Abstract: The present disclosure provides a signal machine alarm method and apparatus, an electronic device and a readable storage medium, and relates to the field of intelligent transportation technologies. The signal machine alarm method, including: acquiring a light-state data stream of a signal machine; determining a target light-state data frame corresponding to a current time according to the light-state data stream; acquiring a timing scheme of the signal machine at the current time; extracting target light-state information of a target phase from the target light-state data frame; and obtaining a calculation countdown according to the timing scheme, the target light color state and the target cycle countdown, and sending alarm information if the calculation countdown is determined to be inconsistent with the target light color countdown.

Abstract: Embodiments of the present disclosure provide a method for processing vehicle driving mode switching, a vehicle and a server. The method includes: determining (S103) a target switching reason upon detecting that a driving mode of a vehicle is switched from unmanned driving to manned driving; acquiring (S104) status information and/or traveling environment information of the vehicle corresponding to the target switching reason; and sending the status information and/or the traveling environment information, and the target switching reason to a server, to enable the server to analyze the target switching reason, and improve the automatic driving system continuously according to the analysis result.

Abstract: The present disclosure provides an intelligent transportation road network acquisition method and apparatus, an electronic device and a storage medium, and relates to the field of artificial intelligence such as intelligent transportation. The method includes: acquiring a target demand set; acquiring annotation information, the annotation information being microscopic road network attribute information manually annotated on a displayed map road network for intersections in the target demand set; acquiring macroscopic road network information corresponding to the target demand set from road network data corresponding to the map road network; and generating an intelligent transportation road network corresponding to the target demand set according to the annotation information and the macroscopic road network information.

Abstract: The present disclosure provides a signal machine alarm method and apparatus, an electronic device and a readable storage medium, and relates to the field of intelligent transportation technologies. The signal machine alarm method, including: acquiring a light-state data stream of a signal machine; determining a target light-state data frame corresponding to a current time according to the light-state data stream; acquiring a timing scheme of the signal machine at the current time; extracting target light-state information of a target phase from the target light-state data frame; and obtaining a calculation countdown according to the timing scheme, the target light color state and the target cycle countdown, and sending alarm information if the calculation countdown is determined to be inconsistent with the target light color countdown.

Abstract: The present disclosure provides a data processing method and apparatus, an electronic device and a readable storage medium, and relates to the field of intelligent transportation technologies. The data processing method includes: acquiring a light-state data stream of a signal machine, the light-state data stream including a plurality of light-state data frames arranged in chronological order; determining a target light-state data frame in the light-state data stream and a target time of the target light-state data frame; acquiring a timing scheme of the signal machine; and generating, according to the timing scheme and the target light-state data frame, at least one light-state data frame at a time before and/or after the target time.

Abstract: The present disclosure provides an intelligent transportation road network acquisition method and apparatus, an electronic device and a storage medium, and relates to the field of artificial intelligence such as intelligent transportation. The method includes: acquiring a target demand set; acquiring annotation information, the annotation information being microscopic road network attribute information manually annotated on a displayed map road network for intersections in the target demand set; acquiring macroscopic road network information corresponding to the target demand set from road network data corresponding to the map road network; and generating an intelligent transportation road network corresponding to the target demand set according to the annotation information and the macroscopic road network information.

Abstract: A method of determining a state of an intersection, an electronic device and a storage medium, which relate to a field of an artificial intelligence technology, in particular to fields of an intelligent transportation technology, a computer vision technology, and a machine learning technology. The intersection is formed by a convergence of a plurality of road segments including at least two driving-in road segments. The method includes: determining attribute data and traffic data of each of the at least two driving-in road segments; determining a congestion parameter of each driving-in road segment based on the attribute data and the traffic data; determining a state of each driving-in road segment by using the congestion parameter of each driving-in road segment as an input of a predetermined multi-classification model; and determining the state of the intersection based on the states of the at least two driving-in road segments.

Abstract: A method of determining a state of an intersection, an electronic device, and a storage medium, which relate to a field of artificial intelligence technology, and in particular to fields of intelligent transportation technology and computer vision technology. The intersection is formed by a convergence of a plurality of road segments including at least two driving-in road segments, and each driving-in road segment includes at least one sub road segment. The method includes: determining attribute data and traffic data of each sub road segment of each driving-in road segment; determining a traffic condition information of each driving-in road segment based on the attribute data and the traffic data; and determining the state of the intersection based on the traffic condition information of the at least two driving-in road segments.

Abstract: A method and apparatus for controlling an autonomous vehicle. The method may include: acquiring vehicle traveling environment information; determining an intended traveling state of the autonomous vehicle based on the vehicle traveling environment information; and in response to detecting an interactive operation of a target user for the intended traveling state, generating a traveling state adjustment instruction corresponding to the interactive operation to control the autonomous vehicle to adjust a traveling state.

Abstract: Embodiments of the present disclosure provide a method for processing vehicle driving mode switching, a vehicle and a server. The method includes: determining (S103) a target switching reason upon detecting that a driving mode of a vehicle is switched from unmanned driving to manned driving; acquiring (S104) status information and/or traveling environment information of the vehicle corresponding to the target switching reason; and sending the status information and/or the traveling environment information, and the target switching reason to a server, to enable the server to analyze the target switching reason, and improve the automatic driving system continuously according to the analysis result.

Abstract: An obstacle avoidance method and apparatus for an autonomous driving vehicle is provided. The method includes: in response to determining that there is an obstacle in a preset driving path, sending obstacle information to a preset terminal device so that the preset terminal device displays the obstacle information in a display page thereof, the obstacle information including an image of the obstacle and location information; receiving obstacle category information sent by the preset terminal device and inputted according to the displayed obstacle information; and determining an obstacle avoidance instruction for the autonomous driving vehicle according to the obstacle category indicated by the category information.