Overview

Project details

In a futuristic smart city, the traffic management system is entirely autonomous and responsible for ensuring smooth traffic flow, minimizing congestion, and responding to incidents.

Specifications

Objective:

Design and implement an autonomous traffic management system for a smart city that controls traffic lights, manages vehicle routing, monitors road conditions, and handles emergency scenarios without relying on any external APIs or third-party services.

Context:

In a futuristic smart city, the traffic management system is entirely autonomous and responsible for ensuring smooth traffic flow, minimizing congestion, and responding to incidents. This system should handle many vehicles, diverse road networks, and various real-world scenarios such as accidents, road maintenance, and emergency vehicle priority.


Tracks: Python

845

number of points you will earn

5

launches to complete the project

19

tasks to complete the project

This project is part of the following tracks:

Learning outcomes

  • Get adapted to the EpicLaunchX learning style.

  • Understand the flow actions at EpicLaunchX.

  • Explore PR and code best practices, and earn your first points.

  • Learn more about GitHub and master the conventional commit style.

  • Use Makefile extensively, explore code formatting, linting style, etc.

  • Usage of Domain Driven Design(DDD).


Project Launches & Tasks

Note: Only the first 2 of 5 launches are shown below as a preview.

launch_1

  • task_1 (50 points)

    • Create a domain/models.py file to manage the traffic lights state.

    • Create a TrafficLightState class that inherits from the Enum class.

    • Use the enum to change the traffic lights state.

    • Traffic light states must be RED, YELLOW, and GREEN.

    • __str__ method has to return the key's value.

    • Remember to implement unit tests for traffic light states, and use pytest for tests.

  • task_2 (45 points)

    • Create an Intersection class with id and connected_roads class fields.

    • Class must be located in domain/entities.py.

    • The id field must be str type, connected_roads field must be a list of strings.

    • Remember to implement unit tests for an Intersection class, use hypothesis for tests.

launch_2

  • task_6 (35 points)

    • Create a Vehicle class with id, type, speed, current_route, and current_position class fields.

    • Class must be located in domain/entities.py.

    • The id and type fields must be str type, the speed field must be int type, the current_route field must be list of Intersection, and the current_position field must be Intersection type and optional.

    • Implement the move_to_next_intersection method to update the vehicle's current position.

    • Implement the has_reached_destination method to check if the vehicle has reached its final destination. It has to return the bool type.

    • Remember to implement unit tests for a ** Vehicle ** class and its methods, use pytest for tests.

  • task_7 (35 points)

    • Create a function called vehicle_factory with id, type, speed, current_route, and current_position arguments.

    • The function must be located in domain/entities.py.

    • id and type arguments must be str type, speed argument must be int type, current_route argument must be list of Intersection and current_position argument must be Intersection type and optional.

    • Factory should return the type as a Vehicle class object.

    • Remember to implement unit tests for a vehicle_factory function, use pytest for tests.

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