system 60.

[0071] The use of the relative positioning system 50 and the absolute positioning system 60 for controlling the vehicles 10 in FIG. 2 will now be further described.

[0072] Turning to FIG. 2, there is illustrated a number of vehicles 10 operating within a confined geographical area 200. In FIG. 2, the confined geographical area 200 corresponds to a quarry area. The confined geographical area 200 can be defined in several different manners, as is commonly known in the art.

[0073] By way of example, defining the confined geographical area 200 for autonomous vehicles 10 here involves specifying the boundaries and parameters within which these vehicles are authorized to operate. The definition of the confined geographical area 200 often includes considerations for geographic limits and operational boundaries for the vehicle(s) 10. More specifically, the confined geographical area 200 for autonomous vehicles 10 is defined by any one of geographic coordinates, which specifies the geographical coordinates (latitude and longitude) that define the boundaries of the area, physical landmarks, which identifies physical landmarks or boundaries that set the edges of the confined area, and digital mapping, which utilizes digital mapping technologies to create a virtual boundary for the confined area. GPS-based mapping systems can e.g. be employed to create a geofence, a virtual perimeter that the autonomous vehicles 10 should not cross. GPS or RFID (Radio- Frequency Identification) may also be used to further create a virtual boundary.

[0074] The definition of the confined geographical area 200 may also be based on operational boundaries, which specify operational restricting within the confined geographical area 200. The operational restricting may include speed limits, acceleration limits, deceleration limits, turning radius limits, specific routes, or areas where certain vehicle behaviors are restricted or encouraged. The definition of the confined geographical area 200 may also be based on environmental conditions (e.g. weather conditions, lighting, or specific road surfaces). The definition of the confined geographical area 200 may also be based on legal and regulatory framework and various safety measures.

[0075] In FIG. 2, the confined geographical area 200 comprises a plurality of geographical zones, such as the three geographical zones 224, 226 and 228, Each one of these geographical zones comprises at least one operation restricting condition. The term “operational restricting condition”, as used herein, typically refers to specific rules, regulations, or requirements that restrict or dictate the behavior of an autonomous vehicle within a certain geographical zone. Such conditions are typically set based on safety protocols, legal requirements, or environmental considerations. Examples of such operational restricting conditions are speed limits, access restrictions, and / or emission controls. Onecommon operational restricting condition might be a speed limit specific to a geographical zone, such as an ongoing working zone where the speed limit is reduced during working hours and / or when there are other vehicles operating within the zone. Another example of an operational restricting condition is access restrictions, in which a certain area might restrict vehicle access during specific times or for specific vehicle types (e.g., heavy vehicles banned during certain hours). Another operational restricting condition is an emission restriction. In areas with high pollution levels, there might be restrictions on the operation of vehicles with certain types of engines (e.g., diesel engines) or requirements for reduced emissions. Yet another restricting condition might be noise restrictions. Some zones, particularly near residential areas, might impose restrictions on noise levels, requiring vehicles to operate more quietly.

[0076] Also, in order to allow for communication between the vehicles 10, the confined geographical area 200 may generally include a communication protocols so as to establish communication protocols between the autonomous vehicles 10 and a central control system or infrastructure within the confined area. In this manner, the vehicles 10 can be monitored in real-time and further coordinated in relation to each other. In FIG. 2, the central control system is an integral part of the computer system 100.

[0077] The vehicles 10 are controlled in an autonomous manner so as to carry out several different transportation missions within the quarry area. The vehicles 10 are operating along one or more vehicle pathways 220, 220a, 220b, 220c, 220d, as illustrated in FIG. 2. The vehicles 10 may not only transport material from a first starting position (location) 222, such as a loading zone, to a second destination position (location) 223, such as an unloading zone, but also perform one or more quarrying operations, including e.g. removal of material from the earth’s surface. The materials may e.g. be rock, sand, gravel, limestone, or other minerals.

[0078] The vehicle pathway 220 is here typically defined by the road, including one or more road segments. The vehicle pathway 220 also corresponds to the intended route for the transport (transport mission). In other words, the computer system 100 typically receives transport mission characteristics about the upcoming transport mission, which here includes route data about the intended route. The intended route for the vehicle 10 thus refers to the pathway of the vehicle 10 for performing the transport mission. The vehicle pathway 220, sometimes also referred to as the vehicle path, thus refers to the specific trajectory or course that the vehicle 10 is planned to take to perform the transport mission. The vehicle pathway 220 typically encompasses the physical route traveled by a vehicle 10, as illustrated in FIG. 2. The route, or intended route, typically refers to a predetermined course for the vehicle 10 to operate from one place to another, e.g. from 222 to 223 along the vehicle pathway 220. The route can include a series of directions or instructions indicating the specific roads or paths to take along the vehicle pathway 220 to reach a destination.

[0079] Occasionally, the vehicles 10 may be subject to conditions resulting in a loss of positioning detecting via the absolute positioning system 50 due to different factors such as signal blocking etc. In other situations, the confidence in the absolute positioning data may be too low for detecting the position of the vehicle 10 along the vehicle pathway 220. By way of example, hilly terrains within the confined geographical area 200 may introduce additional complexities and disturbances in navigation, potential affecting the operation performance of the vehicles 10.

[0080] To this end, the vehicles 10 may be subjected to unpredictable losses of positioning that can adversely affect the communication between vehicle 10 and the computer system 100, as well as between vehicle 10 and any adjacent vehicles. For example, being subjected to a loss of positioning within the confined geographical area 200 may result in vehicle 10 entering one of the geographical zones 224, 226, 228 in a manner that violates the operational restriction conditions of these zones, such as breaching speed limits or other zone-specific regulations. In FIG, 2, the destination 223 is localized within the geographical zone 224. In other transport missions, the destination may be localized outside the geographical zones 224, 226, 228, however, still requiring the vehicle 10 to cross one or more the geographical zones 224, 226, 228 for reaching the destinations 223. In yet other examples, the transport mission may contain deliver of material to several destinations in multiple geographical zones 224, 226, 228.

