This guide gets the Robotaxi Zoox simulation running on your machine and walks you through your first algorithm run. By the end you will have cloned the repository, launched the animated GUI, loaded a built-in city map, and watched BFS guide the taxi to collect every passenger — then you will know exactly how to read the results modal and swap in any of the other four algorithms without restarting the app.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/Juan-Carlos-Cruz/robotaxi-zoox/llms.txt
Use this file to discover all available pages before exploring further.
Prerequisites before you begin:
- Python 3 installed and on your
PATH. - A graphical environment — a desktop session on Linux, macOS, or Windows. The GUI cannot render over a plain SSH connection without X11 forwarding.
- tkinter — ships with most Python installers; used for the map file-picker dialog.
- pygame — installed automatically by the bootstrap scripts; version 2.6.1 is pinned.
Clone the repository
Download the project to your local machine:The repository includes all map files, audio assets, and algorithm source code — no additional downloads are required.
Run with a single command
The bootstrap scripts detect your Python version, create a virtual environment, install Windows:The first run takes a few extra seconds while the virtual environment is created and dependencies are installed. Subsequent runs start immediately.
pygame, and launch the application automatically.Unix, Linux, or macOS:Select a map
A file-picker dialog opens automatically pointing to the
mapas/test/ directory. The folder contains eight pre-built city maps (Prueba1.txt through Prueba8.txt) that range from simple to complex.Select Prueba1.txt and click Open to load the introductory map. The grid renders on the left panel — roads, buildings, a taxi, passengers, and a destination marker all appear in city-themed sprites. The algorithm control panel occupies the right side.Choose an algorithm
In the right-hand panel, click No informada to expand the uninformed search options. Three buttons appear: Amplitud, Costo uniforme, and Profundidad.Click Amplitud to run BFS.The taxi animates across the grid, playing road and horn sound effects as it moves and collects each passenger. When the taxi reaches the destination the animation stops and the results modal opens automatically.
Reading the Results Modal
The modal that appears at the end of each run reports six metrics drawn directly from the search algorithm’s output:| Field | What it means |
|---|---|
| Nodos expandidos | Total nodes removed from the frontier and processed — a direct measure of how much of the search space was explored. |
| Profundidad | Depth of the solution node in the search tree, i.e. how many moves deep the solution lies. |
| Pasos del camino | Number of individual grid steps in the solution path from start to destination. |
| Costo total | Accumulated movement cost along the solution path; high-traffic cells contribute more than free roads. |
| Tiempo de búsqueda | Wall-clock time in milliseconds spent running the search algorithm. Animation time is measured separately and excluded from this value. |
| Heurística final (informed only) | The heuristic value at the goal node; shown only for Greedy Best-First and A*. |