Weather Detection via Untracked Laser Data Points
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately detecting weather conditions, such as rain, fog, and sunlight, using onboard sensors, which can affect their safe operation and driving behavior.
Innovation Solution
The method involves receiving and processing laser data points from a vehicle's environment, associating them with objects, and identifying unassociated data points as indicative of weather conditions by comparing them with data from radar and camera systems, along with additional information like geographic location and time, to determine weather conditions like wet roads, fog, or sunny conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If onboard sensors are used to detect weather conditions, then autonomous vehicles can identify weather conditions like rain, fog, and sunlight, but the accuracy of detection is insufficient and may not provide reliable information for safe operation
Solution Approach 1:
The patent segments the detection process into multiple independent analysis streams: laser data processing, radar data processing, and camera image processing. Each sensor type independently analyzes specific aspects of the environment, and their results are integrated to form a comprehensive weather assessment. This segmentation allows each sensor to optimize for its specific detection task while maintaining overall system reliability.
Solution Approach 2:
The patent merges data from multiple sensor types (laser, radar, camera) to detect weather conditions. By combining the detection results from these different sensor systems, the patent achieves both high reliability (through multiple independent verification sources) and high precision (through complementary detection capabilities of different sensor types).
2Measurement precision
If multiple sensor systems are integrated to improve detection accuracy, then weather conditions can be detected more reliably, but the device complexity increases
Solution Approach 1:
The patent implements a multi-functional processing system where a single computing device handles multiple sensor types (laser, radar, camera) and performs various functions including object detection, weather condition detection, and driving behavior determination. This universal approach reduces overall system complexity by consolidating processing capabilities rather than requiring separate dedicated systems for each function.
Solution Approach 2:
The patent introduces an intermediary processing layer that integrates data from multiple sensor systems. This intermediary computing device acts as a mediator that receives raw data from various sensors, processes and correlates the information, and outputs unified detection results. This intermediary layer simplifies the integration complexity by providing a standardized interface between diverse sensor types and the control system.
3Measurement precision
If unassociated laser data points are analyzed to identify weather conditions, then detection accuracy improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent extracts and isolates unassociated laser data points from the overall point cloud data. By specifically identifying and separating these unassociated points (which represent weather conditions rather than objects), the system can analyze them independently without the complexity of processing all laser data points. This extraction approach simplifies the detection process while maintaining high precision in weather condition identification.
Solution Approach 2:
The patent applies partial action by focusing analysis only on the specific subset of laser data points that are unassociated with detected objects. Rather than processing all laser data points equally, the system selectively analyzes only those points relevant to weather condition detection. This partial approach reduces computational difficulty while maintaining detection precision.
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 accurately identify weather conditions, allowing for appropriate adjustments in driving behavior, such as transitioning to manual mode or modifying speed and braking distances, thereby enhancing safety and operational efficiency.
Implementation Method 1
receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points
Data Source
AI summary
Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.