[0081] As will be described hereinafter, the computer system 100 is configured to control at least one vehicle, such as the vehicle 10a, of a plurality of vehicles 10 based on an estimated vehicle position relative to at least one geographical zone, such as the geographical zone 224, and the operational restricting conditions applying to the geographical zone 224. It should be appreciated that the computer system 100 may likewise be configured to control the other vehicles in similar fashion. For ease of reference, however, an example of the disclosure is described in relation to a control of one vehicle 10, such as the vehicle 10a.

[0082] The computer system 100 is here an integral part of the vehicle 10. It should be noted that the computer system 100 may be an integral part of the powertrain system 14. In other examples, the computer system 100 and the powertrain system 14 may be separate parts configured to communicate with each other. In addition, or alternatively, the computer system 100 may e.g. be a part of a remote server, such as the central control system, or the like, as illustrated in e.g. FIG. 2 and FIG. 3, while further being configured to be in communication with one or more corresponding sub-computer systems 100’ of the vehicles 10. Hence, in some examples, there is provided a computer system 100 comprising a central control system and a number of vehicles 10, each one of the vehicles having a sub-computer system, and wherein the central control system is configured to be in communication with the sub-computer systems of the vehicles 10 so as to control each vehicle 10 based on itsestimated position relative to one or more geographical zones and the operational restricting condition(s) applying to the one or more geographical zones.

[0083] As further illustrated, the computer system 100 comprises processing circuitry 102. The processing circuitry 102 is configured to control at least one vehicle, and in some example a plurality of vehicles 10, as described herein.

[0084] The computer system 100 may also comprise a memory and a system bus (although not illustrated). These components and further optional technical details of the computer system 100 are described in relation to FIG. 5.

[0085] As mentioned herein, the processing circuitry 102 is in communication with the absolute positioning system 50 and the relative positioning system 60.

[0086] Typically, the positioning of the vehicle 10 within the confined area 200 is controlled by means of the absolute positioning system 50 and the relative positioning system 60 in cooperation with the computer system 100, and further in cooperation with the other components of the powertrain system 14, such as the propulsion unit (e.g. the electric machine 20) and the steering device(s).

[0087] The processing circuitry 102 is configured to receive data indicative of the geographical zones 224, 226, 228 within the confined geographical area 200. Each one of the geographical zones 224, 226, 228 comprises one or more operational restricting conditions, as described above. As such, each one of the geographical zones 224, 226, 228 is associated with at least one operational restricting condition for the vehicle(s) 10.

[0088] Moreover, the processing circuitry 102 is configured to determine to use the relative positioning system 60 in response to a detected low confidence in absolute positioning data from the absolute positioning system 50. In other words, when the processing circuitry 102 detects that no reliable absolute positioning data is received from the absolute positioning system 50, the processing circuitry 102 determines to use the relative positioning system 60. As such, the processing circuitry 102 switch from the absolute positioning system 50 to the relative positioning system 60 in response to the detected low confidence in absolute positioning data. In some situations, the computer system 100 may already use both the absolute positioning system 50 and the relative positioning system 60 when the low confidence in absolute positing data is detected. In such situations the computer system 100 determines to only use the relative positioning system 60. Detected low confidence in the absolute positioning data is determined as non-reliable absolute positioning data by the processing circuitry 102.

[0089] The term “low confidence in absolute positioning data”, as used herein, typically refers to situations where low confidence in absolute positioning data is detected, typically occurring when the data received from, e.g., global positioning systems (GPS) or other absolute positioning systems is unreliable, inaccurate, or uncertain. This can be due to various factors affecting signal quality andaccuracy. Examples of situations when low confidence in absolute positioning data may be detected are signal blockage due to tall buildings, tunnels, or natural terrain features such as mountains, which can block or reflect GPS signals, leading to poor signal quality; signal multipath (e.g., GPS signals can reflect off buildings causing delays and errors in the position data); atmospheric conditions (e.g., atmospheric disturbances can interfere with GPS signal transmission, reducing accuracy); and equipment malfunction (e.g., issues with the GPS receiver or outdated firmware can lead to inaccurate position data).

[0090] To this end, detected low confidence in the absolute positioning system 50 amounts to a situation where the absolute positioning system 50 reports no data, or reports data with low confidence, etc. Determining the level of confidence (low, medium, or high) in the readings from the absolute positioning system, such as GNSS, typically involves assessing the quality and reliability of the data it provides. Such assessment is e.g. performed by the processing circuitry 102. If the absolute positioning system reports "no data" or explicitly states that the data is of "low confidence," this typically falls under the low confidence category. This could mean the system recognizes that the conditions for reliable data are not met (such as insufficient satellites or poor signal quality). "Medium confidence" might be indicated by partial data availability or moderate signal quality and satellite coverage. "High confidence" typically implies optimal conditions with strong, consistent signal reception from multiple satellites, low GDOP, and all system integrity checks passed. These assessments allow the computer system 100 to categorize the confidence level of the positioning data accurately.

[0091] Accordingly, responsive to the detected low confidence in absolute positioning data, the processing circuitry 102 determines to rely less on the absolute positioning data and typically switches to an operation where the relative positioning system 60 is used for estimating the position of the vehicle 10 within the confined geographical area 200. It should be noted that the relative positioning system 60 can be used also when the absolute positioning system 50 is active to increase accuracy.

