Abstract: Embodiments of the present disclosure relate to the technical field of autonomous driving, and in particular to methods for updating an autonomous driving system, autonomous driving systems, and on-board apparatuses. In the embodiments of the present disclosure, the autonomous driving system, in a manual driving mode, senses the surrounding environment of a vehicle, performs vehicle positioning, and plans a path for autonomous driving for the vehicle. However, the autonomous driving system does not issue an instruction to control the driving of the vehicle. Instead, it compares the path with a path along which a driver drives the vehicle in the manual driving mode to update a planning and control algorithm of the autonomous driving system. As such, the updated autonomous driving system better caters to the driving habits of the driver and improves the driving experience for the driver without compromising the reliability of planning and decision-making of autonomous driving.

Abstract: According to some aspects of the present disclosure, a method for loading a visual localization map is provided. The method may include: localizing a current pose; predicting, based on the current pose, a set of group numbers to be loaded for the visual localization map, wherein each group number in the set of group numbers to be loaded corresponds to a sub-map file of the visual localization map, wherein the visual localization map includes a master map file and a plurality of sub-map files, wherein the plurality of sub-map files respectively store map data of corresponding groups obtained by grouping the visual localization map based on key frames, and wherein key frame index information for indexing the plurality of sub-map files is stored in the master map file; and loading corresponding sub-map files based on the group numbers in the set of group numbers to be loaded.

Abstract: The present disclosure provides methods, apparatuses, and storage media for storing and loading visual localization maps. The methods for storing the visual localization maps may include acquiring a visual localization map; extracting key frame abstract information of each key frame from the visual localization map; grouping the key frame abstract information of all key frames of the visual localization map; for each group, generating and storing a sub-map-file of the group using the key frame abstract information of the group; generating key frame space index information based on the key frame abstract information of all groups; and generating and storing a master map file according to the key frame space index information for indexing the sub-map-file.

Abstract: A method for controlling traffic lights and a traffic light system using such method are provided. The method comprises: a receiving apparatus acquires a vehicle classification of a target vehicle (410), and then determines whether to turn green for a vehicle arriving at a traffic light, according to the vehicle classification (420). Due to a low network delay and high data transmission rate requirement, although applicable in a 4G network environment, the disclosed technology is more suitable for a 5G network environment.

Abstract: A method for controlling traffic lights and a traffic light system using such method are provided. The method comprises: a receiving apparatus acquires a vehicle classification of a target vehicle (410), and then determines whether to turn green for a vehicle arriving at a traffic light, according to the vehicle classification (420). Due to a low network delay and high data transmission rate requirement, although applicable in a 4G network environment, the disclosed technology is more suitable for a 5G network environment.

Abstract: The present disclosure provides an apparatus and method for positioning, and particularly, for data processing resource allocation positioning. The method includes determining a current system state of a system and allocating data processing resources of a data processing device based on the current system state. The system state may be determined based on operation conditions of positioning sensors of the system. The system state may correspond to one or more lifespan parameters. The method may enable allocation of limited computing resources to sensor data analysis models corresponding to positioning sensors in good operation conditions. Therefore, positioning can be performed accurately and efficiently.