Autonomous Driving Control for Real-Time Pothole Detection
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Solution Overview
Problem
Current autonomous driving systems are unable to detect potholes and cracks on roads in real time, which poses safety risks and poor ride experiences for passengers, especially when driving at high speeds, as they can lead to rollovers or collisions.
Innovation Solution
An autonomous driving control method and system that uses image detection algorithms to identify road surface damage, determine its degree and distance from the vehicle, and adjust the driving strategy to avoid or decelerate in response, incorporating bounding boxes, coordinate system conversion, and category confidence levels to classify damage types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If autonomous driving systems use traditional detection methods, then they can detect road conditions, but they cannot detect potholes and cracks in real time
Solution Approach 1:
The patent replaces traditional mechanical or manual road inspection methods with an optical imaging system. A sensor (camera) captures road surface images, and an image detection algorithm processes these images to identify potholes and cracks. This substitution enables real-time detection with high precision, resolving the contradiction between detection capability and response time.
Solution Approach 2:
The system creates a visual copy of the road surface through imaging sensors and processes this copy digitally using image detection algorithms. This allows the system to analyze road conditions without physical contact, enabling real-time detection while maintaining high measurement precision for pothole and crack identification.
2Reliability
If autonomous driving vehicles do not detect road surface damage, then the system is simpler, but safety risks increase due to rollovers or collisions
Solution Approach 1:
The patent makes the sensor serve multiple functions: it captures images for both general autonomous navigation and specific road surface damage detection. The image processing system handles multiple tasks including pothole detection, crack detection, and road condition assessment. This multi-functionality improves safety without proportionally increasing device complexity.
Solution Approach 2:
The patent introduces an image detection algorithm as an intermediary between the sensor and the autonomous driving control system. This intermediary layer processes visual information to identify road surface damage and translates it into actionable data for the driving system, enhancing safety while managing complexity through modular architecture.
3Reliability
If autonomous driving systems detect road surface damage, then safety improves, but the system requires complex image processing algorithms
Solution Approach 1:
The patent segments the road surface image into different regions and applies targeted detection algorithms to identify specific features such as potholes, cracks, and other damages. This segmentation approach improves detection accuracy by focusing computational resources on relevant features while managing algorithmic complexity through divided processing tasks.
4Productivity
If the vehicle maintains current speed, then productivity is high, but poor ride experience occurs when encountering bumps
Solution Approach 1:
The patent detects road surface damage in advance before the vehicle reaches it. By identifying potholes and cracks ahead of time, the system can prepare appropriate responses such as speed adjustment or path modification. This preliminary action allows the vehicle to maintain high productivity while avoiding poor ride experiences by addressing bumps before they affect passengers.
Data Source
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AI summary
The present disclosure relates to a vehicle, and an autonomous driving control method and a system for the vehicle. An autonomous driving control method for a vehicle may comprise: obtaining a road surface image from a sensor of the vehicle; detecting road surface damage from the road surface image using an image detection algorithm; determining a damage degree of the detected road surface damage and a damage distance of the road surface damage from the vehicle; and adjusting an autonomous driving strategy for the vehicle based on the damage degree and the damage distance. The autonomous driving control method for the vehicle can detect potholes or cracks in front of road accurately in real time and adjust the autonomous driving strategy based on a detection result, ensuring safety of passenger in the vehicle and improving passenger experience during the autonomous driving process.