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1.发明公开公开(公告)号：US20240062553A1
公开(公告)日：2024-02-22
申请号：US18452045
申请日：2023-08-18
申请人： ZENSEACT AB
IPC分类号： G06V20/56 , G06V10/778 , G06V10/764
CPC分类号： G06V20/56 , G06V10/7792 , G06V10/764
摘要： A method for updating a perception function of a vehicle having an Automated Driving System (ADS) is disclosed. The ADS has a self-supervised machine-learning (ML) algorithm for reconstructing an ingested image and a ML algorithm for an in-vehicle perception module for detecting one or more objects or free-space areas depicted in an ingested image. At first, an image of a scene in a surrounding environment of the vehicle is obtained. The obtained image is processed to obtain an output image with one or more detected objects or free-space areas. Then, an evaluation dataset is formed accordingly. The evaluation dataset and the obtained image is processed to obtain a reconstruction error value for each evaluation image and an evaluation image with highest reconstruction error value is selected among plurality of evaluation images. Using the obtained image and the selected evaluation image, the ML algorithm for the in-vehicle perception module is updated.
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2.发明申请公开(公告)号：US20230090338A1
公开(公告)日：2023-03-23
申请号：US17947455
申请日：2022-09-19
申请人： ZENSEACT AB
摘要： 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.
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公开(公告)号：US20220350336A1
公开(公告)日：2022-11-03
申请号：US17729470
申请日：2022-04-26
申请人： Zenseact AB
摘要： 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.
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公开(公告)号：US20240140486A1
公开(公告)日：2024-05-02
申请号：US18495723
申请日：2023-10-26
申请人： ZENSEACT AB
IPC分类号： B60W60/00
CPC分类号： B60W60/0015
摘要： 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.
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5.发明公开公开(公告)号：US20230297845A1
公开(公告)日：2023-09-21
申请号：US18182629
申请日：2023-03-13
申请人： ZENSEACT AB
IPC分类号： G06N3/098 , G06N3/0895 , G05B13/04 , G05B13/02 , G06F8/65
CPC分类号： G06N3/098 , G06N3/0895 , G05B13/048 , G05B13/027 , G06F8/65 , B60W50/0098
摘要： A computer implemented method and related aspects for updating a perception function of a plurality of vehicles having an Automated Driving System (ADS) are disclosed. The method includes obtaining one or more locally updated model parameters of a self-supervised machine-learning algorithm from a plurality of remote vehicles, and updating one or more model parameters of a global self-supervised machine-learning algorithm based on the obtained one or more locally updated model parameters. Further, the method includes fine-tuning the global self-supervised machine-learning algorithm based on an annotated dataset in order to generate a fine-tuned global machine-learning algorithm comprising one or more fine-tuned model parameters. The method further includes forming a machine-learning algorithm for an in-vehicle perception module based on the fine-tuned global machine-learning algorithm, and transmitting one or more model parameters of the formed machine-learning algorithm for the in-vehicle perception module to the plurality of remote vehicles.
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公开(公告)号：US20220350338A1
公开(公告)日：2022-11-03
申请号：US17729447
申请日：2022-04-26
申请人： Zenseact AB
摘要： 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.
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公开(公告)号：US20230290199A1
公开(公告)日：2023-09-14
申请号：US18178730
申请日：2023-03-06
申请人： Zenseact AB
摘要： 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.
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公开(公告)号：US20230091986A1
公开(公告)日：2023-03-23
申请号：US17947441
申请日：2022-09-19
申请人： ZENSEACT AB
摘要： 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.
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公开(公告)号：US20230071569A1
公开(公告)日：2023-03-09
申请号：US17901127
申请日：2022-09-01
申请人： ZENSEACT AB
IPC分类号： B60W50/029 , B60W60/00
摘要： 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. Based on said retrieved data, determining whether there is an anomaly associated with said monitored operation; and taking at least one action of a set of predefined actions if an anomaly is determined.
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公开(公告)号：US20220371614A1
公开(公告)日：2022-11-24
申请号：US17741599
申请日：2022-05-11
申请人： Zenseact AB
摘要： 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.
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