Autonomous Driving Road Damage Detection for Pothole Avoidance
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Solution Overview
Problem
Current autonomous driving systems are unable to detect potholes and cracks on the road in real time, which poses safety risks and poor ride experiences, especially at high speeds, as they do not account for road surface conditions in their driving strategies.
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 accordingly, incorporating sensors to capture road surface images and convert pixel positions to ego-vehicle coordinates for accurate damage assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous driving systems do not detect road surface damage, then the system complexity remains low, but safety and ride experience deteriorate due to rollover or collision risks
Solution Approach 1:
The patent combines road surface damage detection functionality with the existing autonomous driving control system. The sensor array captures road surface images, the image detection algorithm processes these images to identify damage, and the autonomous driving unit integrates this information with existing driving strategies. This merging approach allows safety improvement without creating a completely separate complex system.
Solution Approach 2:
The autonomous driving control system is enhanced to perform multiple functions: it continues its original autonomous driving operations while simultaneously detecting road surface damage, determining damage degree and distance, and adjusting driving strategies based on detected conditions. This multi-functionality allows the system to improve safety without requiring entirely separate dedicated systems for each function.
2Reliability
If real-time road surface detection is implemented, then safety and ride experience improve, but processing time and computational resources increase
Solution Approach 1:
The system continuously captures road surface images using the sensor array and processes them through the image detection algorithm in real-time before the vehicle reaches the damaged area. By performing detection and analysis in advance, the autonomous driving unit has sufficient time to process the damage information and adjust driving strategies without compromising safety or requiring excessive processing time during critical moments.
3Reliability
If the vehicle decelerates or avoids road surface damage, then safety improves, but driving efficiency and speed reduce
Solution Approach 1:
The autonomous driving unit adjusts driving strategies locally only when road surface damage is detected. The system determines the damage degree and distance, then applies targeted deceleration or avoidance maneuvers specifically for the affected area. Outside of damaged zones, the vehicle maintains normal driving speed and efficiency, thus improving safety without significantly compromising overall driving productivity.
Data Source
AI summary
An autonomous driving control method for a vehicle may include: 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.