The disclosure belongs to the technical field of autonomous vehicle, in particular to an automatic driving acceleration test method considering efficiency and coverage, which includes the following steps. Step 1 is definition of scenario test priority. Step 2 is zone division. Step 3 is search within zones. Step 4 is update of scenario test priorities. Step 5 is iterative test. After selecting the automatic driving function to be tested and setting the parameters of the vehicle operation zone, the scenario generation range is formed. The coverage of the test scenario is improved by dividing the generated range and setting the freedom of early autonomous driving exploration. The efficiency of the test process is improved by continuously improving the probability of generating dangerous scenarios in the test process. Thus, it is ensured that the generated test scenarios take into account both test efficiency and test coverage.

To identify the sweet spot for criteria attributes (i.e., variables) within a complex system, a data source having objectively acceptable values or ranges of values for the criteria attributes for each variant of the system is generated. The identification system used to analyze the complex system to identify the sweet spot receives measurement values from a testing system that measures values of the criteria attributes from variants of the complex system and provides the measurement values to the identification system. The criteria attributes may be prioritized for determination of the sweet spot, including a selection of a value or range of values that are to be used for the most highly prioritized criteria attribute. The prioritized criteria attributes and objectively acceptable values can be used to filter the measurement values to identify the sweet spot for the variants of the complex system.

A method and apparatus for calibrating a projection axis orientation for an optical projector associated with a vehicle inspection or service system so as to enable projection of indicia onto selected spatial locations within a vehicle service area. Projector axis orientations required for the projection of visible indicia onto reference targets disposed at determinable locations within a common coordinate system of the vehicle service area are utilized to establish a relationship utilized to mathematically transform between selected spatial coordinate locations for projected indicia and corresponding orientations of the projection axis, facilitating projection of the visible indicia to additional spatial coordinate locations within the common coordinate system.

A fault diagnosis device 80 includes an input unit 81 and a generation unit 82. The input unit 81 receives input of fault data obtained from a vehicle when a fault of the vehicle occurs and observation data observed in time series by each device of the vehicle until immediately before the fault occurs. The generation unit 82 generates a feature master that associates a content of the fault indicated by the fault data with features extracted from the corresponding observation data.

System for automatically classifying vehicle vocation and benchmarking vehicle performance relative to other vehicles having the same vocation classification, independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings, is disclosed. The system includes a vehicle vocation classifier in communication with a data management system to store historical vehicle data including recurring vehicle usage data, and assign one or more predicted vocations for each vehicle based on the recurring vehicle usage data using a machine learning technique. The system also includes a benchmarking management system for grouping the historical vehicle data for vehicles of same determined predicted vocation, determining therefrom benchmarking vehicles having better performance characteristics than other vehicles of the same determined predicted vocation, and benchmarking performance of the other predicted vocation vehicles relative to the benchmarking vehicles.

System for automatically classifying vehicle vocation and benchmarking vehicle performance relative to other vehicles having the same vocation classification, independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings, is disclosed. The system includes a vehicle vocation classifier in communication with a data management system to store historical vehicle data including recurring vehicle usage data, and assign one or more predicted vocations for each vehicle based on the recurring vehicle usage data using a machine learning technique. The system also includes a benchmarking management system for grouping the historical vehicle data for vehicles of same determined predicted vocation, determining therefrom benchmarking vehicles having better performance characteristics than other vehicles of the same determined predicted vocation, and benchmarking performance of the other predicted vocation vehicles relative to the benchmarking vehicles.

A system comprises a processor that is programmed to define a plurality of vehicle groups based on vehicle specification data and define a plurality of sub-groups for each of the vehicle groups based on environmental data and sensor data received from each of a plurality of vehicles. The processor is programmed to adjust fuel tank leak detection classifiers for the sub-groups based on ground truth data. The ground truth data include, for each of the plurality of vehicles, a leak detection status and a leak test result.

The application provides a method and an apparatus for testing an autonomous vehicle, and a storage medium, where the method includes: obtaining detection information of the autonomous vehicle, where the detection information is configured to indicate the test result obtained when the detecting apparatus in the autonomous vehicle tests the autonomous vehicle; further, generating a test interface according to the obtained detection information, and displaying the test interface, so that the tester can visually check various test information of the autonomous vehicle during the road running test, thereby not only saving a labor cost, but also improving a test efficiency of the road running test.

The present invention makes it possible to provide temperature traceability for a test vehicle. A vehicle control device controls temperature information for a test vehicle and includes a peripheral temperature acquisition unit that acquires a peripheral temperature of a test vehicle from a first temperature sensor that is provided in a soak chamber where the test vehicle is stored or in a test chamber where the test vehicle is tested, a position information acquisition unit that acquires position information for the test vehicle, and a recording unit that associates the peripheral temperature of the test vehicle with the position information for that test vehicle and records the association.

The present invention makes it possible to provide temperature traceability for a test vehicle. A vehicle control device controls temperature information for a test vehicle and includes a peripheral temperature acquisition unit that acquires a peripheral temperature of a test vehicle from a first temperature sensor that is provided in a soak chamber where the test vehicle is stored or in a test chamber where the test vehicle is tested, a position information acquisition unit that acquires position information for the test vehicle, and a recording unit that associates the peripheral temperature of the test vehicle with the position information for that test vehicle and records the association.