[0092] The processing circuitry 102 is further configured to use the relative positioning system 60 for estimating a vehicle position relative to the at least one geographical zone, such as the geographical zone 224 in FIG. 2. To this end, the relative positioning system 60 transmit data to the processing circuitry 102, meanwhile the processing circuitry 102 uses positioning data indicative of the last known position of the vehicle 10, as determined by the absolute positioning system 50. By way of example, the processing circuitry 102 is configured to control the relative positioning system 60 to utilize the last known vehicle position as determined by the absolute positioning system 50, and further estimate whether the vehicle 10 may have reached one of the geographical zones 224, 226, 228 since the last known vehicle position, as determined by the absolute positioning system 50.

[0093] As such, the processing circuitry 102 is typically configured to establish the vehicle position in the confined geographical area 200 based on a previously determined positioning of the vehicle 10, as determined from high-confidence absolute positioning data by the absolute positioning system 50, and then configured to estimate the vehicle position relative to the at least one geographical zone using the relative positioning system 60, wherein the previously determined positioning of the vehicle is used as reference point for the processing circuitry 102 and the relative positioning system 60.

[0094] It should be noted that the vehicle position relative to the at least one geographical zone refers to the estimated location of the vehicle with respect to a predefined geographical zone. Thus, the estimated position may not always be a single precise point but rather a region within which the vehicle is likely located.

[0095] Moreover, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 based on the estimated vehicle position relative to the at least one geographical zone 224, 226, 228 and the operational restricting conditions applying to the at least one geographical zone 224, 226, 228. By way of example, based on the estimated vehicle position relative to the geographical zone 224, the processing circuitry 102 determines to adapt the operation of the vehicle 10 relative to the operational restricting condition applying to the geographical zone 224.

[0096] As such, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 prior to the entrance of the geographical zone 224. In other examples, the processing circuitry 102 may decide that it is sufficient to adapt the operation of the vehicle 10 on the verge of entering such zones. In this context, it should be noted that some adaptations of the operations, such as reducing speed, need to be executed before entering a zone to ensure the vehicle 10 complies with speed limits upon entry. Conversely, adaptations of other operations may be activated upon zone entry, such as an emergency stop.

[0097] In other examples, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 if it is determined that the vehicle 10 already has entered the geographical zone 224. As such, in some examples, the processing circuitry 102 is configured to determine that the vehicle 10 is within the at least one geographical zone, such as the geographical zone 224, based on the estimated vehicle position relative to the at least one geographical zone 224. The vehicle position relative to the at least one geographical zone 224 is estimated by means of the relative positioning system 60, as described herein.

[0098] In addition, or alternatively, the processing circuitry 102 is configured to predict a vehicle entrance in the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone. As such, the processing circuitry 102 is configured to use the relative positioning system 60 for predicting a possible vehicle entrance of at least one geographical zone,such as the geographical zone 224 in FIG. 2. To this end, the relative positioning system 60 transmit data to the processing circuitry 102, meanwhile the processing circuitry 102 uses positioning data indicative of the last known position of the vehicle 10, as determined by the absolute positioning system 50. As mentioned above, the processing circuitry 102 is configured to control the relative positioning system 60 to utilize the last known vehicle position as determined by the absolute positioning system 50, and further estimate whether the vehicle 10 may have reached one of the geographical zones 224, 226, 228 since the last known vehicle position, as determined by the absolute positioning system 50. Moreover, in this example, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 based on the predicted vehicle entrance of the at least one geographical zone 224, 226, 228 and the operational restricting conditions applying to the at least one geographical zone 224, 226, 228. By way of example, based on the predicted vehicle entrance of the geographical zone 224, the processing circuitry 102 determines to adapt the operation of the vehicle 10 relative to the operational restricting condition applying to the geographical zone 224.

[0099] As such, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 prior to the entrance of the geographical zone 224. In other examples, the processing circuitry 102 may decide that it is sufficient to adapt the operation of the vehicle 10 on the verge of entering such zones. In this context, it should be noted that some adaptations of the operations, such as reducing speed, need to be executed before entering a zone to ensure the vehicle 10 complies with speed limits upon entry. Conversely, adaptations of other operations may be activated upon zone entry, such as an emergency stop.

[0100] Typically, although strictly not necessary, the processing circuitry 102 is configured to determine proximity to the nearest geographical zone of the group of geographical zones 224, 226, 228 based on the last-received absolute positioning data from the absolute positioning system 50. In addition, the processing circuitry 102 is configured to predict entrance of the nearest geographical zone. Further, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 based on the predicted vehicle entrance of the nearest geographical zone. Typically, the last-received absolute positioning data should also be determined as reliable absolute positioning data. Thus, the processing circuitry 102 is here configured to determine the reliability of the absolute positioning data. For example, the processing circuitry 102 determines that the absolute positioning data is reliable if the data is of medium or high confidence, as mentioned above.

[0101] In other words, in situations where absolute positioning data becomes unavailable, the stored, or determined shortest distance to a geographical zones 224, and its associated operational restricting condition may thus serve as a reference for the processing circuitry 102 and the vehicle 10. The vehicle 10 then employs the relative positioning system 60 as a fallback positioning system, and operate the vehicle 10 based on e.g. vehicle odometry, inertial measurement units (IMU), and / or otheronboard sensor-derived data, so as to maintain a record of distance traveled since the last update. As long as the calculated movement distance of the vehicle 10 remains less than the shortest recorded distance to any one of the geographical zones 224, 226, 228, the computer system 100 assumes that the vehicle 10 has not entered any one of the geographical zones 224, 226, 228, and thus, no action is required. However, if the traveled distance exceeds the shortest distance to one of the geographical zones 224, 226, 228, the processing circuitry 102 decides to adapt the operation of the vehicle 10 based on the predicted vehicle entrance as the vehicle 10 may approach or may have already reached the zone.

