Road Obstruction Detection via Dual Traffic State Recognition
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Solution Overview
Problem
Existing road information systems cannot accurately determine whether a road is passable based on the size of a movable body, particularly in situations where disasters or obstructions occur, as they do not differentiate between the traffic states of larger and smaller vehicles.
Innovation Solution
A road information providing system that includes first and second traffic state recognition units to assess the traffic states of larger and smaller movable bodies, a specific road area extraction unit to identify areas with decreased traffic volume and obstruction conditions, and a traveling obstruction information unit to notify of potential travel hazards, using traffic determination conditions and captured images to determine road passability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single traffic state recognition system is used for all movable bodies, then the system complexity is reduced, but the measurement precision of road passability information deteriorates
Solution Approach 1:
The traffic state recognition system is segmented into multiple independent recognition units, each dedicated to a specific movable body type (first-type and second-type). This segmentation allows each unit to specialize in detecting traffic states appropriate to its target vehicle category, thereby improving measurement precision without requiring a single overly complex system that attempts to handle all vehicle types simultaneously.
Solution Approach 2:
Different recognition units are assigned different detection capabilities and parameters tailored to their specific movable body type. For example, larger first-type movable bodies may require different detection thresholds, speed ranges, and traffic flow parameters compared to smaller second-type movable bodies. This local quality approach ensures each unit operates with optimal precision for its designated function.
2Reliability
If traffic state recognition is differentiated by movable body size, then the reliability of road passability information is improved, but the device complexity increases
Solution Approach 1:
The system is divided into separate recognition units for first-type and second-type movable bodies, allowing each unit to independently analyze traffic states relevant to its vehicle category. This segmentation improves reliability by ensuring that road passability assessments are based on size-appropriate traffic patterns, while the modular structure manages complexity through functional separation.
Solution Approach 2:
The multiple recognition units feed into a unified specific road area extraction unit that synthesizes information from both units to determine overall road passability. This multi-functionality allows the system to handle different vehicle types with specialized detection while maintaining a cohesive decision-making process, balancing reliability improvement with manageable system complexity.
3Measurement precision
If multiple traffic state recognition units are deployed for different movable body types, then the accuracy of specific road area extraction is improved, but the loss of information processing resources increases
Solution Approach 1:
Traffic state recognition is segmented into specialized units that process information relevant to specific movable body types, improving the accuracy of specific road area extraction by focusing computational resources on size-appropriate traffic patterns. This segmentation reduces the processing burden on each individual unit compared to a single unit attempting to analyze all vehicle types comprehensively.
Solution Approach 2:
Each recognition unit processes only the traffic state information relevant to its designated movable body type, performing a partial analysis rather than attempting complete comprehensive analysis. This partial action approach improves extraction accuracy for each vehicle category while reducing the total information processing resource consumption by avoiding redundant analysis of irrelevant traffic data.
Data Source
AI summary
A road information providing system includes: a first traffic state recognition unit that recognizes a first traffic state that is a traffic state of first-type movable bodies; a second traffic state recognition unit that recognizes a second traffic state that is a traffic state of second-type movable bodies smaller in size than the first-type movable bodies; a specific road area extraction unit that extracts, as a specific road area, a road area satisfying traffic determination conditions including a determination condition that the first traffic state shows that a traffic volume of the first-type movable bodies has decreased and a determination condition that the second traffic state shows that the second-type movable body is traveling; and a traveling obstruction information providing unit that provides traveling obstruction information serving as notification that an event has occurred which obstructs the traveling of the first-type movable bodies in the specific road area.