American-Eurasian Journal of Scientific Research 12 (5): 229-235, 2017

ISSN 1818-6785
© IDOSI Publications, 2017
DOI: 10.5829/idosi.aejsr.2017.229.235

Effective Tracking of Bus Location Using Map Matching Algorithm

1
P. Suganya and 2T. Karthija

1
P.G Scholar, Computer Science and Engineering, VV College of Engineering, Tisaiyanvilai, India
2
Assistant professor, Computer Science and Engineering, VV College of Engineering, Tisaiyanvilai, India

Abstract: Smart phones make the world smarter. A student availing in the college bus may wait for the bus at
the bus stop. Sometimes the student may be late to the stop and they doesn’t know whether the bus have
crossed their boarding point or not. If any path deviation occurs in the route the students doesn’t know which
alternative path should be taken to catch the bus to reach the destination. To overcome these problems an
android application is developed for the students to track the bus location easily. This application needs
student’s details for verifying the authorized students and this application gets the information about the buses
like bus numbers, bus routes for the students. The web server utilize the technology of Location Based
Services, which helps to track the current location of the bus and it estimates if any deviation occurs in the bus
route using the Client-Server technology. Each bus sends its current location to the web server. This
information is stored on the server database. The students who installed the college bus tracking application
can track the bus routes, bus number, bus location and the arrival time of the bus using Kalman filter algorithm.
The bus location is tracked by using global positioning system and the location information is send to the
students in the Google map which reduces their waiting time.

Key words: Android Application Bus location Global Positioning System Google map Real-Time Bus
Tracking

INTRODUCTION tracking device. The two parts work mutually to offer the
most expediency to the users as they become clever to
Vehicle tracking systems were primarily implemented track vehicle locations in real-time.
for the shipping diligence because people wanted to know A vehicle tracking is a prerequisite of the most
where each vehicle was at any specified time. Now-a- fundamental function in all fleet organization systems. A
days, nevertheless with technology mounting at a fast fleet organization is the management of a company’s
pace, automatic vehicle tracking system is being used in transportation navy. The fleet organization aims at
a multiple ways to track and display vehicle locations in improving the excellence and effectiveness of the industry
real-time. This paper proposes a vehicle tracking system by identifying major obstructions on the road and
using GPS expertise and a Smartphone application to tracking real-time locations of their navy on a map [2].
present well again service and charge effective solution Most of the vehicles tracking systems are intended by
for users. using GPS/GSM technology [4]. In vehicle tracking
Smartphone users are now more widespread within systems, a vehicle location is one of the most significant
the overall populace than owners of basic mobile phones mechanisms. The position and time information anywhere
[1]. As Smart phones turn into more familiar to people and on earth is provided by using GPS technology [5].
judgment use in the day to day life, their authority on Systems for monitoring and tracking vehicle progress
society continues to grow. The main driving force for this offer many opportunities for the management of
accelerated growth in Smartphone usage is the transportation systems. The data composed from such
accessibility of a large variety of applications to meet the systems also has the probable to provide a fuller
needs of a wide variety of users. In this project developed understanding of the behaviour of travellers and the price
a Smartphone application beside with the in-vehicle of that behaviour both on the transport system and

Corresponding Author: P. Suganya, P.G Scholar, Computer Science and Engineering, VV College of Engineering,
Tisaiyanvilai, India.
229
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