[0102] To this end, the computer system 100 is configured to prevent the vehicle 10 from entering the geographical zones 224, 226, 228 at excessively high speeds. Such configuration of the compute system 100 not only ensures safety but also maintains a higher productivity by allowing the vehicle(s) 10 to continue operation. In the event that the absolute positioning system 50 completely fails to return to providing high-confidence positioning data, the processing circuity 102 would typically decide to halt one or more vehicles 10. Typically, the adaptation of vehicle behavior upon entering a geographical zone aims to mitigate the risk of collisions and other hazardous incidents.

[0103] In addition, or alternatively, the processing circuitry 102 is further configured to determine a distance between the vehicle 10a and the destination location 223 in the confined geographical area 200. In such example, the processing circuitry 102 is configured to determine the distance from pre-recorded trajectories corresponding to roads within the confined geographical area 200.

[0104] It should be noted that the processing circuitry 102 usually assumes that vehicle 10a is heading to the nearest geographical zone, such as geographical zone 224. Configuring the processing circuitry 102 to assume that vehicle 10a is heading to the nearest geographical zone serves to adopt a more conservative approach.

[0105] In some examples, the processing circuitry 102 is configured to assume that the vehicle 10 is heading toward the nearest geographical zone in response to only receiving travel distance data from the relative positioning system 50. Such assumption of the processing circuitry 102 may occur in situations where the processing circuitry 102 merely receives travel distance data from the relative positioning system 50.

[0106] In some examples, the processing circuitry 102 is configured to determine the shortest travel distance to each one of the geographical zones 224, 226, 228. In addition, or alternatively, the processing circuitry 102 is configured to determine the shortest travel distance among the determined shortest travel distances to the geographical zones 224, 226, 228.

[0107] In the above examples, the processing circuitry 102 is thus configured to receive data indicative of multiple geographical zones 224, 226, 228 within the confined geographical area 200,and further configured to determine shortest travel distance to each one of the geographical zones of the multiple geographical zones 224, 226, 228. As the multiple geographical zones 224, 226, 228 may have different operational restriction conditions, such as different speed limits and / or activation of one or more vehicle functions, the processing circuitry 102 is here typically also configured to receive data indicative of multiple geographical zones having different operational restricting conditions.

[0108] In other words, the computer system 100 may often need to manage multiple geographical zones 224, 226, 228 simultaneously, particularly if the geographical zones 224, 226, 228 mandate different actions (e.g., speed limits vs. emergency stops). If the vehicle 10 travels a distance that might suggest entry into multiple geographical zones 224, 226, 228 with varying restrictions, the most restrictive adaption of the vehicle operation may be executed to ensure compliance with all possible operating restriction conditions of the geographical zones 224, 226, 228.

[0109] In addition, or alternatively, the processing circuitry 102 is configured to determine one or more vehicle restriction criteria for the vehicle 10 based on duration and / or distance travelled since last-received absolute positioning data from the absolute positioning system 6. Moreover, the processing circuitry 102 is configured to adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria. One example of a vehicle restriction criteria is a vehicle stopping criteria. Another example of a vehicle restriction criteria may be a steering adjustment criteria for the vehicle.

[0110] As such, the processing circuitry 102 here also includes provisions for stopping the vehicle 10 under certain conditions to mitigate risks associated with positioning uncertainty. For example, the processing circuitry 102 may halt operation of the vehicle 10 if the absolute positioning system 50 remains inactive beyond a predefined duration or distance, reducing the risk of erroneous zone entry.[OHl] For example, the processing circuitry 102 is configured to determine one or more vehicle restriction criteria based on an estimated error of the relative positioning system 50. In addition, or alternatively, the processing circuitry 102 is configured to determine one or more vehicle restriction criteria based on an uncertainty in estimating the vehicle position relative to the at least one geographical zone, such as the geographical zone 224. In one example, the processing circuitry 102 is configured to determine one or more vehicle restriction criteria based on an uncertainty in predicting vehicle entrance of at least one geographical zone, such as the geographical zone 224, which is based on estimated vehicle position relative to the geographical zone 224.

[0112] As such, the processing circuitry 102 is configured to adapt the operation of the vehicle 10 based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone, and further to adapt the operation of the vehicle 10 based on the determined one or more vehicle restriction criteria.

[0113] FIG. 3 schematically illustrates another example of a confined geographical area 200. The confined geographical area 200, the computer system 100, and the vehicles 10 are the same as in the example of FIG. 2. In addition, in FIG. 3, the confined geographical area 200 further comprises a plurality of non-drivable areas 230. The term “non-drivable area”, as used herein, typically refers to regions within a geographical area where vehicles are physically unable to drive. Examples of non- drivable areas are natural obstacles or infrastructure limitations. Natural obstacles may be rivers, lakes, or terrain features (e.g., cliffs) that vehicles cannot cross; man-made obstacles such as road sections closed due to construction, pedestrian zones, or areas designated for non-motorized traffic only. Moreover, the term "non-drivable area" may specifically refer to regions within the confined geographical area where autonomous vehicles are restricted from operating, despite these areas being physically navigable by manually operated vehicles. As such, while an autonomous vehicle may possess the physical capability to traverse such areas, regulatory, safety, or operational protocols may explicitly prohibit the autonomous vehicles from operating through or within such areas.

[0114] As such, in the example of FIG. 3, the processing circuitry 102 is configured to identify occurrence of one or more non-drivable areas 230. In addition, the processing circuitry 102 is configured to refine the determined shortest travel distance to any one of the multiple geographical zones 224, 226, 228 based on the identified one or more non-drivable areas 230. Accordingly, the processing circuitry 102 is configured to determine an alternative vehicle pathway 221 for the vehicle 10 based on the identified occurrence of one or more non-drivable areas 230 and the refined determined shortest travel distance. By way of examples, the processing circuitry 102 determines an alternative vehicle pathway 221 for the vehicle 10 to the geographical zone 224 based on the identified occurrence of the non-drivable area 230, and further based on a refined determined shortest travel distance in comparison with the previous vehicle pathway 220, as illustrated in FIG. 2.

