GPS Toll based System The proposed project aims to automate the toll collection system, eliminating the need for traditional toll gates. This innovative system enhances efficiency compared to the existing manual toll collection methods. By streamlining the toll collection process, it significantly reduces the time required for vehicles to pass through, leading to smoother traffic flow and reduced congestion. This not only saves time for commuters but also contributes to lower emissions due to less idling and stop-and-go traffic. The automated toll system represents a significant advancement in transportation infrastructure, providing a seamless and more effective solution for toll collection. The automation also decreases vehicle emissions caused by idling and frequent stops, contributing to environmental sustainability.
*Note that the attached project is running on simulated Vehicle objects and can be edited to accept real time gps pings from actual vehicles, once all vehicles have the provision to transmit these pings.
Installation process: For main code: (actual project) Download the geojson file for toll road data (can use any geojson file with toll data to scale the program) Download the json file to get vehicle details, or use you can use the cardealershipdb in Visual Studio Code to create and access your own vehicle details database. When using the jupyter program make sure to paste you actual path to the geojson and json files as well as your own google api key. Run the code in jupyter, the output will be printed under the running cell and the map as well as excel sheet with the real time saved data will be found in the directory in which the program is run.
For database provided: (for car dealers to enter vehicle and owner details in a user friendly manner, and it will get converted to json file for running the main code)
Install Visual Studio Code and Node.js. After downloading all the files into cardealshipdb folder, run the server.js and then open the live server to access the front end. Else directly downlaod the customer.json file for the vehicle details.
Basic Markdown Syntax Libraries folium: Interactive maps random: Random number generation json: JSON data handling datetime: Date and time handling shapely.geometry: Geometric operations shapely.ops: Geometric operations geopandas: Geospatial data handling requests: HTTP requests time: Time-related functions
Load GeoJSON Load file and re-project to UTM
Map Initialization Center map around centroid
Add Route Function Adds LineString or MultiLineString routes to map
Add Routes Apply route addition to GeoDataFrame
Save Map Save map to HTML
Nearest Point Function Finds nearest point on routes to GPS ping
Distance Calculation Function Calculates distance between two points
Get Address Function Retrieves address from coordinates using Google Maps API
Vehicle Class Represents vehicle on mapped route Attributes: vehicle_no, owner, bank_account, vehicle_type, current_ping, total_distance, previous_point, marker, api_key Methods: update_marker, update_location, calculate_toll, reset
Track Vehicles Function Tracks multiple vehicles on map
Load Vehicles from JSON Loads vehicle data from JSON file
Initialize Map and Routes Add routes to map
Load Vehicles Load vehicles from JSON file
Add Vehicle Markers Add markers for each vehicle on map
Save Map with Markers Save map with vehicle markers to HTML
Track Vehicles Begin tracking vehicle locations
THIS IS THE PRESENTATION URL: https://docs.google.com/presentation/d/1oDWdpmH7wco0tbfBOPsKAcDaPdVhcfwx/edit?usp=sharing&ouid=102194741991869562597&rtpof=true&sd=true