M.MONICA BHAVANI 1 Dr.A.VALARMATHI 21
1(Department of CSE, Anna
2(HOD,Department of MCA, Anna
The main aim of this Traffic route finder
system is to reduce the number of re-computations for finding optimised route
and alternate routes. This is to obtain less memory consumption & less
wastage of resources that results in minimal response times.On the development
of Intelligent Transport System (ITS), this increasing intensive on- demand of
routing guidance system in the real time coincides with increasing growth of
roads in the real world. This paper is about the values of the real-time
traffic data obtained for arrving at an optimal vehicle routing solution within
a dynamic transportation networks.Our proposal is to implement an optimal
vehicle routing algorithm in order to incorporate the dynamically changing
traffic flows.Thus we present a dynamic approach in selecting the paths for the
implementation of our proposed algorithm for the effective road traffic
transportations routing system by providing dynamically changing traffic flow
of information & the historical data using GIS.
path,Geographical Information System,optimal route,real time traffic
HIS paper gives the
optimal traffic routes for the road traffic using the Geographical Informatiob
Syatem(GIS).The method has been determined for the calculation of shortest path
using the modified Dijikstra’s algorithm with the usage of the fuzzy logic.The
dijikstra’s algorithm is the frequently used shortest path calculating
algorithm so far.The fuzzy logic is used
with the dijikstra’s algorithm in order to find out the various other paths of
the source node to the destination node to be selected with the various weights
of the paths to be found.
With the development of
geographic information systems (GIS) technology this is much possible to calculate
the fastest route can be found with the assistance of GIS. Because a path on a
real road network in a city tends to have various levels of traffic during
different time periods of a day, and it is not an easy task to locate a
shortest path. Hence, the fastest path can only be calculated in real time. In some cases the fastest route
has to be calculated in a few other ways. Wherever the large area of road
networks are involved in the applications, the calculation of shortest paths on
a large network can be computationally very tough because of the applications
are involved are to find the shortest path over the road networks.
With the geographic
information systems (GIS), and the usage of GPS log of information,the
real-time & dynamically changing information that have been collected has become
a common practice in many of the applications. The application of this paper is
to show that the real-time traffic information of the system combined with the
historical data are used to develop the various routing strategies in order to
improve both the travel time & the fuel consumption of the travelling cost
measures.This paper is about to develop the new algorithm for to reduce the
travelling time and cost by providing an optimal routing path for every source
We hereby propose an
optimal transportation routing algorithm called modified Dijkstra’s algorithm
with the fuzzy logic in order to select the various routing paths that caters
to these constraints. We also present an approach to get the implementation of
our proposed algorithm for an optimal road transportation routing system which
could be combined with a GIS providing real-time traffic flow of information. We
consider providing a shortest path problem on a road network with travel times where
the paths are observed for traffic flow dynamically with the help of GIS.The
proposed algorithm is designed to provide the optimal path by the fuzzy logic
in selecting the next shortest path to reach the destination.
2. Related Work
The shortest path problem finding with the
lower or minimal cost and time from a source to a destination is the fundamental
problem in the path finding in a road network.Most of the papers deals with the
finding of the shortest path with the algorithms like Bellmann ford,Dijkstra’s
etc for the traffic routing between source and destination.Our problem is to
find the shortest path with the more optimal algorithms like Dijkstra’s.Many of
the literatures talk about the Dijkstra’s algorithm is best suited for the
shortest path calculation.From the dijkstra’s algorithm,most of the
advantageous parts are obtained for creating this new algorithm called modified
Dijkstra’s algorithm with fuzzy logic for the decision making part of finding
the next shortest destination path to be selected as an optimal route to find
the destination by considering the dynamic traffic flows information and so on.
Traffic congestion can be of two types
Recurring traffic and non-recurring traffic.Recurring traffic is the place
where the traffic occurs all the time and thus they can be easily
predictable.But the non-recurring traffic is the place where the traffic occurs
at sometimes which can not be predictable by most of these systems to provide
the most optimal path slection in between a source and destination.
The development of the communication has
bring the dynamic routing to a reality by providing the Geographical
Positioning System (GPS) for positioning the traffic flows and the Geographical
Information System(GIS) to map the features of the traffic routing system.
The paper 5 extended the work of the paper
8 to examine the case where the network taffic status is available to the vehicle
driver. Systematic state space reduction techniques for dynamic stochastic
shortest path problems with real-time traffic information were provided to efficiently
improve computation and implementation processes. This paper is an extension of
the paper5 and we determine the various issues integrating vehicle routing
with real-time traffic flow information from GIS.
The shortest path calculation is the main
problem in the transportation network.Our aim is to create a shortest path
algorithm which is more advantageous than the other algorithms for calculation
of shortest path.This calculation contains various constraints. Some of them
are real-time traffic information that is of the dynamic traffic flows and
time-dependent information that is available.In the dynamic transportation
network, the network can be of dynamic traffic flow of information with the
network path weight changes can be of either deterministic or the stochastic
dynamic network which is dynamic.
The shortest path problem has
been immensely examined in the literature that. The paper 2 gives an optimal
Dijkstra’s type algorithm can be used to compute the minimum weight for the
route in a static network. The paper 3 showed that standard shortest path
algorithms (such as Dijkstra’s algorithm 16) do not find the minimum expected
cost path on a non-stationary or dynamic stochastic network and that the
optimal route choice cannot be computed as a simple path but determined based
on a policy. This is because there are many dynamically varying parameters that
require policy-based decision making using the fuzzy logic systems.
