Camera-Based Road Characteristic Detection From Object Motion
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Solution Overview
Problem
Existing systems for determining road characteristics, such as lidar and radar, are expensive and inefficient for autonomous and semi-autonomous vehicles to detect road irregularities like potholes or terrain changes.
Innovation Solution
A method and system using camera information to identify the position and relative motion of features in front of a vehicle, determining road characteristics based on this motion, and adjusting vehicle parameters like suspension settings accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor based systems such as lidar or radar are used to determine road characteristics, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a camera to capture visual images of the road and processes these images to extract road characteristics. Instead of using expensive lidar or radar sensors, the system creates a visual copy of the road scene and analyzes it through image processing algorithms to determine road features, thereby achieving comparable measurement precision with simpler, cheaper equipment
Solution Approach 2:
The patent replaces complex mechanical sensing systems (lidar, radar) with an optical system (camera). By substituting the mechanical sensor-based approach with image capture and processing, the system achieves road characteristic detection with reduced device complexity and lower cost while maintaining adequate measurement precision
2Measurement precision
If sensor based systems such as lidar or radar are used to determine road characteristics, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent employs a camera, which is a relatively inexpensive and widely available component compared to lidar or radar systems. The system uses standard image processing techniques that can be implemented with affordable computational resources, thereby significantly reducing the overall system cost while maintaining adequate measurement precision for road characteristic detection
Solution Approach 2:
The system creates visual copies of the road through camera imaging and processes these copies to extract road characteristics. This approach eliminates the need for expensive specialized sensors, achieving cost-effective road detection by using standard imaging technology combined with software-based analysis
3Device complexity
If camera information is used to determine road characteristics, then device complexity is reduced, but measurement precision may decrease
Solution Approach 1:
The patent employs dynamic image processing techniques that adapt to varying road conditions. The system processes a sequence of images over time, using temporal dynamics to enhance the detection of road characteristics. By dynamically adjusting processing parameters and analyzing changes across multiple frames, the system compensates for the inherent limitations of camera-based sensing and maintains measurement precision
Solution Approach 2:
The patent transitions from analyzing single static images to processing temporal sequences of images, adding the time dimension to the analysis. By examining how road features change across multiple frames and combining this temporal information with spatial analysis, the system enhances measurement precision while maintaining device simplicity
Data Source
AI summary
Methods, systems, and media for determining characteristics of roads are provided. In some embodiments, the method comprises: receiving, at a first time point, first camera information from a camera associated with a vehicle; identifying a first position of a feature of an object in front of the vehicle based on the first camera information; receiving, at an additional time point, additional camera information from the camera; identifying an updated position of the feature of the object in front of the vehicle based on the additional camera information; determining a relative motion of the feature of the object in front of the vehicle based on the first position and the updated position; and determining a characteristic of a road the vehicle is on based on the relative motion of the feature of the object in front of the vehicle.