external effects. This paper reports on a research and Predicting Bus Arrivals Using One Bus Away: Catherine
development project to generate and reveal the M.Baker [12] proposed a one bus away prediction to
capabilities of an accurate, consistent and cost effective improve the experience of riders in the area by providing
real time data collection device, the vehicle concert and real time arrival time of bus. This application provides
emission monitoring system (VCEMS). The VCEMS will good accuracy of arrival time of bus. This method used
be monitor vehicle and driver performance. K-Nearest neighbours to predict multiple values. And it is
help to decrease the root mean square error. This method
Literature Survey use two methods first measure the nearest neighbour
Bus Arrival Time Prediction: Lei Wang, [8] proposed trajectory vehicle. Second, support varying length nearest
two phases first one Radial Basis Function Neural neighbor queries. This technique use to measure the
Network (RBFNN) mode 1, it is used to approximate the history based travel time predictions for vehicles and
non –linear relationship in historical data. The second used to compare the prediction accuracy. In this paper
phase is online oriented method it is used to modify the incremental algorithm is used for efficiency.
RBFNN predict result and adjust the actual situation.
The RBFNN and online adjustment predict to given a Easy Tracker: Automatic Transits Tracking: James
better performance. In this method Kalman filter is using Biagoni [13] proposed a automatic system for transits
to adjust the online data. This method shows the bus tracking to predict the arrival time prediction using
arrival time by using two phases. The RBFNN model gives different algorithm that use GPS traces data collected to
the number of passenger getting on or off, delay, distance determine routes. This proposed method consists of
travel speed between 2 stops. The online filter method collection unit in vehicle and number of online algorithm
shows the speed of real time condition. It is unique and batch data process. Online processing matches
module and it is mainly useful for urban transportation.
vehicle to routes and perform arrival time prediction. This
method is helps to reduce the cost and complexity. In
Real Time Bus Tracking: Transportation plays on
additionally online algorithm is used to predict the arrival
important role for supporting various activities. Putu
time and determine the bus route. This method also
Wina Buana [10] proposed a real time transportation bus
introduces a easy tracker system to reduce the cost and
tracking system help to solve the problems in unexpected
complexity for service. It provides accurate transits
delays and incidents. The movement of bus
tracking and real time arrival time prediction.
transportation provides information to passenger to
estimate the arrival time of bus. This method using a
Bus Monitoring System Allows Polyline Algorithm:
hybrid application technology based on web and mobile
Every country needs an efficient public transportation
application. In real time transmission bus tracking system
develops a administrator application and operator system. So vishual Bharte [16] proposed a technology
application and member application. This application GPS. The Google maps and GPS are also including in this
helps the passenger to make efficient use of time and method. The system include mobile application the user
estimate the arrival time of bus. can able to track the real time bus location on Google
maps and also find out the nearest bus stop by using
Smart Bus Tracking System: Süleyman Eken [11] mobile phones. The data can transferred over GPRS
proposed a smart bus tracking system that any passenger (General Packet Radio Service) and the location tracked
with a smart phone can scan the QR (Quick Response) by using GPS that is early available in mobile application.
codes that was placed in a bus stop. The user can view The system is easy and simple for user to get information
the bus arrival time and also view the bus route on the from Google map.
map with their geographic and non-geographic
attributes. In this method used c4.5 statistical classifier Development of Bus Tracking System: For the most part,
algorithm for to estimate the bus arrival time to minimize every individual sits tight for the transport entry. Because
the passenger waiting time. The Google maps are useful of overwhelming movement, the general population feels
to display the current location of bus on the map to give awkward to contact with their neighbours. The application
the route information. If the user get registered the brings and message benefits over telephone require more
system it show the bus route and arrival time via SMS and cost. Portable based transport following framework was
E-mails. This method helps the user to avoid unnecessary proposed in [17] which help to recover the transport area
waiting time spend in bus stop. without calling or aggravating the individual going in the