[0115] Typically, the processing circuitry 102 is here also configured to receive travel mission data for the vehicle 10a. In this example, the processing circuitry 102 also receives travel mission data for the other vehicles 10 within the confined geographical area 200. As such, the computer system 100 receives travel mission data for at least one vehicle 10 of a plurality of vehicles 10, but typically for all vehicles 10 within the confined geographical area 200. The travel mission data comprises data about intended routes for completing one or more transport missions, such as travel mission data for the vehicle 10a for completing its transport mission along the vehicle path 220a. To this end, the processing circuitry 102 obtains transport mission characteristics for an upcoming transport mission for the vehicle 10a.

[0116] The travel mission data can be varied for different types of vehicles 10. By way of example, the travel mission data can contain data indicative of a transportation to transport materials and / or goods from point 222 (position / location) to point 224 (position / location) along a plannedroute, here corresponding to the vehicle path 220a, see e.g. FIG. 2. In other words, the transport should be performed by the vehicle 10a from a geographical starting point (first position) to a geographical destination (second position). The transport may typically be performed along a route, including one or more road segments and / or roads. Hence, the vehicle pathway 220, 220a is here a road. Other examples are also possible, such as transportation of people. The transportation may also include an iterative transportation of materials along a certain route. The processing circuitry 102 is typically configured to determine transport mission characteristics for the upcoming transport mission for the vehicle 10 based on the received transport mission data.

[0117] The travel mission data can be provided in several different manners to the processing circuitry 102. In addition, the travel mission data may contain several different types of data. By way of example, the travel mission data for an upcoming transport mission for the vehicle 10 comprises transport mission data indicative of at least the destination location 224 and a destination time. The destination time refers to a point in time for the vehicle 10a to arrive at the destination point 224.

[0118] In an extended example, the travel mission data further contains transport mission duration data, distance to be traveled and similar transport mission data. The transport mission data may also contain a speed restriction profile for the transport mission, a minimum speed profile for the transport mission, desired or required speed for different segments of the transport mission. It should be noted that the categorization of speed segments within the confined geographical area 200 is typically influenced from various factors pertaining to the road conditions. Such factors may include, but are not limited to, the type of material constituting the road surface, the physical topography of the road, and the width of the road. Roads constructed from coarser materials or those characterized by a more uneven surface generally necessitate a reduction in speed to maintain vehicle stability and ensure safety. Conversely, roads made from smoother materials allow for higher speeds. In areas where roads are steep or hilly, lower speeds are mandated due to the increased challenge of navigating such gradients safely. On the other hand, roads that are predominantly flat enable vehicles to travel at increased speeds due to reduced driving difficulties and lower risk factors. Wider roads typically provide sufficient room for vehicles to maneuver and pass safely, thereby supporting higher speed limits. In contrast, narrower roads require lower speeds to ensure safe passage of vehicles, particularly in areas where oncoming traffic must be negotiated.

[0119] In addition, or alternatively, the processing circuitry 102 is configured to obtain topology data from a number of data sources, such as digital maps, GPS data, or geographic information system (GIS) databases. These sources may generally include relevant information about the road network, including roads, elevation data, inclination data, and potential destinations. In one example, the topology data is received by the processing circuitry 102 from a route planner system of the computersystem 100 and / or the vehicle 10. In other examples, the topology data is obtained from previous transport missions along the planned route.

[0120] In addition, or alternatively, the topology data of the intended route for the transport mission may comprise relevant data for determining the route profile of the vehicle pathway 220, including elevation changes, inclination and inclination changes, road grade, and terrain type (urban, highway, off-road, etc.).

[0121] It should be noted that the processing circuitry 102 is typically configured to obtain realtime positioning data and / or vehicle data from all vehicles 10 within the confined geographical area 200. In addition, or alternatively, the processing circuitry 102 obtains real-time positioning data and / or vehicle data for all vehicles from the central control server, which is arranged in communication with the processing circuitry 102.

[0122] In addition, based on the estimated vehicle position relative to the geographical zone 224, and the operational restricting conditions applying to the geographical zone 224, the processing circuitry 102 adapts the operation of the vehicle 10a along the vehicle pathway 220a when the vehicle 10a performs its travel mission, such as the transportation of material in the illustrated geographical area of FIG. 2. As such, the processing circuitry 102 is configured to control the vehicle 10a based on the estimated vehicle position relative to the geographical zone 224, and the operational restricting conditions applying to the geographical zone 224 when performing and completing the travel mission.

[0123] In one example, the processing circuitry 102 adapts the operation of the vehicle 10a along the vehicle pathway 220a based on the predicted vehicle entrance of the geographical zone 224, and the operational restricting conditions applying to the geographical zone 224, when the vehicle 10a performs its travel mission, such as the transportation of material in the illustrated geographical area of FIG. 2. As such, the processing circuitry 102 is configured to control the vehicle 10a based on the predicted vehicle entrance of the geographical zone 224, and the operational restricting conditions applying to the geographical zone 224 when performing and completing the travel mission.

[0124] By way of example, the processing circuitry 102 adapts a driving mode by adapting a traction power to the drive axles and wheels. Adapting the driving mode by adapting the traction power is here controlled by controlling the transfer of traction force to the wheels of the front axle 11 and the rear axle 12. The traction force is provided by the propulsion unit, such as the electric machine 20. In some examples, each one of the axles, such as the front axle 11 and the rear axle 12 are powered by a separate electric machine. That is, the vehicle 10 comprises a plurality of electric machines 20. It should also be noted that the computer system 100 may be configured to adapt the traction power to another set of axles among the axles of the vehicle 10, e.g. between the rear axles 12, 13.

