Abstract: An isolated inter-pole voltage self-balancing circuit based on an L-type current-input configuration is provided. The circuit includes one input voltage source uin, two field-effect transistors S1 and S2, two inductors L1 and L2, one transformer T, four switching diodes D11, D12, D21, and D22, four capacitors C1, C2, Cp, and CN, and bipolar loads Rp and RN. The circuit employs an L-type current-input topology with interleaved control, such that currents flowing through the input inductors L1 and L2 are interleaved and complementary, thereby effectively reducing input current ripple. A bipolar voltage-doubling unit is utilized to compensate for inter-pole voltage deviation caused by unbalanced loads, thereby achieving automatic inter-pole voltage self-balancing. The circuit does not rely on detection of voltage imbalance and does not require complex sampling or control algorithms, thus reducing design complexity.

Abstract: A method and a computing device for object detection and tracking from a video input are described. The method and the computing device may be used to, for example, track objects of interest, such as lane markings, in traffic. A plurality of frames corresponding to a video may be analyzed in a spatiotemporal domain by a neural network. The neural network may be trained using data synthesized in the spatiotemporal domain.

Abstract: A vehicle control method includes obtaining sensor status information and autonomous driving function information, where the sensor status information includes information indicating that one or more sensors are in a failed state. The autonomous driving function information indicates a currently running autonomous driving function. The autonomous driving function includes a plurality of running conditions, and implementation of each running condition is related to one or more sub-functions. A driving policy is implemented based on the impact of a failure of the one or more sensors on the running condition and the currently running autonomous driving function.

Abstract: A self-driving safety evaluation method, including determining RB based on a risk value of a vehicle in a shadow driving mode in a first measurement unit, where RB is a risk value of the vehicle in the shadow driving mode in a plurality of measurement units, and determining RC based on a risk value of the vehicle in a self-driving mode based on a preset route in the first measurement unit, where RC is a risk value of the vehicle in the self-driving mode based on the preset route in the measurement units, where RB and RC are used to determine whether safety of the vehicle in the self-driving mode meets a requirement.

Abstract: A method and a computing device for object detection and tracking from a video input are described. The method and the computing device may be used to, for example, track objects of interest, such as lane markings, in traffic. A plurality of frames corresponding to a video may be analyzed in a spatiotemporal domain by a neural network. The neural network may be trained using data synthesized in the spatiotemporal domain.

Abstract: This application discloses a method for determining a lane line recognition abnormal event, and a lane line recognition apparatus and system. One example method includes: determining an updated lane line recognition confidence based on a posteriori lane line recognition result; constructing a lane line true value based on the updated lane line recognition confidence; and determining a lane line recognition abnormal event based on the lane line recognition result and the lane line true value.

Abstract: A self-driving safety evaluation method, including determining RB based on a risk value of a vehicle in a shadow driving mode in a first measurement unit, where RB is a risk value of the vehicle in the shadow driving mode in a plurality of measurement units, and determining RC based on a risk value of the vehicle in a self-driving mode based on a preset route in the first measurement unit, where RC is a risk value of the vehicle in the self-driving mode based on the preset route in the measurement units, where RB and RC are used to determine whether safety of the vehicle in the self-driving mode meets a requirement.