The methodology deals with the various
constraints and characteristics of the dynamic traffic flow of the information
like the time dependent traffic flow of information which is dynamic and the
historical informations which are the GPS datasets of the road traffic
The methodology is to collect the GPS
datasets of the information from the vehicles which traverse through the
various parts of the city.The routes of the whole city can be noted down for a
weeks time. This traffic information is gathered from the GPS dataset which is
noted down with the timing constraints and it is transformed into a GIS
database.From this GIS database, the traffic flow of information is gathered
which is able to detect the traffic in the peak hours and the weekends where
the traffic values are high and low respectively.
From this GIS database,the shortest path is
calculated with the various clustering techniques and with the proposed
algorithm which is Modified Dijkstra’s algorithm using fuzzy logic is used in
order to detect the traffic route from the source to destination. The
clustering techniques uses the time constraints and the distance of the travel
time of the vehicles and thus the optimal shortest path is calculated with the
modified Dijkstra’s algorithm using fuzzy logic for the decision making
The shortest path calculated from these
techniques and algorithm has to be mapped with the GIS softwares for the
visualization of the results of the specific regions.This methodology provides us
with the optimal traffic route.
This paper provides an approach for the implementation of an optimal
routing system for the transportation that is combined with GIS technology that
provides real-time changing traffic flows.We observe that when the number of
paths for the same source to destination
increases with real-time traffic information, the finding of an optimal
routing path for the changing traffic flows is predictable based on the
decision making process using the fuzzy logic technique..Hence,our algorithm
based on the shortest path calculation has been possible with the modified
Dijkstra’s algorithm with the fuzzy logic.Our conclusion is that real-time
traffic information from GIS which is incorporated
can significantly reduce expected costs and usage of the vehicle during times of heavy
6. Future Work
Our aim is to work on with the real-time
traffic flow of information to obtain the optimal traffic information using GIS
by dynamically changing values of information.This will be providing us only
with the dynamic time to time varying dependent informations with the real time
traffic flows.This scenario will be created as an application with the most
optimal shortest path.
Bander, J. & White, C., “A heuristic
search approach for a nonstationary stochastic shortest path problem with terminal
cost”, Transportation Science, 2002, 36, 218 – 230.
Y.; Kalaba, R. & Moore, I., “Shortest paths in stochastic networks
with correlated link costs”, Computers & Mathematics with Applications,
Elsevier, 2005, 49, 1549-1564
D. & Wagner, D., ” Time-Dependent Route Planning”, Robust and
Online Large-Scale Optimization, Springer, 2009, 5868, 207-230.
S.; Mokarami, S. & Nasrabadi, E., “Dynamic shortest path problems with
time-varying costs”, Optimization Letters, Springer, 2010, 4, 147-156.
S.; Lewis, M. & White III., “C. “State space reduction for non
stationary stochastic shortest path problems with real-time traffic information”,
IEEE Transactions on Intelligent Transportation Systems, 2005, 6, 273-284.
M.; Ferguson, D.; Gordon, G.; Stentz, A. & Thrun, S., “Anytime search
in dynamic graphs”, Artificial Intelligence, Elsevier, 2008, 172,
S. & Miller-Hooks, E., “Multicriteria adaptive paths in stochastic,
time-varying networks”, European Journal of Operational Research,
Elsevier, 2006, 173, 72-91.
H. & Tsitsiklis, J., “Dynamic shortest paths in acyclic networks with
Markovian arc costs”, Operations Research, JSTOR, 1993, 41, 91-101.
R. & Valdez-Flores, C., “Applied probability and stochastic
processes”, Springer, 2010.
10 Cherkassky, B.; Goldberg, A. & Radzik,
T., “Shortest paths algorithms: theory and experimental
evaluation”,Mathematical programming, Springer, 1996, 73, 129-174..
11 Dial, R., “Algorithm 360: Shortest-path
forest with topological ordering H”, Communications of the ACM, ACM,
1969, 12, 632-633.
12 Zeng, W., “Finding shortest paths on
real road networks: the case for A*”, International Journal of Geographical
Information Science, Taylor & Francis, 2009, 23, 531-543.
Amrita Sarkar, G.Sahoo, and U.C.Sahoo “Application Of Fuzzy Logic In
Transport Planning”, International Journal on Soft Computing (IJSC) Vol.3,
No.2, May 2012.
Sasikala K.R., Petrou M., Kittler J “Fuzzy Classificationwith A GIS As
An Aid To Decision Making”, University of Surrey,
Guildford, Surrey GU2 5XH, U.K.
On Shortest Path Finding For Underground Cable Transmission Lines Routing Using
GIS”, Journal of
Theoretical and Applied Information Technology,31st July 2014. Vol. 65 No.3
Ammar Alazab, Sitalakshmi Venkatraman, Jemal Abawajy, and Mamoun Alazab
“An Optimal Transportation Routing Approach using GIS-based Dynamic Traffic
Flows” 2011 3rd International Conference on Information and Financial
Engineering,IPEDR vol.12 (2011) © (2011) IACSIT Press, Singapore
1 Dr.A.VALARMATHI,HOD,Department of MCA, Anna University,BIT Campus,Trichy,Tamilnadu,India