route_optimization.py

import requests

# Module 1: API Integration

def get_real_time_traffic_data(start_point, end_point):
    # Use TomTom API to get traffic data (mock function for demonstration)
    traffic_data = {"traffic_delay": 10}  # Example response
    return traffic_data

def get_weather_data(location):
    # Use AQICN API to fetch meteorological data (mock function for demonstration)
    weather_data = {"temperature": 25, "weather_condition": "Clear"}  # Example response
    return weather_data

def get_route_data(start_point, end_point):
    # Use Google Maps or OSRM API to fetch route details (mock function for demonstration)
    route_data = {"distance": 100, "estimated_time": 120}  # Example response
    return route_data

# Module 2: Route Optimization

def calculate_optimal_route(start_point, end_point, vehicle_details):
    # Fetch data from APIs
    traffic_data = get_real_time_traffic_data(start_point, end_point)
    weather_data = get_weather_data(start_point)
    route_data = get_route_data(start_point, end_point)
    
    # Logic to optimize the route considering traffic, weather, and vehicle details
    optimized_route = {
        "route": f"{start_point} to {end_point}",
        "traffic_delay": traffic_data["traffic_delay"],
        "weather_condition": weather_data["weather_condition"],
        "distance": route_data["distance"],
        "estimated_time": route_data["estimated_time"]
    }
    
    return optimized_route

# Module 3: Emission Calculation

def calculate_emissions(distance, fuel_consumption, emission_factor):
    """
    Calculate vehicle emissions for a given route.
    
    :param distance: Distance of the route (in km)
    :param fuel_consumption: Fuel consumption of the vehicle (L/km)
    :param emission_factor: Emission factor for the fuel type (gCO2/L)
    :return: Estimated emissions in grams of CO2
    """
    emissions = distance * fuel_consumption * emission_factor
    return emissions

# Module 4: User Interface

def user_interface():
    # Get user input for start and end points, vehicle details
    start_point = input("Enter starting point: ")
    end_point = input("Enter destination: ")
    vehicle_details = {
        "type": input("Enter vehicle type (e.g., gasoline, electric): "),
        "efficiency": float(input("Enter vehicle fuel efficiency (L/km): "))
    }
    
    # Calculate optimal route
    route = calculate_optimal_route(start_point, end_point, vehicle_details)
    
    # Calculate emissions
    emission_factor = 2392  # gCO2/L for gasoline, can change based on vehicle type
    emissions = calculate_emissions(route["distance"], vehicle_details["efficiency"], emission_factor)
    
    # Display results
    print(f"Optimal route: {route['route']}")
    print(f"Distance: {route['distance']} km")
    print(f"Estimated travel time: {route['estimated_time']} minutes")
    print(f"Traffic delay: {route['traffic_delay']} minutes")
    print(f"Weather condition: {route['weather_condition']}")
    print(f"Estimated emissions: {emissions} gCO2")

if __name__ == "__main__":
    user_interface()