Vehicle Coverage Analysis by Road Class and Vehicle Type
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Solution Overview
Problem
Existing navigation systems struggle to provide accurate and real-time coverage analysis for autonomous vehicles, leading to safety risks and inefficiencies in traffic reporting.
Innovation Solution
A system and method for determining vehicle coverage by analyzing sensor data and vehicle type to generate accurate navigation instructions, using a processor to classify road function and vehicle type, and output notifications based on threshold comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If navigation systems rely on aggregated probe vehicle geolocation data and sensor data, then traffic information and incident information can be provided, but accurate coverage analysis for autonomous vehicles cannot be ensured
Solution Approach 1:
The patent segments coverage analysis by vehicle type (autonomous, semi-autonomous, manual) and road function class (highway, urban, rural). This segmentation allows the system to calculate coverage separately for each category, ensuring accurate coverage data for autonomous vehicles specifically, rather than losing it in aggregated general traffic data.
Solution Approach 2:
The patent changes the parameters of coverage calculation by introducing vehicle-type-specific coverage metrics and road-function-class-specific thresholds. Coverage is calculated as a ratio of autonomous vehicle miles to total vehicle miles for each road segment, with different threshold values applied based on road function class, enabling precise and reliable coverage analysis.
2Productivity
If existing methods aggregate probe vehicle data, then general traffic information can be obtained, but real-time coverage monitoring for autonomous vehicles is insufficient
Solution Approach 1:
The patent implements feedback mechanisms where coverage data is continuously calculated, compared against thresholds, and used to generate notifications. The system monitors coverage in real-time, compares it with predefined thresholds for different road types, and provides feedback through notifications when coverage is insufficient, enabling dynamic adjustment and reliable real-time monitoring.
Solution Approach 2:
The patent creates a universal coverage analysis system that handles multiple vehicle types and road function classes through a single integrated framework. The system can process coverage data for autonomous vehicles, semi-autonomous vehicles, and manual vehicles simultaneously, while applying appropriate thresholds for different road types, improving overall navigation service efficiency.
3Measurement precision
If coverage data is not accurately determined, then navigation instructions may be inaccurate, but implementing precise coverage analysis increases system complexity
Solution Approach 1:
The patent reduces system complexity through segmentation by dividing coverage analysis into discrete categories (vehicle types and road function classes). This segmentation allows the use of simple threshold comparisons for each segment rather than complex continuous analysis, achieving precise measurement through structured simplification.
Solution Approach 2:
The patent changes parameters to simplify the system by converting continuous coverage data into discrete threshold-based evaluations. Coverage ratios are calculated and compared against predefined threshold values for different road function classes, transforming a complex continuous measurement problem into a simpler discrete classification system while maintaining precision.
Data Source
AI summary
The disclosure provides a system, a method, and a computer program product for determining coverage of a vehicle. The system is configured to, for example, acquire sensor data and vehicle data from a user equipment. The sensor data is associated with a region including a plurality of roads. Further, the system is configured to determine a function class of each of the plurality of roads based on the sensor data. Further, the system is configured to determine a type of a vehicle associated with the user equipment, based on the vehicle data. The system is configured to further determine coverage data of the vehicle for each of the plurality of roads based on the function class of a respective road of the plurality of roads and the type of the vehicle. Further, a first notification associated with the coverage of the vehicle, is generated as output.