Vehicle operation and/or simulation based on decision registry

    公开(公告)号:US12131599B1

    公开(公告)日:2024-10-29

    申请号:US17538809

    申请日:2021-11-30

    申请人: Zoox, Inc.

    摘要: Tracking component decisions may comprise generating a data structure in association with an output determined by a component. This data structure, along with one or more data structures generated in association with other outputs generated by the same or different components of the vehicle, may be used to determine a trace that identifies component(s) that determined outputs that affected a particular component's generation of an output. The data structures and/or traces may be used to determine whether a component is the source of an error, a portion of the component that is the source of the error, unintended impacts to unmodified portions of components, among additional or alternate uses discussed herein.

    Multi-scan sensor fusion for object tracking

    公开(公告)号:US12123945B2

    公开(公告)日:2024-10-22

    申请号:US17651420

    申请日:2022-02-16

    发明人: Bin Jia Xiaohui Wang

    摘要: This document describes techniques, systems, and methods for multi-scan sensor fusion for object tracking. A sensor-fusion system can obtain radar tracks and vision tracks generated for an environment of a vehicle. The sensor-fusion system maintains sets of hypotheses for associations between the vision tracks and the radar tracks based on multiple scans of radar data and vision data. The set of hypotheses include mass values for the associations. The sensor-fusion system determines a probability value for each hypothesis. Based on the probability value, matches between radar tracks and vision tracks are determined. The sensor-fusion system then outputs the matches to a semi-autonomous or autonomous driving system to control operation of the vehicle. In this way, the described techniques, systems, and methods can provide high-precision object tracking with quantifiable uncertainty.