Braking Event Mapping for Unsafe Road Condition Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current autonomous vehicle technologies primarily focus on navigation and fail to fully utilize existing hardware for additional services, lacking effective detection and response mechanisms for unsafe road conditions encountered during operation.
Innovation Solution
A system that analyzes braking event data from multiple vehicles to identify unsafe locations, using a cloud service and machine learning to create a map of hazardous areas, enabling real-time control responses for vehicles to avoid such conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles use sensors and AI algorithms to detect objects and analyze environment, then navigation capability is improved, but the system fails to detect unsafe road conditions like deep potholes
Solution Approach 1:
The patent combines braking event data from multiple vehicles with sensor data to create a comprehensive unsafe condition detection system. By merging crowdsourced braking data with individual vehicle sensor inputs, the system achieves both high reliability (through pattern recognition) and broad adaptability (through multiple data sources), solving the contradiction between detection accuracy and detection coverage.
Solution Approach 2:
The system makes existing vehicle sensors and processing power multi-functional by using them not only for navigation but also for detecting unsafe road conditions. The same sensors that capture environmental data are repurposed to identify braking patterns and unsafe conditions, achieving versatility without adding specialized detection hardware.
2Reliability
If the system collects and analyzes braking event data from multiple vehicles, then unsafe location detection capability is improved, but data processing complexity increases
Solution Approach 1:
The patent introduces a server as an intermediary that centralizes the complex task of collecting, storing, and analyzing braking event data from multiple vehicles. This mediator handles the data processing complexity remotely, allowing individual vehicles to maintain simpler onboard systems while still benefiting from comprehensive unsafe condition detection through pattern recognition algorithms executed on the server.
3Productivity
If existing sensors and processing power are fully utilized for additional services, then system efficiency is improved, but navigation performance may be compromised
Solution Approach 1:
The system enables vehicles to self-enhance their safety capabilities by utilizing their own existing sensors and processing power to contribute to and benefit from the collective braking event database. Each vehicle serves itself by processing its own sensor data locally while simultaneously contributing to the broader unsafe condition detection network, achieving high system utilization without compromising navigation performance.
Data Source
AI summary
Data is received regarding vehicle braking events, each event occurring on one of a plurality of vehicles, and each event associated with a location. A determination is made that the braking events correspond to a pattern. Based on determining that the braking events correspond to the pattern, a first location is identified. In response to identifying the first location, at least one action is performed.