230
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

transport. Here the general population boarding the beneficially evaluates customer advancement using a
transport and the organizer of the transport ought to have commitment cycled accelerometer and utilizations
an Android cell phone with web association. The GPS Bluetooth correspondence to diminishing position
which bolsters GSM will report the vehicle data to the shakiness among neighbouring devices. Finally, it uses
server. The data from the server is conveyed to the client cell tower-RSS boycotting to recognize GPS unavailability
to track the transport area. The upside of this strategy is (e.g., inside) and decline turning on GPS in these cases.
that it has high adaptable. The drawback is that the We survey RAPS through genuine trials using a model
traveller does not get the correct area of the transport. execution on a present day propelled cell and exhibit
Framework can be valuable for short separations. Long that it can grow phone lifetimes by more than a part of
separation following won't give exact area of the 3.8 over an approach where GPS is reliably on. The upside
transport. of this procedure is uses Bluetooth correspondence.
It diminishes GPS starts. The bother of this procedure is
Situating For Smartphone the Rate Adaptive the GPS does not work fittingly in urban districts and by
Method: In this system Yamuna investigates, present using Bluetooth office the long detachment can't be taken
RAPS, rate-adaptable arranging system for cutting edge after. It was perceive region in little partition.
cell phone applications. It relies on upon the observation
that GPS is all things considered less correct in urban Proposed Work
reaches, so it suffices to turn on GPS similarly as Objective of Proposed System:
frequently as essential to achieve this precision. This To track the arrival of the bus location more
structure [18] uses a social affair of techniques to accurately.
distinctly choose when to turn on GPS. It uses the region To predict the arrival time of the bus from the
time history of the customer to gage customer speed and boarding point.
adaptively turn on GPS just if the surveyed helplessness To alert the students if any bus route changes
in position outperforms as far as possible. It moreover without proper planning.
profitably evaluates customer advancement using a
commitment cycled accelerometer and utilizations Proposed System Architecture: An Android application
Bluetooth correspondence to diminishing position is developed to provide all required information about bus
insecurity among neighbouring contraptions. Finally, it it gives necessary information about all the buses
uses cell tower-RSS boycotting to recognize GPS travelling in that route. The bus location is displayed on
detachment (e.g., inside) and go without turning on GPS map also.
in these cases. We survey RAPS through genuine trials
using a model execution on a present day propelled cell
and show that it can grow phone lifetimes by more than a
part of 3.8 over an approach where GPS is reliably on. The
burden of this procedure is the GPS does not work
suitably in urban districts and by using Bluetooth office
the long partition can't be taken after. It was perceive zone
in little partition.

Situating For Smartphone the Rate Adaptive

Method: In this paper, we present RAPS, rate-adaptable
arranging system for cutting edge cell phone applications.
It relies on upon the discernment that GPS is all around
less correct in urban reaches, so it suffices to turn on GPS
similarly as routinely as essential to fulfil this precision. Fig. 3.1: System architecture
This system [19] uses a social event of methodologies to
distinctly choose when to turn on GPS. It uses the zone Input will be a bus number and output will be details
time history of the customer to gage customer speed and of the bus location with map. The details about bus
adaptively turn on GPS just if the evaluated weakness in information will be stored in the database and can be
position outperforms as far as possible. It moreover retrieved whenever it is needed. It will be easy for the user

231
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

to access and track the bus location. Whenever the

latitude and longitude values get changed then the
location information will be updated to server database,
so that all changes in the bus timings and the routes are
recorded. The tracker will track the location of the
passenger as well as the bus so that approximate time
required by the bus to reach the stop will be calculated. Fig. 3.2: Schematic of a Bus Route with Several Stops

Modules: This application contains the three modules Assuming that bus n is currently at stop i
Admin module
Student module ATn(i + 1) = DTn(i) + RTn(i,i + 1)
Bus Tracking module
where: ATn(i + 1) is the predicted arrival time of bus n at stop
Admin Module: In this module is used to enter the i+1 RTn(i,i + 1) is the predicted running time between i and
student details such as student name, register number, i+1 from Kalman Filter prediction algorithm DTn(i) is the
date of birth and course source point, destination actual departure time of bus n from stop I.
point etc. This student details can be added, updated
or deleted. This module deals with bus location Bus Module: The bus should have installed the College
details such as location of bus. When the administrator Bus application. Using the Latitude and longitude the
selects the bus number from the dropdown list, the current location of the bus can be found out and the
location will be display. This module can utilize the current location is updated to the server. Corresponding
technology of Location Based Services, which is used to to the bus movement the change in latitude and longitude
track the current location of the bus. The system uses are updated in the database for every minute. Updated
Global Positioning System [GPS], to find information latitude and longitude value in the database is used to
about the location of the vehicle that is to be monitored find the exact location of the bus using Google map. GPS
and then send the latitude and longitude to the System is fixed in Bus which can send the GPS location
monitoring centre through satellite. At the Administration continuouslyIn this module the updated latitude and
application is used to display the vehicle on the Google longitude value in the database is used to find the exact
map. location of the bus using Google map. Android
application should be installed in all the buses for sending
Student Module: This module deals with bus location the location and timing information to the server. Reverse
details such as location of bus. The student selects the Geocoding is point location (latitude, longitude) to a
bus number from the dropdown list; the location of the readable address or place name.
bus will be displayed. The user can easily to track the bus GPS System is fixed in Bus which can send the GPS
location as well as the approximate bus arrival time. In this location continuously to the web server. The user can
module, students are added to this application. Users with install this Application.
this application can track the bus routes and bus number
from source to destination and the current location of the Map Matching Algorithm: The fundamental attributes of
bus. Admin send the notification for bus route gets the Map Matching Algorithm incorporate the utilization
changed. The admin send this notification to the of yield from the GPS Extended Kalman Filter (EKF)
particular bus students. Algorithm, it including position, speed and time. Data on
the vehicle direction is utilized to keep away from sudden
Kalman-Filter Prediction Algorithm: Kalman-Filter exchanging of mapped areas between detached street
Prediction Algorithms is a linear recursive predictive joins.
update algorithm used to estimate the parameters of a The MM process is shown diagrammatically in
process model. Starting with initial estimates, the Kalman Figure 3. The three data sources described above are the
filter allows the parameters of the model to be predicted link and node data and the positioning data. The process
and adjusted with each new measurement. Kalman filter is initiated with nodal matching to identify a correct link
algorithm works conceptually as follows, the historical among all the links connected with the closest node to the
passenger arrival rate is obtained from the data. GPS point and the determinations of the physical location