[0125] In one example, the processing circuitry 102 adapts the operation of the vehicle 10, 10a based on the estimated vehicle position relative to the geographical zone 224, the operational restricting conditions applying to the geographical zone 224, and the determined one or more vehicle restriction criteria. To this end, the processing circuitry 102 adjusts the propulsion power of the electric machine(s) 20 based on the determined vehicle restriction criteria.

[0126] In other examples, the processing circuitry 102 adapts the driving mode by adapting a steering angle of the steering device(s) 24, 26 of one or more wheels. As such, the processing circuitry 102 is configured to adapt the driving mode by adapting a steering angle of the steering device(s). Such operation typically includes controlling one or more of the front and rear steering devices 24, 26 based on the determined one or more vehicle restriction criteria.

[0127] The above example in relation to FIGS. 2 and 3 are only brief examples of the disclosure for the ease of describing and illustrating the operations of the proposed computer system 100 and the methods herein.

[0128] As described above, the computer system 100 of FIGS. 2 and 3 is e.g. a part of a remote server (i.e. the central server), while further being configured to be in communication with a corresponding computer systems 100’ of the vehicle 10. The remote server is e.g. a centralized controller. Alternatively, or in addition, the processing circuitry 102 may be arranged in the central control system (part of the computer system 100) for the vehicles 10 and the confined geographical area 200.

[0129] As such, in an example where the computer system 100 is arranged, partly or entirely, in the remote server, e.g. as a central control system (part of the computer system 100) for the vehicles 10, the processing circuitry 102 is configured to collect data from the vehicles 10 on the site within the confined geographical area 200 via e.g. the wireless interface 52. The processing circuitry 102 is also configured to define and generate the transport mission to the vehicles 10, which together with the above determined adapted operations of the vehicle(s) 10 form the basis for the control commands for the vehicles 10 in the confined geographical area 200. To this end, the parts of the computer system 100, including one or more processing circuitry and control units, may be comprised in a single vehicle 10, in a plurality of vehicles 10 and / or be comprised in any other suitable location. The processing circuitry 102 of the computer system 100 may be communicatively connected with the absolute positioning system 50, the relative positioning system 60, including any one of one or more sensors of the vehicles 10, sensors within the confined geographical area 200, the GNSS, and the wireless network 52. The processing circuitry 102 may further be able to actuate the navigation of the autonomous vehicles 10, or at least be able to provide commands to the autonomous vehicles 10. The processing circuitry 102 may also be configured to feed additional motion commands to the vehicle 10 for realizing the route associated with the transport mission.

[0130] It should be noted that the present disclosure relates primarily to operational situations involving autonomous vehicles where reliable absolute positioning data is low or absent, typically due to detected low-confidence levels in such data. In such circumstances, the vehicle's computer system loses the safe positioning signal that is needed for operation. In this context, it is noteworthy that the operations as described herein are typically exerted during specific interventions when proximity issues between machines, possibly due to lost positioning, are detected. In other operations where there is reliable absolute positioning data available, the system described herein may not be used to exert control. The aim is thus typically to sustain operations until it is definitively unsafe to continue, which could occur when vehicles, typically both manual and autonomous, are in close proximity. The system is designed to monitor the situation conservatively, allowing operations to persist potentially until the safety-critical position data is restored, thus preventing unnecessary halts in operation.

[0131] For instance, if a manual and an autonomous vehicle operating within the same site lose positional data yet are known to be 2 kilometers apart, it can be safely assumed that they will not collide immediately since significant time is required to cover this distance. This assumption allows operations to continue while the situation is monitored conservatively for safety. Once positional accuracy is regained, the operations will resume. Accordingly, the operations of the processing circuitry as described herein may provide for a fallback system to the navigation system, which directly controls the vehicle's movement. As such, the proposed system functions to monitor operations and may intermittently intervene to ensure safety during operational anomalies.

[0132] FIG. 4 is a flow chart of an exemplary method to control an autonomous vehicle 10 according to an example. More specifically, FIG. 4 is an exemplary computer implemented method 300 according to an example. Thus the method 300 is implemented by the computer system 100 and the processing circuitry 102, as described herein. The computer-implemented method 300 is intended for controlling one or more vehicles 10, such as the vehicle 10a, operating in the confined geographical area 200. For example, the method 300 is intended for controlling an autonomous vehicle operation of the autonomous vehicle 10a within the confined geographical area 200 in FIG. 2 or FIG. 3.

[0133] As illustrated in FIG. 4, the method 300 comprises a step S10 of receiving, by the processing circuitry 102 of the computer system 100, data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions.

[0134] Moreover, the method 300 comprises a step S20 of determining, by the processing circuitry 102 of the computer system 100, to use a relative positioning system in response to a detected low confidence in absolute positioning data from an absolute positioning system.

[0135] In addition, the method 300 comprises a step S30 of using, by the processing circuitry 102 of the computer system 100, the relative positioning system 60 for estimating a vehicle position relative to the at least one geographical zone. Estimating the vehicle position relative to the at least one geographical zone is based on the last trustable position of the vehicle as determined from / by the absolute positioning system 50.

[0136] Also, the method 300 comprises a step S40 of adapting, by the processing circuitry 102 of the computer system 100, the operation of the vehicle 10 based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone

[0137] Optionally, in an extended example, the method 300 may further comprise receiving travel mission data for the vehicle 10 performing the travel mission, such as a transport mission, and using the received travel mission data for determining a distance between the vehicle 10 and the destination location 223 in the confined geographical area 200. Such data can be received by the processing circuitry 102. The processing circuitry 102 may typically also receive road topography data for the intended road. The road topography data includes information about the road's elevation, slope, curvature, and other geometric features. Road topography data is for example acquired by the absolute positioning system 50 and the relative positioning system 60, such as the onboard sensors and the GPS, as mentioned herein. The absolute positioning system 50 and the relative positioning system 60 may be integral part of an Autonomous Driving Systems.

