The focus of this term is,
- Path Planning: brains of a self-driving car
- An elective (Semantic Segmentation OR Functional Safety)
- System Integration module
GitHub repository links to Term 3 projects are as given below.
1. Highway Path Planner
Tie together prediction, behavior, and trajectory engines from the previous lessons to create an end-to-end path planner that drives the car in traffic.
Curriculum / Expert Instructors: Mercedes-Benz Research & Development North America
Here is the link for the completed project - SDC-P11-Path-Planner
2. Functional Safety
The goal of this module is to learn functional safety frameworks to ensure that vehicles is safe, both at the system and component levels.
Curriculum / Expert Instructors: Elektrobit
Here is the link for the completed project - SDC-P12-Functional-Safety
3. Advanced Deep Learning Project: Semantic Segmentation (Optional)
To build a semantic segmentation network to identify free space on the road using fully convolutional networks.
- Special techniques are used to create a semantic segmentation model that classifies each pixel of free space on the road.
- To accelerate the network’s performance, inference optimizations like fusion, quantization, and reduced precision are implemented.
Curriculum / Expert Instructors: NVIDIA Deep Learning Institute
Here is the link for the completed project - < TBD >
4. System Integration
To implement perception, path planning, and control sub-systems as ROS nodes and integrate software modules to get the simulated car to successfully navigate the test track.
Here is the link for the completed project - SDC-Final-Capstone