Autonomous Car Grid Simulation

GUI-based simulator that runs seven search algorithms on the same grid, compares their performance, and visualizes the optimal path.

Features

• Preset grids (5x5, 10x10, 15x15, maze, weighted) or deterministic custom random grids with obstacles and weights.
• Algorithms: BFS, DFS, Uniform Cost, Greedy Best-First, A*, IDA*, Bidirectional, Bidirectional A*.
• Metrics: path cost, explored nodes, execution time. Automatic optimal selection (cost → nodes → time).
• Tkinter GUI with start/pause/resume/reset controls, speed slider, live exploration animation, final path highlighting, and a car sprite (asset at assets/car.png, with a base64 fallback in src/app.py) that drives along the finished path.
• Analytics overlay: Visualization screen features a Show Analytics button (implemented in src/app.py → VisualizationFrame.show_analytics_overlay) that plots per-algorithm bar charts for SearchResult.cost, SearchResult.explored_nodes, and SearchResult.duration using embedded matplotlib.

Run

python -m src.app

Requires Python 3 with Tkinter available (bundled in standard CPython).

Usage

1. Choose a preset or enter custom grid parameters (rows/cols, obstacle ratio, weighted ratio).
2. Click Start. When prompted, choose whether to use the preset; select "No" to use custom settings.
3. Watch exploration animate; pause/resume as needed. Final optimal algorithm and metrics appear in the side panel along with per-algorithm comparisons, and once the path is ready a car drives the route. After each run, click Show Analytics to open the chart overlay for time, cost, and nodes explored.
4. Click Reset to clear the canvas and run again.

Structure

• src/grid.py — grid model, weights, random generation.
• src/presets.py — preset grid definitions.
• src/algorithms/ — implementations of the seven algorithms and shared helpers.
• src/evaluator.py — runs algorithms (threaded) and selects the optimal result.
• src/app.py — Tkinter GUI and visualization.

Documentation

The docs/ directory holds deeper dives for contributors:

• docs/ARCHITECTURE.md details the simulator layers and threading flow.
• docs/CODEBASE_GUIDE.md maps modules, data structures, and extension points.
• docs/TESTING.md and docs/TROUBLESHOOTING.md cover validation steps and fixes.
• docs/USER_FLOWS.md documents the GUI journeys we support today. Review these guides whenever you touch adjacent areas to keep the overview aligned with the implementation.