Fog Detection via Unassociated Laser Data Points
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in accurately detecting weather conditions like fog using onboard sensors, which can affect their safe operation and driving behavior.
Innovation Solution
The method involves receiving and processing laser data points from vehicle scans, associating them with environmental objects, and comparing unassociated data points with stored patterns to identify fog conditions, utilizing a computing device to determine the presence of fog and adjust vehicle behavior accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser sensors are used to detect objects in the environment, then object detection capability is improved, but the ability to accurately distinguish weather conditions like fog deteriorates
Solution Approach 1:
The patent segments laser data points into two categories: those associated with known objects and those unassociated with objects. This segmentation allows the system to separately analyze object detection data and weather condition data, resolving the contradiction by enabling both functions to operate effectively on different data subsets.
Solution Approach 2:
The patent introduces an intermediary approach by using unassociated laser data points as a mediator to detect fog conditions. These data points, which do not correspond to known objects, serve as indicators of weather conditions, allowing the system to detect fog without compromising object detection accuracy.
2Ease of operation
If the vehicle operates in autonomous mode, then operator workload is reduced, but safety in adverse weather conditions deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the autonomous vehicle system continuously monitors laser data for fog conditions and automatically adjusts its operational mode. When fog is detected through analysis of unassociated laser data points, the system provides feedback to switch from autonomous to manual mode, ensuring safety while maintaining ease of operation in clear conditions.
3Reliability
If the vehicle switches to manual mode in foggy conditions, then safety is improved, but productivity deteriorates
Solution Approach 1:
The patent applies dynamics by making the vehicle's operational mode flexible and adaptive rather than fixed. The system dynamically switches between autonomous and manual modes based on real-time fog detection from laser data analysis, allowing the vehicle to maximize productivity in clear conditions while ensuring safety in adverse weather.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables autonomous vehicles to safely navigate through foggy conditions by identifying fog presence and modifying driving actions, such as switching to manual mode or adjusting speed, thereby ensuring safe operation.
Implementation Method 1
a laser sensor may be unable to detect objects through fog, and may in fact, receive data points reflected off the fog
Implementation Method 2
receiving laser data collected from scans of an environment of a vehicle
Data Source
AI summary
Methods and systems for detecting weather conditions including fog using vehicle onboard sensors are provided. An example method includes receiving laser data collected from scans of an environment of a vehicle, and associating, by a computing device, laser data points of with one or more objects in the environment. The method also includes comparing laser data points that are unassociated with the one or more objects in the environment with stored laser data points representative of a pattern due to fog, and based on the comparison, identifying by the computing device an indication that a weather condition of the environment of the vehicle includes fog.