Method and system for vehicle analysis

A vehicle analysis system for analyzing vehicle diagnosis data generated by a vehicle, the system comprising one or more processors configured to:

• receive a first collection of vehicle diagnosis data, the vehicle diagnosis data comprising a plurality of different sets of digital data representing a plurality of different vehicle components comprised with the vehicle, wherein the different sets of digital data representing the plurality of different vehicle components are generated from a CAN bus information flow;
• perform a modeling of the first collection of vehicle diagnosis data by correlating at least a selected portion of the different sets of data comprised with the first collection of vehicle diagnosis data, wherein the modeling comprises applying a machine learning process to the selected portion of the different sets of digital data and wherein the selected portion of the different sets of digital data is identified from the first collection of vehicle diagnosis data by utilizing pattern recognition;
• form, based on the performed modeling, an indication of a status for a single one of the vehicle components comprised with the vehicle based on an identified pattern provided as an outcome of the pattern recognition, wherein the indication of the status for the single one of the vehicle components relates to an error relating to that vehicle component;
• determine a validity of the status for the single one of the vehicle components;
• and
• output the indication in combination with the validity of the status, wherein the validity comprises information stating if the indication is to be treated as reliable or unreliable.

A computer program product comprising a non-transitory computer readable medium having stored thereon computer program means for controlling a vehicle analysis system, wherein the computer program product comprises:

• code for receiving a first collection of vehicle diagnosis data, the vehicle diagnosis data comprising a plurality of different sets of digital data representing a plurality of different vehicle components comprised with the vehicle, wherein the different sets of digital data representing the plurality of different vehicle components are generated from a CAN bus information flow;
• code for performing a modeling of the first collection of vehicle diagnosis data by correlating at least a selected portion of the different sets of data comprised with the first collection of vehicle diagnosis data, wherein the modeling comprises applying a machine learning process to the selected portion of the different sets of digital data and wherein the selected portion of the different sets of digital data is identified from the first collection of vehicle diagnosis data by utilizing pattern recognition;
• code for forming, based on the performed modeling, an indication of a status for a single one of the vehicle components comprised with the vehicle based on an identified pattern provided as an outcome of the pattern recognition, wherein the indication of the status for the single one of the vehicle components relates to an error relating to that vehicle component;
• code for determining a validity of the status for the single one of the vehicle components;
• and
• code for outputting the indication in combination with the validity of the status, wherein the validity comprises information stating if the indication is to be treated as reliable or unreliable.