Abstract: The present invention relates to methods and systems that utilize the production vehicles to develop new perception features related to new sensor hardware as well as new algorithms for existing sensors by using federated learning. To achieve this, the production vehicle's own worldview is post-processed and used as a reference, towards which the output of the software (SW) or hardware (HW) under development is compared. In case of a large discrepancy between the baseline worldview and perceived worldview by the module-under-test, the data is weakly annotated by the baseline worldview. Such weakly annotated data may subsequently be used to update the SW parameters of the “perception model” in the module-under-test in each individual vehicle, or to be transmitted to the “back-office” for off-board processing or more accurate annotations.

Abstract: A method for closed-loop evaluation of path planning modules for a vehicle equipped with an Automated Driving System (ADS) is disclosed. The method includes obtaining a candidate path from each of a plurality of path planning modules of the ADS. The method further includes determining a fulfilment of convergence criteria by the obtained candidate paths by comparing the obtained candidate paths with each other and determining a level of convergence between the candidate paths. If the convergence criteria is fulfilled, one of the obtained candidate paths is selected and the vehicle is controlled so to execute the selected candidate path. If the convergence criteria is not fulfilled, determining an exposure need of each path planning module in view of a predicted scene or scenario in the surrounding environment of the vehicle that the vehicle is expected to be exposed to while executing any one of the obtained candidate paths.

Abstract: Method and device for supporting generation of scenarios for testing autonomous driving and/or advanced driver assistance system, AD/ADAS, functionality for real world vehicles. A device (101; 500) provides (301) a virtual environment (200) simulating an environment relevant for operation of vehicles having said AD/ADAS functionality and in which is operating: fully computer controlled movable virtual objects (230a-c), human controlled movable virtual objects (220) and at least one virtual AD/ADAS vehicle (210) operating according to said AD/ADAS functionality. The device allows (303) a user of the device (101; 500) to, via user interface (506), control said one or more human controlled movable virtual objects (220) during operation and thereby cause generation of scenarios that the virtual AD/ADAS vehicle (210) is subjected to.

Abstract: An assessment system for performance evaluation and updating of a PMUD of an ego-vehicle. The assessment system obtains world view data from a perception module configured to generate the world view data based on sensor data obtained from vehicle-mounted sensors; obtains other world view data generated by another perception module; forms a joint world view by matching the world view data the other world view data; and obtains perception data based on a perception model and sensor data obtained from one or more vehicle-mounted sensors. The assessment system further matches the perception data to the formed joint world view; evaluates the obtained perception data in reference to the joint world view to determine an estimation deviation in an identified match between the perceptive parameter of the perception data and a corresponding perceptive parameter in the joint world view; and updates parameters of the perception model based on the estimation deviation.

Abstract: The present disclosure relates to a method for augmenting capabilities of an Automated Driving System (ADS) of a vehicle. The method includes locally processing, by means of a perception module of the ADS, sensor data obtained from one or more sensors of the vehicle in order to generate a local world-view of the ADS, wherein the sensor data includes information about a surrounding environment of the vehicle. The method further includes transmitting sensor data including information about the surrounding environment of the vehicle to a remote system, and receiving off-board processed data from the remote system, the off-board processed data being indicative of a supplementary world-view of the ADS. Furthermore, the method includes forming an augmented world-view of the ADS based on the generated local world-view and the supplementary world-view.

Abstract: The present disclosure relates to a method for augmenting capabilities of an Automated Driving System (ADS) of a vehicle. The method includes locally processing, by means of a perception module of the ADS, sensor data obtained from one or more sensors of the vehicle in order to generate a local world-view of the ADS. The sensor data is associated with a time period and includes information about a surrounding environment of the vehicle during the time period. The method further includes generating a local candidate path to be executed by the ADS based on the generated local world-view of the ADS, and transmitting a first set of data to a remote system. The first set of data is associated with the time period and including information about the surrounding environment of the vehicle during the time period.

Abstract: A method performed by a locations mapping system for supporting identifying locations crucial to a vehicle equipped with an Automated Driving System, ADS. The locations mapping system obtains data of crucial locations of past vehicle situations identified as critical and/or challenging; extracts from the crucial locations data, for at least a first past vehicle situation, static road features and operating conditions pertaining to the at least first past vehicle situation; identifies road segments exhibiting road features to a predeterminable extent matching the static road features pertaining to the at least first past vehicle situation; and generates a mapping associating the identified road segments with said operating conditions. The disclosure also relates to a locations mapping system in accordance with the foregoing, an arrangement, e.g., an offboard system and/or a vehicle comprising such a locations mapping system, and a respective corresponding non-volatile computer readable storage medium.

