Roadway Analysis Index Using Traffic Light Density and Speed Variation
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Solution Overview
Problem
Existing navigation and black box systems fail to provide comprehensive driving analysis that accounts for road and traffic conditions, limiting their ability to accurately assess driving habits and patterns, and thus are unsuitable for setting routes that consider safety, economic efficiency, and environmental impact.
Innovation Solution
A method and apparatus that calculate an analysis index for a roadway section by synthesizing traffic light density, road shape information, and speed variation using GPS and sensor data, providing a differentiated analysis based on actual conditions to evaluate driving efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional driving evaluation information is provided based only on fuel efficiency and basic driving data, then the system complexity remains low, but the measurement precision of driving habits and road conditions is insufficient
Solution Approach 1:
The patent combines multiple data sources including GPS location data, map data, vehicle sensor data (acceleration, steering angle, brake pressure), and traffic information into a unified driving evaluation system. This integration enables comprehensive analysis of driving habits by synthesizing data from previously separate systems, thereby improving measurement precision without proportionally increasing device complexity.
Solution Approach 2:
The navigation device is enhanced to perform multiple functions: traditional navigation guidance, driving habit analysis, road condition evaluation, and route optimization. By making the device universal, the patent avoids adding separate dedicated systems, thus improving measurement capabilities while controlling overall system complexity through multi-functional integration.
2Loss of information
If simple driving information is provided by navigation devices, then the device complexity is low, but the information completeness for route setting is insufficient
Solution Approach 1:
The patent segments driving information into multiple categories: basic driving data (speed, acceleration), vehicle state data (steering angle, brake pressure), environmental data (road gradient, curvature), and traffic data. This segmentation allows comprehensive information collection while organizing data systematically, reducing the complexity burden by structured information management.
Solution Approach 2:
The patent adds new dimensions to traditional navigation by incorporating temporal patterns (driving behavior over time), spatial patterns (route-specific characteristics), and contextual dimensions (road conditions, traffic conditions). This multi-dimensional approach provides complete driving condition information while using advanced data processing techniques to manage the increased information complexity.
3Reliability
If driving evaluation is performed without considering road and traffic conditions, then the calculation process is simple, but the reliability of route setting is insufficient
Solution Approach 1:
The patent implements feedback mechanisms where driving evaluation results are continuously updated based on actual road conditions and traffic patterns. The system compares expected driving behavior with actual performance, adjusts evaluation criteria based on road-specific characteristics, and refines route recommendations over time. This feedback loop enhances reliability by ensuring evaluations reflect actual conditions while using iterative processing to manage calculation complexity.
Solution Approach 2:
The patent dynamically adjusts evaluation parameters based on road conditions (gradient, curvature, surface type) and traffic conditions (density, speed, incidents). By changing parameters according to contextual factors, the system achieves reliable route setting that adapts to varying conditions. Advanced algorithms process these dynamic parameter changes efficiently, balancing reliability improvement with computational complexity management.
Data Source
AI summary
Provided is an apparatus and method for providing an analysis index of a roadway section based on road and traffic conditions. The method may include calculating a traffic light density of a roadway section using a number of traffic lights installed in the roadway section, calculating road shape information based on at least one of a curvature and a gradient of the roadway section, calculating a speed variation of the roadway section using a change of speed in the roadway section, and calculating an analysis index of the roadway section using the traffic light density, the road shape information, and the speed variation.