The autonomous vehicle revolution generates massive amounts of data every second. From LIDAR point clouds to camera feeds, GPS coordinates to acceleration metrics – modern self-driving cars are essentially computers on wheels, constantly collecting and processing information.
But here's the challenge: all that data means nothing without proper analysis. Whether you're an automotive engineer validating safety systems, a data scientist optimizing route planning algorithms, or a fleet manager tracking vehicle performance, you need tools that can handle the complexity of real-time automotive data analysis.
That's where Sourcetable transforms the game. Instead of wrestling with complex coding environments or waiting for IT support, you can analyze autonomous vehicle data directly in a familiar spreadsheet interface – powered by AI that understands automotive metrics.
Transform raw vehicle data into insights that drive safer, smarter autonomous systems
Track critical safety metrics like collision avoidance response times, sensor fusion accuracy, and emergency braking performance in real-time dashboards.
Combine LIDAR, camera, radar, and GPS data streams into unified analytics. No complex coding required – just natural language queries to your data.
Compare vehicle performance across different weather conditions, traffic scenarios, and route types. Identify optimization opportunities instantly.
Analyze sensor degradation patterns and component wear to predict maintenance needs before failures occur. Reduce downtime and ensure safety.
Evaluate energy efficiency, travel time optimization, and passenger comfort metrics across different routing algorithms and real-world conditions.
Automatically generate compliance reports for safety standards, track testing milestones, and maintain audit trails for regulatory submissions.
See how automotive teams use Sourcetable to solve real AV data challenges
A major automotive manufacturer needed to validate their emergency braking system across 50,000 test scenarios. Using Sourcetable, they imported sensor logs, crash test data, and simulation results. AI analysis revealed that braking performance degraded 15% in wet conditions with tire temperatures below 40°F – a critical finding that led to algorithm improvements before production.
An autonomous taxi service analyzed 100,000+ rides to optimize their routing algorithms. By combining GPS tracks, traffic data, and passenger feedback in Sourcetable, they discovered that avoiding highways during rush hour reduced trip time by 12% while improving passenger comfort scores by 18%.
A research team studying LIDAR accuracy across different weather conditions processed millions of point cloud measurements. Sourcetable's AI identified that accuracy dropped 8% in fog but remained stable in rain – insights that directly influenced sensor placement and calibration protocols.
An electric AV development team tracked energy consumption across urban, highway, and mixed driving scenarios. Analysis revealed that regenerative braking efficiency varied 25% based on traffic patterns, leading to software optimizations that increased range by 8%.
Transform complex vehicle telemetry into clear analytics in four simple steps
Connect directly to your data sources – whether it's real-time telemetry streams, historical log files, or simulation outputs. Sourcetable handles CAN bus data, sensor logs, GPS traces, and more. No data engineering required.
Instead of writing complex queries, simply ask: 'Show me safety incidents by weather condition' or 'Compare energy efficiency across routes.' Our AI understands automotive terminology and generates the analysis automatically.
Sourcetable's AI doesn't just crunch numbers – it understands automotive contexts. It can identify anomalies in sensor data, correlate performance metrics with environmental conditions, and suggest optimizations based on industry best practices.
Generate automated reports for stakeholders, create real-time dashboards for operations teams, and export findings for regulatory submissions. Keep everyone aligned with data-driven insights.
Sourcetable works with all major autonomous vehicle data formats and sources:
Yes, Sourcetable is designed for big data analytics. We can process terabytes of sensor data, real-time telemetry streams, and historical logs. Our AI optimizes queries automatically, so you get fast results even with massive datasets. Plus, you can connect directly to cloud storage and data lakes without moving data around.
Security is paramount for automotive data. Sourcetable provides enterprise-grade encryption, SOC 2 compliance, and supports on-premises deployment for sensitive development work. Your proprietary algorithms, test data, and performance metrics remain completely secure and under your control.
Not at all. Sourcetable's AI understands automotive terminology and can process complex multi-sensor data through natural language queries. Ask questions like 'correlate LIDAR accuracy with weather conditions' or 'show me brake performance trends' and get instant visualizations and insights.
Absolutely. Sourcetable connects with popular automotive tools including MATLAB/Simulink, CANoe, Vector tools, and major simulation platforms. We also support standard automotive data formats like MDF4, ASC, and custom proprietary formats through our flexible import system.
Sourcetable processes real-time data streams with sub-second latency. You can set up live dashboards showing current vehicle performance, safety metrics, and system status. Critical alerts and anomaly detection happen in real-time, so you can respond immediately to any issues.
Yes, Sourcetable includes templates for common automotive safety standards including ISO 26262, NHTSA guidelines, and other regulatory frameworks. Generate compliance reports automatically, track safety metrics over time, and maintain audit trails for regulatory submissions.
To analyze spreadsheet data, just upload a file and start asking questions. Sourcetable's AI can answer questions and do work for you. You can also take manual control, leveraging all the formulas and features you expect from Excel, Google Sheets or Python.
We currently support a variety of data file formats including spreadsheets (.xls, .xlsx, .csv), tabular data (.tsv), JSON, and database data (MySQL, PostgreSQL, MongoDB). We also support application data, and most plain text data.
Sourcetable's AI analyzes and cleans data without you having to write code. Use Python, SQL, NumPy, Pandas, SciPy, Scikit-learn, StatsModels, Matplotlib, Plotly, and Seaborn.
Yes! Sourcetable's AI makes intelligent decisions on what spreadsheet data is being referred to in the chat. This is helpful for tasks like cross-tab VLOOKUPs. If you prefer more control, you can also refer to specific tabs by name.
Yes! It's very easy to generate clean-looking data visualizations using Sourcetable. Simply prompt the AI to create a chart or graph. All visualizations are downloadable and can be exported as interactive embeds.
Sourcetable supports files up to 10GB in size. Larger file limits are available upon request. For best AI performance on large datasets, make use of pivots and summaries.
Yes! Sourcetable's spreadsheet is free to use, just like Google Sheets. AI features have a daily usage limit. Users can upgrade to the pro plan for more credits.
Currently, Sourcetable is free for students and faculty, courtesy of free credits from OpenAI and Anthropic. Once those are exhausted, we will skip to a 50% discount plan.
Yes. Regular spreadsheet users have full A1 formula-style referencing at their disposal. Advanced users can make use of Sourcetable's SQL editor and GUI, or ask our AI to write code for you.