Abstract: The present disclosure relates to a method performed by a buffer resources prioritizing system for storage prioritization in an event buffer configured to continuously collect operational data of an Automated Driving System, ADS, of a vehicle. The buffer resources prioritizing system obtains sensor data of one or more sensors onboard the vehicle. The buffer resources prioritizing system further determines, at least partly based on the sensor data, current ADS-related operational conditions at least comprising states of vehicle surroundings and internal states of the vehicle. Moreover, the buffer resources prioritizing system determines an upcoming scene predicted to evolve from the current operational conditions. Furthermore, the buffer resources prioritizing system deduces based on assessment of the predicted scene, a storage priority score thereof reflecting predicted relevance of freezing event data of the predicted scene in the event buffer.

Abstract: A method performed by a buffer segment length adjusting system for dynamically adjusting an event segment length of data stored in an event recording buffer of an Automated Driving System, ADS, of a vehicle. The buffer segment length adjusting system obtains sensor data of one or more sensors onboard the vehicle. The buffer segment length adjusting system further identifies, upon the sensor data rendering fulfilment – and/or a state of a software of the ADS rendering fulfilment – of event recording triggering criteria, conditions of a triggering event underlying the fulfilment. The buffer segment length adjusting system determines at least a first current ADS-related operational condition. The buffer segment length adjusting system sets a respective start time point and end time point of - e.g. an event segment length of - the event recording buffer based on the triggering event conditions and the at least first current ADS-related operational condition.

Abstract: An apparatus and method performed by a perception comparing system of a vehicle for perception performance evaluation of an ADAS or ADS. The perception comparing system establishes communication with a secondary vehicle determined and/or estimated to be positioned within a potential range of surrounding detecting sensors on-board the vehicle. The system derives perception data from a perception system of the ADAS or ADS. The system receives secondary perception data from a secondary perception system of a secondary ADAS or ADS of the secondary vehicle and determines a discrepancy output based on comparison of at least a portion of the both of perception data and the secondary perception data. The system communicates acknowledgement data when at least a portion of the discrepancy output fulfils discrepancy exceedance criteria and/or when the vehicle is perceivable in the secondary perception data but the secondary vehicle not is locatable in the perception data.

Abstract: An image frames handling system for reconstruction of image frames obtained by an image capturing device of an Automated Driving System, ADS, of a vehicle at an entity. The image system stores in a surrounding state data buffer obtained object-level environmental data indicating states of vehicle surroundings derived from perception data output from an onboard perception system; stores image frames of vehicle surroundings captured by the capturing device in an image data buffer; processes the image data buffer to determine motions of objects in the image frames and respective values of the motions; extracts key image frames from the image data buffer and pixels having motion values exceeding a predeterminable level from non-key image frames of the image data buffer; transfers the extracted key image frames and the extracted pixels; and reconstructs at the entity interpolated image frames at the predeterminable frame rate based on the selected data.

Abstract: The present disclosure relates to a method, system, a vehicle and a computer-readable storage medium. The method comprises determining a fulfilment of a set of predefined Operational Design Domain (ODD) conditions for an Automated Driving System (ADS) feature of an ego-vehicle at least partly based on sensor data obtained from on-board sensors of the ego-vehicle and determining a first ODD exit boundary along an estimated route to be travelled by the ego-vehicle. The method further comprises obtaining data from at least one external vehicle located on the estimated route to be travelled by the ego-vehicle. Further, the method comprises evaluating the obtained data from the at least one external vehicle against an ODD assessment scheme to determine a fulfilment of the predefined ODD conditions in the surrounding environment of the external vehicle and determining a second ODD exit boundary along the estimated route of the ego-vehicle based on the evaluation.

