autonomous_driving

Autonomous Driving

Technical Requirements for C++ Autonomous Driving Developer

Core Skills

C++ Programming

• Modern C++ (C++11/14/17/20) features and best practices
• Template programming and STL containers/algorithms
• Memory management and performance optimization
• Multi-threading and concurrent programming
• RAII and smart pointers usage

Computer Vision

• OpenCV library for image processing
• Camera calibration and distortion correction
• Object detection and tracking algorithms
• Lane detection and road segmentation
• Point cloud processing (PCL library)

Robotics Frameworks

• ROS/ROS2 (Robot Operating System)
• Cyber RT (Baidu Apollo framework)
• DDS (Data Distribution Service) middleware
• Real-time operating systems (RTOS)

Algorithms

• Kalman filters and particle filters
• SLAM (Simultaneous Localization and Mapping)
• Path planning algorithms (A*, RRT, etc.)
• Sensor fusion (camera, LiDAR, radar, IMU)
• Machine learning for perception tasks

Tools & Technologies

Development Tools

• CMake for build system
• Docker for containerization
• Git for version control
• GDB/LLDB for debugging
• Valgrind for memory analysis

Sensors

• LiDAR data processing
• Camera interfaces (GigE Vision, USB3 Vision)
• Radar signal processing
• GPS/IMU integration
• CAN bus communication

Simulation

• Carla, Gazebo, or Apollo Dreamview
• Hardware-in-the-loop testing
• SIL (Software-in-the-loop) validation

Domain Knowledge

• ISO 26262 functional safety standards
• Vehicle dynamics and control theory
• Sensor characteristics and limitations
• HD map formats (OpenDRIVE, Lanelet2)