Lane-Based Slow Vehicle Detection Using Image Speed Measurement
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Solution Overview
Problem
Slow vehicles on fast lanes cause traffic chaos and accidents by affecting the driving experience of surrounding vehicles and are often unaware of traffic congestion or potential accidents due to violating minimum speed limits.
Innovation Solution
A vehicle detection system that uses image processing and speed measurement to identify slow vehicles ahead, tracks historical congestion events, and provides warnings to adjust lane position or speed, preventing traffic disruptions and accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If slow vehicles travel on fast lanes, then their driving speed is maintained, but traffic chaos and accidents occur due to affecting surrounding vehicles
Solution Approach 1:
The system implements feedback by detecting slow vehicles through image recognition and speed measurement, then providing warning information to the slow vehicle's driver. This feedback loop enables the slow vehicle to adjust its speed or lane position, resolving the contradiction between maintaining driving speed and avoiding traffic chaos.
Solution Approach 2:
The system performs preliminary detection and warning before traffic chaos occurs. By identifying slow vehicles in advance and providing warnings, the system prevents harmful effects rather than reacting after accidents or congestion occur.
2Speed
If slow vehicles are not warned, then they maintain their current speed, but they are unaware of traffic congestion or potential accidents
Solution Approach 1:
The warning system provides feedback to slow vehicles about their driving state and surrounding conditions. This feedback includes information about traffic congestion and potential accidents, enabling drivers to make informed decisions to improve safety awareness while maintaining or adjusting their speed.
3Measurement precision
If image recognition and speed measurement are performed continuously, then slow vehicles are accurately identified, but system complexity and processing requirements increase
Solution Approach 1:
The system applies partial action by performing image recognition and speed measurement only when necessary - specifically when detecting vehicles in the fast lane and determining they are traveling below the minimum speed limit. This selective approach maintains identification accuracy while reducing unnecessary processing complexity.
Data Source
AI summary
A vehicle driving detection method includes: obtaining first image data corresponding to a driving direction of a first vehicle; performing lane line detection processing on the first image data to determine that the first vehicle is traveling along a first lane of at least two lanes; performing image recognition processing on the first image data to detect that a second vehicle travels on the first lane within a preset distance in front of the first vehicle; performing speed measurement processing on the second vehicle to obtain a first speed of the second vehicle; and determining, when the first speed is less than a minimum speed limit of the first lane, the second vehicle as a potential slow vehicle.