Thesis: Development of an Automotive Simulation Platform for Sensor Data Generation and Communication Protocols
This simulation platform will be a valuable resource for automotive engineers and researchers, enabling controlled testing and development of automotive systems. By supporting simulated and real data inputs, as well as multiple protocols, the platform will help reduce development costs and improve the reliability of automotive technologies through comprehensive testing and scenario generation.
Description
This thesis aims to develop a simulation platform tailored for the automotive industry, capable of generating simulated sensor data or connecting to actual sensors for real-time data transmission. The platform will support various communication protocols, including CAN (Controller Area Network) and Ethernet, and feature a user-friendly graphical user interface (GUI) for parameter selection, test scenario creation, and monitoring of device responses.
Key Features
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Sensor Data Simulation
- The platform will generate realistic sensor data for automotive applications, such as speed, temperature, and proximity sensors.
- This capability allows for testing and validating automotive systems without requiring physical sensors in all scenarios.
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Integration with Actual Sensors
- The simulator will enable users to connect actual sensors for real-time data capture and transmission.
- This functionality is critical for testing and validating vehicle control systems and other applications requiring live data.
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Multi-Protocol Support
- The platform will accommodate multiple communication protocols, including CAN and Ethernet, providing flexibility for users to simulate diverse network environments and evaluate system behavior under various conditions.
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Graphical User Interface (GUI)
- A user-friendly GUI will allow users to select simulation parameters, visualize sensor data, and monitor the responses of connected devices, enhancing usability and simplifying the testing process.
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Test Scenario Generation
- The platform will generate data for creating specific test scenarios, enabling users to simulate different conditions and evaluate the performance of the device under test (DUT).
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Real Data Integration
- Users will be able to import real data from files (e.g., CSV, Excel) and feed it into the DUT, increasing the realism and depth of testing.
Challenges
- Realism of Simulated Data: Ensuring that the simulated data closely mirrors real-world conditions to provide effective testing outcomes.
- Interoperability: Achieving smooth integration between the simulator, sensors, and protocols may require extensive testing and validation.
- Data Management: Efficiently handling and processing imported real data while maintaining system performance.
- Scalability: Designing the platform to support future enhancements, such as additional sensor types and protocols, without compromising performance or usability.