Road Segment Ranking via Incident Trend Analysis
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Solution Overview
Problem
Current navigation systems do not provide users with adequate information about the safety and danger levels of road segments, leading to unaware selection of potentially hazardous routes, which can increase the likelihood of accidents.
Innovation Solution
Implementing a road assessment component that evaluates incident data and various factors to assign real-time danger ratings to road segments, allowing drivers to make informed decisions by displaying these ratings through navigation devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If navigation systems provide detailed real-time danger ratings and incident data for road segments, then drivers can make informed decisions to select safer routes, but the device complexity and data processing requirements increase significantly
Solution Approach 1:
The system segments road networks into discrete road segments and evaluates each segment independently for danger ratings. Incident data is collected and analyzed at the segment level, allowing the system to provide granular safety information without overwhelming complexity. Each segment can be assessed based on its specific characteristics and incident history.
Solution Approach 2:
The system pre-calculates and stores danger ratings for road segments based on historical incident data and road characteristics. This preliminary assessment allows the navigation system to quickly retrieve and display safety information without performing complex real-time analysis during route planning, reducing computational burden.
2Measurement precision
If the system collects and analyzes multiple factors including incident data, road characteristics, demographics, and real-time events, then the accuracy of danger ratings improves, but the quantity of data and processing requirements increase
Solution Approach 1:
The system extracts only the most relevant features and factors from large volumes of raw data. Instead of processing all available incident data and road characteristics in full detail, the system identifies and extracts key indicators that most strongly correlate with road safety, reducing data volume while maintaining rating accuracy.
Solution Approach 2:
The system implements a multi-factor evaluation model that considers multiple data sources including incident history, road geometry, traffic patterns, and environmental factors. By systematically evaluating these partial aspects separately and combining them, the system achieves comprehensive accuracy without being overwhelmed by the total data volume.
3Reliability
If danger ratings are updated in real-time as new incident data becomes available, then the reliability of safety information improves, but the frequency of data processing and energy consumption increase
Solution Approach 1:
The system implements periodic updates of danger ratings at scheduled intervals rather than continuous real-time processing. Incident data is collected and processed at regular intervals, allowing the system to maintain current information while reducing computational frequency and energy consumption compared to continuous real-time analysis.
Solution Approach 2:
The system monitors incident data and updates danger ratings based on feedback from new incidents and changing road conditions. When significant events occur (such as major incidents or road construction), the system triggers targeted updates to affected segments, balancing information currentness with energy-efficient processing by updating only when necessary.
Data Source
AI summary
One or more techniques and/or systems are provided for road segment ranking. Incident data associated with a first road segment is evaluated to determine an incident trend for the first road segment. Factors for the first road segment are identified. A first danger rating is assigned to the first road segment based upon the incident trend and the factors. The first danger rating is displayed on a display of a device.