[0138] In addition, or alternatively, the method 300 may comprise a step of determining the distance between the vehicle 10 and the destination location 223 in the confined geographical area 200 from pre-recorded trajectories corresponding to roads within the confined geographical area.

[0139] In some examples, there is provided a computer program product comprising program code for performing, when executed by the processing circuitry 102, the method 300 as described above.

[0140] In some examples, there is provided a non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry 102, cause the processing circuitry 102 to perform the method 300 as described above.

[0141] Further details of one example of a computer system that can be used as the computer system 100 will now be described in relation to FIG. 5.

[0142] FIG. 5 is a schematic diagram of a computer system 1000 for implementing examples disclosed herein. The computer system 1000 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 1000 may be connected (e.g., networked) to other machines in a LAN (Local AreaNetwork), 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 1000 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 or 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.

[0143] The computer system 1000 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 1000 may include processing circuitry 1002 (e.g., processing circuitry including one or more processor devices or control units), a memory 1004, and a system bus 1006. The computer system 1000 may include at least one computing device having the processing circuitry 1002. The system bus 1006 provides an interface for system components including, but not limited to, the memory 1004 and the processing circuitry 1002. The processing circuitry 1002 may include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory 1004. The processing circuitry 1002 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 1002 may further include computer executable code that controls operation of the programmable device.

[0144] The system bus 1006 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 1004 may be one or more devices for storing data and / or computer code for completing or facilitating methods described herein. The memory 1004 may include database components, object code components, script components, or other types of information structure for supporting the various activities herein. Any distributed orlocal memory device may be utilized with the systems and methods of this description. The memory 1004 may be communicably connected to the processing circuitry 1002 (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 1004 may include non-volatile memory 1008 (e.g., read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.), and volatile memory 1010 (e.g., random-access 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 1002. A basic input / output system (BIOS) 1012 may be stored in the non-volatile memory 1008 and can include the basic routines that help to transfer information between elements within the computer system 1000.

[0145] The computer system 1000 may further include or be coupled to a non-transitory computer-readable storage medium such as the storage device 1014, 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 1014 and other drives associated with computer- readable media and computer-usable media may provide non-volatile storage of data, data structures, computer-executable instructions, and the like.

[0146] 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 1014 and / or in the volatile memory 1010, which may include an operating system 1016 and / or one or more program modules 1018. All or a portion of the examples disclosed herein may be implemented as a computer program 1020 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 1014, which includes complex programming instructions (e.g., complex computer-readable program code) to cause the processing circuitry 1002 to carry out actions described herein. Thus, the computer-readable program code of the computer program 1020 can comprise software instructions for implementing the functionality of the examples described herein when executed by the processing circuitry 1002. In some examples, the storage device 1014 may be a computer program product (e.g., readable storage medium) storing the computer program 1020 thereon, where at least a portion of a computer program 1020 may be loadable (e.g., into a processor) for implementing the functionality of the examples described herein when executed by the processing circuitry 1002. The processing circuitry 1002 may serve as a controller or control system for the computer system 1000 that is to implement the functionality described herein.

[0147] The computer system 1000 may include an input device interface 1022 configured to receive input and selections to be communicated to the computer system 1000 when executing instructions, such as from a keyboard, mouse, touch-sensitive surface, etc. Such input devices may be connected to the processing circuitry 1002 through the input device interface 1022 coupled to the system bus 1006 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 1000 may include an output device interface 1024 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 1000 may include a communications interface 1026 suitable for communicating with a network as appropriate or desired.

[0148] 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.

[0149] Example 1 : A computer system 100 for controlling an autonomous vehicle operation of an autonomous vehicle 10 within a confined geographical area 200, the computer system comprising processing circuitry 102 configured to be in communication with an absolute positioning system 50 and a relative positioning system 60, the processing circuitry further being configured to: receive data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions; determine to use the relative positioning system in response to a detected low confidence in absolute positioning data from the absolute positioning system; use the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and adapt the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

[0150] Example 2: Computer system of example 1, wherein the processing circuitry is further configured to determine proximity to the nearest geographical zone of a group of geographical zones based on the last-received absolute positioning data from the absolute positioning system; predict entrance of the nearest geographical zone; and adapt the operation of the vehicle based on the predicted vehicle entrance of the nearest geographical zone.

[0151] Example 3: Computer system of example 2, wherein the processing circuitry is configured to assume that the vehicle is heading toward the nearest geographical zone in response to only receiving travel distance data from the relative positioning system.

[0152] Example 4: Computer system of any previous examples, wherein the processing circuitry is configured to receive data indicative of multiple geographical zones within the confined geographical area, and further configured to determine shortest travel distance to each one of the geographical zones of the multiple geographical zones.

[0153] Example 5: Computer system of example 4, wherein the processing circuitry is configured to receive data indicative of multiple geographical zones having different operational restricting conditions.

[0154] Example 6: Computer system of example 4 or example 5, wherein the processing circuitry is configured to identify occurrence of one or more non-drivable areas and refine the determined shortest travel distance to any one of the multiple geographical zones based on the identified one or more non-drivable areas.

[0155] Example 7: Computer system of any previous examples, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on duration and / or distance travelled since last-received absolute positioning data from the absolute positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

[0156] Example 8: Computer system of any previous examples, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on an estimated error of the relative positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

[0157] Example 9: Computer system of any previous examples, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on an uncertainty in estimating a vehicle position relative to the at least one geographical zone, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

[0158] Example 10: Computer system of any previous examples, wherein the relative positioning system is configured to estimate the vehicle position relative to the at least one geographical zone over time based on odometry data.