232
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

of the GPS point on that link. The next step analyzes The above figure shows if bus number gets changed
whether the next GPS point can be matched to the link admin send a notification to the students. This page
identified at the previous step and then determines its contains old and new bus numbers.
physical location on the link. It is vital to carry out the Above figure shows the notification for bus route
first step carefully and reliably, as there could potentially number can be changed. The admin send this notification
be many candidate links. for the particular bus students.

Algorithm Step by Step: The algorithm uses the following Bus Module: In bus module initially installed the college
steps to assign the vehicle on the correct link and to bus application. This application is used to update the
determine its position on that link. bus location changes in server.

Find the closest node from the first GPS point (i.e.,
initial point).
Check whether the next point is an outlier. If not, then
select all the road segments that pass through the
closest node, otherwise take this point as the initial
point and go to step-1.
Using the weighting formula, choose the correct link.
These two points (i.e., initial point and its next point)
should be matched to this link.
Determine the vehicle position on the correct link for
each of the two points.
Check whether the next point is an outlier. If yes,
then go to step-1 and take it as the initial point. If not,
map this point on the same link and determine its
position and continue this process until the above
conditions are true, otherwise go to step-1.
Repeat step-5 until all points has been matched.

Implementation and Result

Admin Module: In this module admin enters the student
details in database and monitor the bus location in Google
map. In case the bus number gets changed, Admin send
notification to those particular bus students. The student
information about register number, student name,
department, course, year of study, semester, date of birth,
email id, mobile number, is a bus student, source and Fig. 4.8: Insert bus number in bus device
destination. These details stored in the database.
Student Module: The student can login to the application
using his/her registration number and date of birth to view
the bus location.

Fig. 4.1: Bus number changes notification Fig. 4.4: bus route changes notification viewed by student

233
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

Above figure shows the notification for bus route CONCLUSION

gets changed. The admin send this notification to the In this proposed system, an Android application is
particular bus students. developed to maintain the student details and to track the
bus location. By using this application the student can
get the location of the bus and if any changes occur in the
bus number immediately the notification is send to the
student to alert that the bus number was changed. When
the student login to this application they can see the
available notification and the bus location in the Google
Map. Further when the people waiting for the bus at the
bus stop and if any bus route changes then immediately
the notification is sent to the particular person who are
waiting for boarding the bus. So that, the particular
person can takes necessary actions to reach their
destination without any time delay.