Abstract: The present invention relates to methods and systems for prioritized activation of sensor hardware of a vehicle for development, evaluation, and/or testing of ADS features. The method comprises obtaining data indicative of a set of platform constraints of the vehicle, set of requirements for each of a plurality of ADS features, and a priority scheme for the plurality of ADS features. The method further comprises obtaining data indicative of a predicted scene or scenario in the surrounding environment of the vehicle that the vehicle is expected to be exposed to at a future moment in time. Then, the method comprises generating, based on the platform constraints, the set of requirements, the priority scheme and the predicted scene or scenario, an arbitration signal indicative of a sensor hardware activation and a resource allocation of the platform of the vehicle for at least one of the plurality of ADS features.

Abstract: The present invention relates to methods and systems for allocating platform resources in a vehicle for development, evaluation, and/or testing of ADS features. The method comprises storing, during a time period, sensor data indicative of a surrounding environment of the vehicle in a data storage device of the vehicle, and obtaining data indicative of a set of platform constraints of the vehicle, a set of requirements for each of a plurality of ADS features, a priority scheme for the plurality of ADS features, and a current scene or scenario in the surrounding environment of the vehicle. Furthermore, the method comprises generating, based on the platform constraints, the set of requirements, the priority scheme and the current scene or scenario, an arbitration signal indicative of a resource allocation of the platform of the vehicle to at least one of the plurality of ADS features.

Abstract: The present disclosure describes a method for monitoring operations of an automated driving system (ADS) of a vehicle. For each monitored operation the method includes: determining a geographical position of the vehicle; determining an intended path of the vehicle; and determining one or more intended parameters associated with performing a driving manoeuvre of said vehicle from the determined geographical position along the intended path. For each monitored operation the method further includes: obtaining one or more parameters associated with performing the driving manoeuvre of said vehicle from said determined geographical position; and retrieving, from a statistical model, data indicative of a statistical distribution related to one or more corresponding intended and/or obtained parameters for said intended path.

Abstract: An assessment system for performance evaluation and updating of a PMUD of an ego-vehicle. The assessment system obtains world view data from a perception module configured to generate the world view data based on sensor data obtained from vehicle-mounted sensors; obtains other world view data generated by another perception module; forms a joint world view by matching the world view data the other world view data; and obtains perception data based on a perception model and sensor data obtained from one or more vehicle-mounted sensors. The assessment system further matches the perception data to the formed joint world view; evaluates the obtained perception data in reference to the joint world view to determine an estimation deviation in an identified match between the perceptive parameter of the perception data and a corresponding perceptive parameter in the joint world view; and updates parameters of the perception model based on the estimation deviation.

Abstract: The present invention relates to a method and apparatus that utilize production vehicles to develop new path planning features for Automated Driving Systems (ADSs) by using federated learning. To achieve this the “under-test” path planning module's output is evaluated in open-loop in order to produce a cost-function that is subsequently used to update or train a path planning model of the path planning module.

Abstract: The present invention relates to a method and apparatus that utilize production vehicles to develop new path planning features for Automated Driving Systems (ADSs) by using federated learning. To achieve this the “under-test” path planning module's output is evaluated in closed-loop in order to produce a cost-function that is subsequently used to update or train a path planning model of the path planning development-module.

Abstract: A test-optimizing system for supporting shadow mode testing of ADS software included in an ADS-provided vehicle. One or more potential vehicle routes are retrieved. A geographical area covering the one or more potential vehicle routes is obtained and data of crucial locations associated with past vehicle situations identified as critical and/or challenging. Moreover, the test-optimizing system retrieves respective ODD for one or more candidate software respectively adapted to run in the background of the vehicle. ODD-compliant locations for respective candidate software are determined, by identifying locations out of the data of crucial locations lying within respective candidate software's ODD. At least a first test-compliant location along at least a first route out of the one or more potential vehicle routes is determined by identifying for at least a first candidate software, locations out of the ODD-compliant locations situated along the at least first route.

Abstract: A computer-implemented method and related aspects for detecting and collecting accident-related driving data on a vehicle are included. The method includes receiving a driving experience data stream from a source on-board the vehicle, determining an accident similarity score for a data segment of the driving experience data stream, wherein the accident similarity score is based on a similarity measurement of data features extracted from the data segment to data features of a historic accident or near-accident driving experience event, determining a criticality score for the data segment, and storing, in dependence on at least one of the determined accident similarity score and the determined criticality score, at least the extracted data features from the data segment as an accident-related driving experience event in association with at least the determined criticality score.