Bus Arrival Time Prediction System

Bus Arrival Time Prediction System: The ability to obtain accurate predictions of bus arrival time on a real time basis is a vital element to both bus operations control and passengers. This project presents a new system that can be used to predict the expected bus arrival ti

Project Title

Bus Arrival Time Prediction System

Project Area of Specialization

Artificial Intelligence

Project Summary

Bus Arrival Time Prediction System:

The ability to obtain accurate predictions of bus arrival time on a real time basis is a vital element to both bus operations control and passengers. This project presents a new system that can be used to predict the expected bus arrival times at individual bus stops. The bus transport system in Pakistan can be enhanced by providing the real time bus arrival information to the passenger through Bus Arrival Time Prediction System. Such information could reduce passenger’s anxieties while waiting for buses and save them travel time because they can time their arrival at the bus stops more close to the schedule. A number of studies have been initiated in the past to address the bus arrival time prediction problem. These efforts have resulted in these types of prediction models: (a) models based on historical data, (b) regression models, (c) kalman filter based model, and (d) artificial neural network model. We will use ANN model in our project because it provides higher accuracy and good results than the other models which we have mentioned. Artificial neural networks (ANN) that is capable of capturing complex nonlinear relationships. Jeong and Rilett proposed an ANN model for predicting bus arrival times and demonstrated its superior performance compared with other methods. However, ANN models require extensive training and testing in order to find the right network structure and determine the best parameter values. We will also use some Google APIs for the Google maps, routes and some other self-made APIs for the login and admin panel etc.

Project Objectives

Project Objectives:

This project aims to make good arrival time predictions for route with the mobile GPS data using artificial neural networks. Providing real-time bus arrival information can help to improve the service quality of a transport system and enhance its competitiveness among other transportation modes. This project will work by detecting the running route and direction of a bus and predict its arrival time and also guide for the bus routes. A  Smartphone will put in a bus and it will continuously send the bus position to central server. When central server will receive position data from GPS, this module will automatically store the data into related table in server database. When central server received bus position data, based on the latest position data received, this module will process the data and update latest bus arrival time in the main bus timetable. Now with the help of mobile app the user will check on bus arrival time through Internet on the mobile. By applying different self APIs and Google API.s map technology, user will continuously retrieve the latest data from central server and it will display the latest bus arrival time for every bus stop on the mobile application.

It will not only focus on the arrival time but also show all the details regarding buses. Suppose if a person has no knowledge about buses of Karachi he will ask from people and it will waste its time but by using this system he will be able to view the relevant information regarding buses. The only thing which the person has to do is to input his source and destination bus stop and then system will inform all the details of that area’s buses like which bus will go to that particular destination. After selecting any bus user will have the time of bus arrival time at his source bus stop.

Our project will have three major components:

1. Detecting Bus Location:

Using mobile phone’s GPS system the user will get direction and location of the buses.

2. Querying Users:

Querying the bus arrival time for a particular bus route with mobile phones.

3. Backend Server:

To collect the instantly reported information from the GPS and intellectually processing such information to monitor the bus routes and predict the bus arrival time.

Project Implementation Method

The functional requirements of the bus arrival time prediction system are stated below:

1. Admin panel
2. User registration
3. User login
4. Driver login
5. The system must show all the buses names for a particular area.
6. The system must be able to process the position data received from GPS and calculate the estimated time to user.
7. The system must be able to do mapping with the position data retrieved from GPS and show the bus position in a map view to user.
8. The system must be able to show estimated arrival time for every bus in every bus stop.
9. The system must be able to calculate waiting time of bus stop.
10. The system must be able to show information to user in real time.
11. The system should have capability to add/delete and update bus information.
12. If the route of the bus is changed for a particular day only, the map will also show it.

13. The system should allow user to access information in anywhere with anytime.

Benefits of the Project

Benefits of the System:

Public transport especially the bus transport has been well developed in many parts of the world. The bus transport service reduces the private car usage and fuel consumption, and alleviates traffic congestion. As it is one of the most comprehensive and affordable means of public transport. When traveling with buses, the travelers usually want to know the accurate arrival time of the bus. Excessively long waiting time at bus stops may drive away the anxious travelers and make them reluctant to take buses. One of the problems occurring in current bus service is that a person does not know exactly what time a bus will arrive, but only know the scheduled arrival time. People need to wait for a bus without knowing what time the bus will arrive actually. This situation wastes a lot of time because the time wasted can actually spend on other matter. Sometimes there can be dangerous situation when student is waiting on the bus stop and due to delay or missed bus, student might become robbery target. Therefore, to overcome these issues we are going to develop bus arrival time prediction system to give real time bus arrival information to the passenger.

Technical Details of Final Deliverable

Technology used in the Project:

• Neo4j Database:

Neo4j is the world's leading open source Graph Database which is developed using Java technology. It is highly scalable and schema free (NoSQL). A graph is a pictorial representation of a set of objects where some pairs of objects are connected by links. It is composed of two elements - nodes (vertices) and relationships (edges). Graph database is a database used to model the data in the form of graph. Here, the nodes of a graph depict the entities while the relationships depict the association of these nodes. Unlike traditional databases, which arrange data in rows, columns and tables, Neo4j has a flexible structure defined by stored relationships between data records. Neo4j provides a powerful declarative query language known as Cypher. It is easy to learn and can be used to create and retrieve relations between data without using the complex queries like Joins.

• React and React Native:

React (also known as React.js) is an open-source, front end, JavaScript library for building user interfaces or UI components. It is developed and maintained by Facebook. It uses JSX (JavaScript XML) instead of HTML. JSX allows us to write HTML elements in .js files, and translates those HTML tags into React elements. React is designed around the concept of reusable components.

React Native is like React, but it uses native components instead of web components as building blocks.

• Django Framework:

Named after the famous jazz guitarist Django Reinhardt, it is a free and open source web application framework written in Python first publicly released in 2005. Django allows us to build our application’s entire data model in Python without needing to use SQL. Using an object-relational mapper (ORM), Django converts traditional database structure into Python classes to make them easier to work with in a fully Python environment. In Django, our database tables become Python classes. The fields of the database are simply converted into class attributes. Django can manage user sessions; we can add more instances of the application and transfer the user’s experience across the instances without losing data. Django facilitates rapid development and clean, pragmatic design. It helps us quickly produce a web frontend that’s feature-rich, secure, and scalable.

• GPS:

The Global Positioning System (GPS) is a U.S. space provides reliable positioning, navigation, and timing services to civilian users on a continuous worldwide basis available to all. For anyone with a GPS receiver, the system will provide location and time. GPS provides accurate location and time information for an unlimited number of people in all weather, day and night, anywhere in the world. The Global Positioning System (GPS) is a satellite-based navigation system made up of a network of 24 satellites placed into orbit by the U.S. Department of Defense. There are no subscription fees or setup charges to use GPS.

Final Deliverable of the Project

Software System

Core Industry

Transportation

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Required Resources

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