REFERENCES

1. Aaron Smith, 2012. Nearly half of American adults are

Fig. 4.2: Notification page in student App Smartphone, http:// pewinternet.org/ ~/media/ Files/
Reports/ 2012/ Smart phone%20owne
rship%202012.pdf, 2012
2. Mohammad A. Al-Khedher, 2011. Hybrid GPS-GSM
Localization of Automobile Tracking System,
International Journal of Computer Science &
Information Technology (IJCSIT), 3(6).
3. Saed Tarapiah, Shadi Atalla and Rajaa AbuHania,
2013. Smart On-Board Transportation Management
System Using GPS/GSM/GPRS Technologies to
Reduce Traffic Violation in Developing Countries,
International Journal of Digital Information and
Wireless Communications (IJDIWC) 3(4): 96-105, The
Society of Digital Information and Wireless
Communications, 2013 (ISSN: 2225-658X).
4. Muruganandham, 2010. Real Time Web based Vehicle
Tracking using GPS, World Academy of Science,
Engineering and Techonogy, pp: 37.
5. Ramani, R., S. Valarmathy, N. Suthanthira Vanitha,
S. Selvaraju and M. Thiruppathi, 2013. Vehicle
Tracking and Locking Sytem Based on GSM and
GPS, I.J. Intelligent Systems and Applications,
09: 86-93.
6. Kiran, G., Kumar, A. Mallikarjuna Prasad, 2012. Public
Transportation Mangement Service using GPS-GSM,
International Journal of Research in Computer and
Communication Technology, IJRCCT, ISSN- 2278-
Fig. 4.5: Student view bus location in Google map 5841, Vol-1, Issue -3, Aug - 2012.
8. Wang, Lei, Zhongyi Zuo and Junhao Fu, 2014. Bus
Figure shows the student can view the bus Arrival Time Prediction Using RBF Neural Networks
location using Google map that was displayed in the Adjusted by Online Data. Procedia-Social and
Google map. Behavioral Sciences, 138: 67-75.

234
 Am-Euras. J. Sci. Res., 12 (5): 229-235, 2017

9. Azevedo, Carlos Lima, João Lourenço Cardoso and 15. Chaturvedi, Manish and Sanjay Srivastava, 2013. Real
Moshe Ben-Akiva, 2014. Vehicle tracking using the k- time vehicular traffic estimation using cellular
shortest paths algorithm and dual graphs. infrastructure, Advanced Networks and
Transportation Research Procedia 1.1: 3-11. Telecommuncations Systems (ANTS), 2013 IEEE
10. Buana, Putu Wira, et al., 2016. Real Time Trans Bus International Conference on. IEEE, 2013.
Tracking and Passenger Information System using 16. Mulla, Afshan, et al., 2015. GPS assisted Standard
Hybrid Application Technology. International Positioning Service for navigation and tracking:
Journal of Software Engineering and Its Applications, Review & implementation, Pervasive Computing
10.9: 35-50. (ICPC), 2015 International Conference on. IEEE, 2015.
11. Eken, Suleyman and Ahmet Sayar, 2014. A smart bus 17. Bharte Vishal, et al., 2014. Bus Monitoring System
tracking system based on location-aware services Using Polyline Algorithm."International Journal of
and QR codes, Innovations in Intelligent Systems Scientific and Research Publications, 4.4.
and Applications (INISTA) Proceedings, 2014 IEEE 18. Lee, SeokJu, Girma Tewolde and Jaerock Kwon.
International Symposium on. IEEE, 2014. "Design and implementation of vehicle tracking
12. Baker, C.B. and Alexander C. Nied, 2014. Predicting system using GPS/GSM/GPRS technology and
bus arrival using One Bus Away real-time data. smartphone application." Internet of Things (WF-
13. Biagioni, James, et al., 2011. Easytracker: automatic IoT), 2014 IEEE World Forum on. IEEE, 2014.
transit tracking, mapping and arrival time prediction 19. Kannaki@vasanthaazhagu, A., N. Vijayalashmy,
using smartphones. Proceedings of the 9th ACM V. Yamuna, G. Rupavani and G. Jeyalakshmy, XXXX.
Conference on Embedded Networked Sensor GNSS based bus monitoring and sending SMS to the
Systems. ACM, 2011. passengers, proceedings of international conference
14. Anderson, Ruth E., et al., 2009. Building a on global innovations in computing technology
transportation information system using only GPS (ICGICT’14).
and basic SMS infrastructure. Information and 20. Sujatha, K., P.V. Nageshwara Rao, K. Sruthi,
Communication Technologies and Development A. Arjuna Rao, 2014. design and development of
(ICTD), 2009 International Conference on. IEEE, Android mobile based bus tracking system, 978-1-
2009. 4799-3486-7/14/$31.00_c 2014 IEEE

235