Driving Skill Evaluation Segmentation for Lower Processing Load

The patent segments the evaluation items into two categories: simple evaluation items (first plurality) and detailed evaluation items (second plurality). This segmentation allows the system to process different amounts of data selectively - basic evaluations use minimal data while comprehensive evaluations can access detailed metrics, thereby maintaining design flexibility while enabling comprehensive assessment when needed.

The patent changes the parameter of data processing volume based on evaluation type. For simple evaluation items, only essential travel data is processed, while for detailed evaluation items, additional detailed data is processed. This dynamic parameter adjustment reduces average processing load while preserving the capability for comprehensive evaluation when required.

The patent implements partial action by selectively processing and outputting evaluation comments based on what is necessary for effective guidance. Not all evaluation items are processed to the same depth - simple items receive basic evaluation while detailed items receive comprehensive analysis only when needed. This partial processing approach maintains guidance effectiveness while reducing overall data processing load.

Different evaluation items receive different levels of processing quality and detail. Simple evaluation items are processed with basic data while detailed evaluation items can access comprehensive data when needed. This local quality differentiation ensures that guidance is effective for each item's purpose without uniformly processing all items at maximum detail, thereby reducing total processing load.