Deep analysis and data-driven insights from our vehicle safety research. Discover patterns, trends, and findings that shape the automotive safety landscape.
Advanced Pattern Recognition in NHTSA Complaint Data
Using natural language processing and machine learning techniques, we analyzed over 5.3 million vehicle safety complaints to identify emerging defect patterns before they become widespread recalls.
NLP AnalysisMachine LearningPredictive Models
Chart: Defect Pattern Recognition Timeline
Updated 2 days ago
Published on •8 min read
Electric Vehicle Battery Safety: Trends and Predictions
A comprehensive analysis of battery-related safety incidents in electric vehicles, examining failure patterns, thermal runaway events, and predictive indicators for potential issues.
Electric VehiclesBattery SafetyThermal Analysis
Chart: EV Battery Incident Trends by Model Year
Updated 1 week ago
Research Categories
Data Analysis
Statistical analysis of vehicle safety data, trend identification, and pattern recognition research.
15 Articles
Predictive Models
Machine learning applications for predicting vehicle defects and safety issues before they escalate.
8 Articles
Industry Insights
Market analysis, regulatory insights, and automotive industry trend research and commentary.
12 Articles
Recent Research
Published on •Research Paper•15 min read
Autonomous Vehicle Safety: Statistical Analysis of Edge Cases
A comprehensive study examining safety incidents in autonomous vehicles, focusing on edge cases and unusual scenarios that challenge current AI systems. Our analysis covers over 50,000 miles of autonomous driving data across multiple manufacturers.
Semiconductor Shortage Impact on Vehicle Safety Systems
Analyzing how the global semiconductor shortage has affected the implementation and reliability of advanced safety features in vehicles manufactured between 2021-2024.
Supply ChainSafety SystemsMarket Analysis
Chart: Safety Feature Availability Timeline
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