Vehicle Road Hazard Detection Using Multi-Sensor Telematics
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Solution Overview
Problem
Current systems lack effective methods to detect and mitigate unsafe road conditions in real-time, such as potholes, construction, and speed bumps, which can lead to accidents and discomfort for drivers.
Innovation Solution
A road condition identification system that utilizes vehicle telematics and sensor data, including GPS coordinates, sound, visual, and movement data, to detect changes in road conditions and alert drivers or other parties, suggesting alternative routes to avoid hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and data sources are integrated to improve road condition detection accuracy, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (accelerometers, gyroscopes, microphones, cameras) and data sources (vehicle telematics, road sensor data, weather data) into a single integrated road condition monitoring system. This merging approach enables comprehensive data collection for accurate pothole detection while managing system complexity through unified processing architecture.
Solution Approach 2:
The system employs multi-functional sensors that can detect multiple types of road conditions simultaneously. For example, accelerometers detect both potholes and speed bumps, while microphones detect construction noises and weather conditions. This universality improves detection accuracy without proportionally increasing device complexity.
2Loss of time
If real-time data processing is implemented to provide immediate alerts, then response time improves, but energy consumption increases
Solution Approach 1:
The system implements periodic sampling of sensor data at optimized intervals rather than continuous monitoring. Data processing is triggered periodically or event-driven, allowing the vehicle to conserve energy during normal operation while still providing timely alerts when road conditions change significantly.
Solution Approach 2:
The system pre-processes and stores sensor data locally before transmission, and pre-identifies potential road hazards using onboard processing. This preliminary action reduces the computational burden during critical alert moments, enabling fast response times without requiring continuous high-energy processing.
Data Source
AI summary
The present disclosure relates to monitoring data in and around a vehicle to predict anomalous, e.g., unsafe, road conditions, and using the data to suggest a corrective action to avoid the unsafe road conditions. A computing device receives information indicative of imagery, sound, or vehicle operation via sensors and/or cameras mounted in or near a vehicle. The information may be received via the vehicle itself or via a device. The computing device then determines whether there is an indication of an anomalous road condition. The computing device also receives vehicle operation data extracted from one or more vehicle sensors. The computing device then determines whether there is an indication of unsafe road conditions, and if there is, the computing device may output a notice or alert via a notification system to alert the driver.