Abstract: The disclosure describes an autotuning framework for tuning an image signal processing (ISP) module of an autonomous driving vehicle (ADV). The autotuning framework can generate different sets of parameter values using a variety of optimization algorithms to configure the ISP module. Each processed image generated by the ISP module configured with the different sets of parameter values is compared by an ISP module testing device with a reference image stored therein to generate an objective core measuring one or more differences between each of the processed images and the reference image. The objective scores and the corresponding sets of parameter values are stored in a database. Different sets of optimal parameter values for different environments can be selected from the database, and uploaded to a cloud database for use by an ADV, which can select a different set of ISP parameter values based on an environment that the ADV is travelling in.

Abstract: In one embodiment, a system configures an image signal processor (ISP) of an autonomous driving vehicle (ADV) with a first set of ISP configuration parameters, where the ISP is used to process raw image data of an image sensor of the ADV based on the first set of ISP configuration parameters. The system determines whether one or more criteria is satisfied, where the one or more criteria corresponds to an expected change in a characteristic of ambient light being perceived by the image sensor of the ADV. In response to determining that the one or more criteria is satisfied, the system configures the ISP of the ADV with a second set of ISP configuration parameters, where the ISP is used to apply an image processing algorithm to raw image data based on the second set of ISP configuration parameters to generate an image.

Abstract: In one embodiment, a system generates an image using either a first or a second image signal processing (ISP) algorithm, where the first or second ISP algorithm is applied to raw image data of a camera of an autonomous driving vehicle (ADV) to generate the image. The system applies a machine learning model to the image to identify a representation of an obstacle, where the machine learning model is generated by a few shots learning algorithm that contrasts labeled data of a positive training sample from images corresponding to the first and second ISP algorithms to labeled data of a negative training sample from images corresponding to the first and second ISP algorithm. The system determines a classification and a location of the obstacle based on the representation of the obstacle. The system plans a motion control of the ADV based on the classification and location of the detected object.

Abstract: A data processing circuit and a fault-mitigating method are provided. In the method, multiple sub-sequences are divided from sequence data. A first sub-sequence of the sub-sequences is accessed from a memory for a multiply-accumulate (MAC) operation to obtain a first computed result. The MAC operation is performed on a second sub-sequence of the sub-sequences in the memory to obtain a second computed result. The first and the second computed results are combined, where the combined result of the first and the second computed results is related to the result of the MAC operation on the sequence data directly. Accordingly, the error rate could be reduced, so as to mitigate fault.

Abstract: A sound signal generator testing apparatus is provided. The apparatus includes a hermetic seal (2), a sound signal input unit (4), and at least a noise suppression unit (5). The sound signal input unit is for receiving sound signals transmitted from a sound signal generator (1) under testing. Each noise suppression unit includes a sound signal input unit, a low pass filter, an inverter, and an output. The sound signal input unit is for receiving sound signals. The low pass filter is for filtering the sound signals by passing the low frequencies of the sound signals that are below a predetermined value. The inverter is for inverting phases of the sound signals transmitted from the low pass filter and producing inverted sound signals. The output unit is placed behind the sound signal input unit for outputting the inverted sound signals.

Abstract: A sound signal generator testing apparatus is provided. The apparatus includes a hermetic seal (2), a sound signal input unit (4), and at least a noise suppression unit (5). The sound signal input unit is for receiving sound signals transmitted from a sound signal generator (1) under testing. Each noise suppression unit includes a sound signal input unit, a low pass filter, an inverter, and an output. The sound signal input unit is for receiving sound signals. The low pass filter is for filtering the sound signals by passing the low frequencies of the sound signals that are below a predetermined value. The inverter is for inverting phases of the sound signals transmitted from the low pass filter and producing inverted sound signals. The output unit is placed behind the sound signal input unit for outputting the inverted sound signals.