Network System for Analyzing Driving Actions on Road Segments
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Solution Overview
Problem
Current systems lack the capability to effectively monitor and characterize driving actions of multiple vehicles across specific road segments in real-time, failing to provide comprehensive data aggregation and baseline establishment for driver performance evaluation.
Innovation Solution
A network computer system that receives and processes vehicle data from multiple vehicles, utilizing motion sensing components, GPS, and OBD data to determine and characterize driving actions, aggregate data, and establish baselines for driving behaviors, while also detecting distractions and correlating them with specific road segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle data from multiple vehicles is collected and processed in real-time, then driver performance evaluation capability is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the geographic region into multiple road segments and processes vehicle data separately for each segment. This allows the system to handle large volumes of data in manageable portions, reducing overall system complexity while maintaining comprehensive driver performance evaluation capabilities across the entire region.
Solution Approach 2:
The system implements baseline establishment through aggregated data from multiple vehicles, using partial data sets to create reference standards. This approach allows the system to progressively improve evaluation precision without requiring complete data from all vehicles simultaneously, thereby managing system complexity.
2Reliability
If real-time monitoring of multiple vehicles is implemented, then safety analysis capability is improved, but data aggregation and processing requirements increase
Solution Approach 1:
The system merges data from multiple vehicles traversing the same road segment to establish aggregated baselines for driving actions. By combining data across multiple sources and time periods, the system improves safety analysis reliability through more robust statistical foundations while managing data processing loads through systematic aggregation.
Solution Approach 2:
The system performs preliminary data aggregation and baseline establishment for road segments before conducting detailed driver performance evaluations. This pre-processing approach prepares reference data in advance, enabling more efficient real-time safety analysis without overwhelming processing requirements during active monitoring.
3Loss of information
If comprehensive vehicle data is collected for baseline establishment, then driver behavior characterization is improved, but data collection and storage requirements increase
Solution Approach 1:
The system applies local quality by establishing baselines specific to each road segment rather than using uniform standards across the entire geographic region. This approach characterizes driver behavior with higher precision by accounting for local driving conditions, while managing data requirements by processing information at the segment level rather than requiring all possible data combinations.
Data Source
AI summary
Examples include a network computer system and/or service which operates to remotely monitor vehicles to detect and characterize driving actions of drivers with respect to specific road segments of a roadway, enabling driving actions performed by multiple drivers at a specific road segment to be characterized and modeled. Models can inform municipalities about potential traffic hazards or other safety challenges. Individual drivers can also be measured against the model to help understand driver performance. Validating vehicle data against baseline values can also detect spoofing of that data.