[0159] Example 11 : Computer system of example 10, wherein the odometry data contains any one of vehicle speed data, vehicle acceleration data, turning rate data, wheel rotation data, vehicle orientation data, and relative distance traveled data.

[0160] Example 12: Computer system of any previous examples, wherein the relative positioning system comprises any one of an inertial measurement unit, lidar, radar, ultrasonic sensor, mono camera, stereo camera, wheel speed sensor, steering angle sensor, and gyroscope.

[0161] Example 13: Computer system of any previous examples, wherein the processing circuitry is configured to determine that the vehicle is within the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone.

[0162] Example 14: Computer system of any previous examples, wherein the processing circuitry is configured to predict a vehicle entrance in the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone.

[0163] Example 15: Computer system of any previous examples, wherein the processing circuitry is configured to determine a distance between the vehicle and a destination location 223 in the confined geographical area.

[0164] Example 16: Computer system of example 15, wherein the processing circuitry is configured to determine the distance from pre-recorded trajectories corresponding to roads within the confined geographical area.

[0165] Example 17: A vehicle 10 comprising a computer system of any of the examples 1-16.

[0166] Example 18: A computer-implemented method 300 for controlling an autonomous vehicle operation of an autonomous vehicle 10 within a confined geographical area 200, the method comprising: receiving, by processing circuitry of a computer system, data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions; determining, by the processing circuitry of the computer system, to use a relative positioning system in response to a detected low confidence in absolute positioning data from an absolute positioning system; using, by the processing circuitry of the computer system, the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and adapting, by the processing circuitry of the computer system, the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

[0167] Example 19: A computer program product comprising program code for performing, when executed by the processing circuitry 102, the method of example 18.

[0168] Example 20: A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry, cause the processing circuitry to perform the method of example 18.

[0169] 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 associatedlisted items. It will be further understood that the terms "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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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

ClaimsWhat is claimed is:

1. A computer system (100) for controlling an autonomous vehicle operation of an autonomous vehicle (10) within a confined geographical area (200), the computer system comprising processing circuitry (102) configured to be in communication with an absolute positioning system (50) and a relative positioning system (60), the processing circuitry further being configured to:- receive data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions;- determine to use the relative positioning system in response to a detected low confidence in absolute positioning data from the absolute positioning system;- use the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and- adapt the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

2. Computer system of claim 1, wherein the processing circuitry is further configured to determine proximity to the nearest geographical zone of a group of geographical zones based on the last-received absolute positioning data from the absolute positioning system; predict entrance of the nearest geographical zone; and adapt the operation of the vehicle based on the predicted vehicle entrance of the nearest geographical zone.

3. Computer system of claim 2, wherein the processing circuitry is configured to assume that the vehicle is heading toward the nearest geographical zone in response to only receiving travel distance data from the relative positioning system.

4. Computer system of any previous claims, wherein the processing circuitry is configured to receive data indicative of multiple geographical zones within the confined geographical area, and further configured to determine shortest travel distance to each one of the geographical zones of the multiple geographical zones.

5. Computer system of claim 4, wherein the processing circuitry is configured to receive data indicative of multiple geographical zones having different operational restricting conditions.

6. Computer system of claim 4 or claim 5, wherein the processing circuitry is configured to identify occurrence of one or more non-drivable areas and refine the determined shortest travel distance to any one of the multiple geographical zones based on the identified one or more non-drivable areas.

7. Computer system of any previous claims, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on duration and / or distance travelled since last-received absolute positioning data from the absolute positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

8. Computer system of any previous claims, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on an estimated error of the relative positioning system, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

9. Computer system of any previous claims, wherein the processing circuitry is configured to determine one or more vehicle restriction criteria based on an uncertainty in estimating a vehicle position relative to the at least one geographical zone, and further adapt the operation of the vehicle based on the determined one or more vehicle restriction criteria.

10. Computer system of any previous claims, wherein the relative positioning system is configured to estimate the vehicle position relative to the at least one geographical zone over time based on odometry data.

11. Computer system of claim 10, wherein the odometry data contains any one of vehicle speed data, vehicle acceleration data, turning rate data, wheel rotation data, vehicle orientation data, and relative distance traveled data.

12. Computer system of any previous claims, wherein the relative positioning system comprises any one of an inertial measurement unit, lidar, radar, ultrasonic sensor, mono camera, stereo camera, wheel speed sensor, steering angle sensor, and gyroscope.

13. Computer system of any previous claims, wherein the processing circuitry is configured to determine that the vehicle is within the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone.

14. Computer system of any previous claims, wherein the processing circuitry is configured to predict a vehicle entrance in the at least one geographical zone based on the estimated vehicle position relative to the at least one geographical zone.

15. Computer system of any previous claims, wherein the processing circuitry is configured to determine a distance between the vehicle and a destination location (223) in the confined geographical area.

16. Computer system of claim 15, wherein the processing circuitry is configured to determine the distance from pre-recorded trajectories corresponding to roads within the confined geographical area.

17. A vehicle (10) comprising a computer system of any of the claims 1-16.

18. A computer-implemented method (300) for controlling an autonomous vehicle operation of an autonomous vehicle (10) within a confined geographical area (200), the method comprising:- receiving, by processing circuitry of a computer system, data indicative of one or more geographical zones within the confined geographical area, the one or more geographical zones having one or more operational restricting conditions;- determining, by the processing circuitry of the computer system, to use a relative positioning system in response to a detected low confidence in absolute positioning data from an absolute positioning system;- using, by the processing circuitry of the computer system, the relative positioning system for estimating a vehicle position relative to the at least one geographical zone; and- adapting, by the processing circuitry of the computer system, the operation of the vehicle based on the estimated vehicle position relative to the at least one geographical zone and the operational restricting conditions applying to the at least one geographical zone.

19. A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 18.

20. A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry, cause the processing circuitry to perform the method of claim 18.

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