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Netherlands
Automotive
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Autonomous Vehicle Simulation Platform
Dedicated Team Engagement
20 months
Vehicle Engineers, Testers, Data Scientists, and Developers
To reduce the physical testing costs of developing an autonomous vehicle and ensure safer deployment, one of the leaders in autonomous vehicle development wanted to build a test simulation platform for autonomous technologies. The aim was to simulate traffic conditions created by real-world interactions between vehicles, road conditions, and weather environments.
Complex Real-World Simulations: The client required high-fidelity simulations that could mimic the reality of real-world driving in its complexity: road terrace variability, traffic behavior, and weather conditions.
High Computations: The task of building self-driving car simulators poses the challenge of extreme computational capabilities, which are essential for handling huge amounts of data, computing real-time vehicle interactions, and evaluating performance metrics.
Continuous Testing and Integration: The client needed a continuous integration pipeline for testing so that new features landed with minimal downtime and updates were done in a faster way.
Data Management: The complexity of the data from a simulation was so voluminous that it could no longer be managed and analyzed for decisions or improvement. Efficient storage and retrieval mechanisms were, therefore, required in this context.
Realistic simulation using AI and Python: Adorebits developed an AI-driven simulation engine utilizing Python to simulate driving scenarios realistically. The platform sed AI models to predict behaviors in traffic, determine obstacles on roads, and simulate real-time decision-making.
Cloud-based hosting: All the simulation platform was hosted on a cloud-based infrastructure through Microsoft Azure, to enable high scalability computing power with the handling of many complex simulations and heavy computational loads.
Containerization and continuous integration: Using Docker and Jenkins, the company was able to provide the client with a seamless CI/CD pipeline. This allowed for fast iteration of code and continuous testing while deploying new features faster with minimal manual intervention.
Data Processing with SQL, SAS, and R: Data was processed using SQL, SAS, and R where massive simulation data were stored and processed using SQL databases, while advanced analytics and data visualization were done using SAS and R to give the client deep insights into the performance of their autonomous vehicle
Frontend with React.js: Adorebits created a user-friendly frontend with React.js, exposing engineers and testers to an effortless configuration of simulations, view of results, and easy changes to parameters while testing.
Reduced Testing Costs: The customer could rely only on costly physical tests by simulating thousands of driving scenarios, but their testing costs were down by 50%.
Faster development cycle: The continuous integration environment allowed the team to test new features and deploy updates much faster, saving them 30% of the development cycle time.
Better Accuracy by Simulations: The nature of the AI-driven models, along with the strength of the data processing, guaranteed better accuracy in such simulations.
Increased safety: By running large amounts of simulations, the client would have been able to foresee and reduce the danger of hazards; thus, their self-driving cars would have increased overall safety before an actual deployment in public.
Adorebits successfully delivered a comprehensive autonomous vehicle simulation platform that meets the client’s objectives, changing the face of their testing and improving the safety and reliability of autonomous vehicle technologies. This solution places Adorebits as the leader in advanced simulation technologies for the autonomous vehicle industry.
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