Autonomous Road Weather Detection Using Vehicle Pose and Slippage
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately determining and responding to adverse weather conditions such as ice, snow, and wet roads, which can impact traction and safe operation, as existing sensor systems may lack precision and fail to adequately assess these conditions.
Innovation Solution
The vehicle employs a method involving sensor data analysis to determine actual and expected vehicle poses, identifying differences that indicate adverse weather or road conditions, and adjusts driving operations or route planning accordingly, using actuation of subsystems like braking, acceleration, and steering, and communication with other vehicles to gather and share information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle uses standard sensor systems to detect environmental features, then the system can operate in autonomous mode, but the sensors lack the precision needed to properly evaluate weather conditions' impact on vehicle operation
Solution Approach 1:
The patent combines multiple data sources including sensor data from the vehicle, pose information from positioning systems, and weather data from external sources into a unified weather condition assessment system. This integration allows the system to achieve higher measurement precision for weather conditions by synthesizing information from multiple inputs rather than relying on a single sensor system.
Solution Approach 2:
The patent creates a multi-functional assessment system that evaluates various weather conditions (precipitation, temperature, road surface conditions) using a single integrated system. This system can determine multiple weather parameters simultaneously and assess their combined impact on vehicle operation, eliminating the need for separate specialized sensors for each weather parameter.
2Reliability
If the vehicle aggregates and analyzes multiple data sources to determine weather conditions, then the system can accurately assess adverse conditions, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary processing of sensor data and pose information to extract relevant features before combining them with weather data. The system pre-processes raw sensor inputs to identify key indicators of weather conditions, reducing the computational burden during real-time integration and assessment phases.
Solution Approach 2:
The patent implements a feedback mechanism where the vehicle's actual response to detected weather conditions is monitored and used to refine future weather assessments. The system learns from the vehicle's operational responses and adjusts its weather condition determination algorithms to improve reliability over time while maintaining efficient processing.
Data Source
AI summary
The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.