feat: initial HSAP platform

Huaxu Sentinel Active Safety Platform with embedded algorithm code,
Docker Compose setup, and vendored dataset scaffolds for clone-and-run.

Co-authored-by: Cursor <cursoragent@cursor.com>

algorithms/lane_ufld/code/pytorch-auto-drive-master/configs/README.md

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+## Configs
+
+Config files in *PytorchAutoDrive* (`./configs/`) are used to define models,
+how they are trained, tested, visualized, *etc*.
+
+### Registry Mechanism
+
+Different to existing class-based registers, we can also register functions.
+For functions, you only write static args in your config,
+while passing the dynamic ones on-the-fly by:
+
+```
+REGISTRY.from_dict(
+    <config dict for a function/class>,
+    kwarg1=1, kwarg2=2, ...
+)
+```
+
+Note that each argument must be keyword (k=v), and some kwargs can overwrite dict configs.
+
+### Use An Existing Config
+
+Modify customized options like the root of your datasets (in `configs/*/common/_*.py`).
+
+### Write A New Config
+
+Copy the config file most similar to your use case and modify it.
+Note that you can simply import config parts from `common` or other config files, it is like writing Python.
+
+### Register A New Class/Func
+
+Choose the appropriate registry and register your Class/Func by:
+
+```
+@REGISTRY.register()
+```
+
+Remember you still need to import this Class/Func for the registering to take effects.
+
+### How To Read The Code
+
+Since you can't just click 'go to definition' in your IDE,
+it is suggested to search the directory for each Class/Function by `name` in configs.