Optimal Traffic Route Finder System

M.MONICA BHAVANI 1 Dr.A.VALARMATHI 2

1(Department of CSE, Anna

University,BIT Campus,Trichy,Tamilnadu,India)

2(HOD,Department of MCA, Anna

University,BIT Campus,Trichy,Tamilnadu,India)

[email protected], [email protected]

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Abstract

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.

Keywords: shortest

path,Geographical Information System,optimal route,real time traffic

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1.

Introduction

T

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 improvement in the

geographic information systems (GIS) technology it is much possible in order to

calculate the fastest & optimized route that can be found with the help of

GIS. This is because a path on a real road network in the city to have the various

different levels of the traffic at different time periods of the day and it is not at all an easy task to

locate the shortest path. Thus, the fastest & optimal path can only be calculated

in the real time. In some of the cases, the fastest & optimal route has to

be calculated in a various other ways. Whenever the larger area of road

networks are involved in any of the application, the calculation of shortest

paths & optimal path on a larger network can be computationally very tough because

some of the applications are involved are to find the optimal path over the

road networks.

With the help of the geographic

information systems (GIS) and the GPS logs of information needed in the

real-time are dynamic, the changing information have been collected has become

a common practice in many of such applications.The usage of the application of

this paper is to provide that the real-time traffic information of the system

integrated with the historical data are used to develop various routing

strategies in order to provide both the travel time between the source to

destination & the fuel consumption of the travelling cost.This paper is to

develop the new algorithm for to reduce the travelling time and cost between

the every source & destination by providing an optimal routing path .

We therby likes to

propose a fastest & an optimal transportation path routing algorithm called

modified Dijkstra’s algorithm with the fuzzy logic in order to select the

various different routing paths that defines to these conditions. Thus, we present

an approach to provide the implementation of the proposed algorithm to an

optimal road transportation routing system where it will be integrated with GIS

providing real-time traffic flow of information.Thus,we consider getting a

shortest path problem on a road network with the various travel times where the

resultant paths are observed for traffic flow in a dynamical way with the help

of GIS.This proposed algorithm is designed in a manner to provide the optimal fastest

path by using the fuzzy logic in selecting the next shortest path for every

source to 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 which is the extended work of

the paper 8 to determine the special case where network taffic status updating

is completely available to all the vehicle drivers. The regular state space

compression technique for the dynamic & flexible stochastic optimal path

problems are with real-time traffic information which is provided to efficiently

increase the computational and the implementational processes. This paper is an

extended work of the paper5 and here to determine the different issues that

are combining the vehicle routing with the various real-time traffic flow

informations from Geographical Information System.

3.Problem

Statement

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 optimal path problem has been

immensely examined in the literature that this paper 2 gives an modified

Dijkstra’s algorithm is used to calculate the minimum cost for the route in a

network which is static.The paper 3 showed that standard shortest path

algorithms (such as Dijkstra’s algorithm 16) do not find the minimum expected

weight path on a non-stationary or a stochastic network which is dynamic and

that the optimal path chosen can’t be calculated as a simple path but examined

based on constraints.This is why because there are many dynamic parameters

which require constraint-based decision making using the fuzzy logic systems.

4.Methodology

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

information.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

purpose.

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.

GPS datasets

GIS Database

Fuzzy Routing Algorithm

Optimal Path Selection

Route Mapping using

GIS

Real time Traffic

Fig.Methodology Diagram

The working of this methodology is done with the help of the fuzzy

condition based modified Dijkstra’s algorithm.The

methodology diagram above provides the implementation steps of the algorithm which

dynamically updates the real time traffic information with that of the

historical collection of the data (GPS logs) which can be collected from the GPS enabled vehicles. The

new algorithm has been proposed which is the fuzzy based modified Dijkstra’s algorithm

as Fuzzy Routing Algorithm(FRA).

5. Fuzzy

Routing Algorithm

The fuzzy based routing algorithm first calculate the intensity of the

road traffic within the city for every source and the destination.This can be

done with the help of the historical dataset which are GPS logs for a

particular city and the real time traffic information.The fuzzy logic is to

provide the details regarding the intensity estimation of every road segment.

ALGORITHM FRA(G,R,C, ingress,

egress, b)

Notation

G = G(N,L) = Input Graph.

R

= Set of link residual bandwidth ri

C = Set of link capacities ci.

ingress = Ingress node.

egress = Egress node.

b = Bandwidth demand.

Pathy = Set of nodes in the path from ingress to node y

Begin

1.

Remove all links which does not

satisfy bandwidth constraint “b” from

G

2.

Run Dijkstra’s Algorithm to

calculate Hmin for each

node

3.

P = {}, Pathy ={} ?y, mringress=1,

and mri = 0 ?i ? ingress.

Loop

4. Find x ? P such that mrx is maximum ?x? P;

5. P = P U {x}. If P contains egress then exit loop;

Loop

6. ?y? P having a link xy Update

test y = ? × min ( pxy ,lxy ,hxy ) + (1- ?) ×1/3( pxy ,lxy ,hxy )

If testy > mry

then Pathy = Pathx U {x};

m ry = max(m ry ,test

) ; End If

y y y

End Loop

End Loop

7.

Return Pathegress

8.

End FRA

6. Implementation

The implementation of this work is to provide the optimal and the

shortest path based on various kinds of conditions like traffic intensity

estimation, cost of the travelling path, shortest in time to reach the

destination and so on. This can be done with the help of the modified dijkstra’s

algorithm and the application of fuzzy logic. The modified dijkstra’s algorithm

based on fuzzy logic is to find the shortest and an optimal path to every

source and the destination.This algorithm

is proposed as the Fuzzy Routing Algorithm(FRA).

·

The various implementation steps

of this process are

·

Collection of the datasets which

are the historical datasets from the GPS logs.

·

Integration of the real time data

of traffic information

·

Formation of the GIS database

·

Execution of the fuzzy based routing

system which provides the traffic intensity estimation which is the application

of the fuzzy logic

·

Finding an optimal route between

the source and the destination.

Fig. 1 . Shortest

path computation using Fuzzy Routing Algorithm (FRA).

5. Conclusion

This paper gives an approach for providing an optimal routing in

transportation system and that is combined with GIS technology that provides the

real-time changing & dynamic traffic flows.We have observed that when there

are number of paths for the same source to same destination increased with

real-time dynamic traffic flow information, thus 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

congestion.

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.

References

1

Bander, J. & White, C., “A heuristic

search approach for a nonstationary stochastic shortest path problem with terminal

cost”, Transportation Science, 2002, 36, 218 – 230.

2

Fan,

Y.; Kalaba, R. & Moore, I., “Shortest paths in stochastic networks

with correlated link costs”, Computers & Mathematics with Applications,

Elsevier, 2005, 49, 1549-1564

3

Delling,

D. & Wagner, D., ” Time-Dependent Route Planning”, Robust and

Online Large-Scale Optimization, Springer, 2009, 5868, 207-230.

4

Hashemi,

S.; Mokarami, S. & Nasrabadi, E., “Dynamic shortest path problems with

time-varying costs”, Optimization Letters, Springer, 2010, 4, 147-156.

5

Kim,

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.

6

Likhachev,

M.; Ferguson, D.; Gordon, G.; Stentz, A. & Thrun, S., “Anytime search

in dynamic graphs”, Artificial Intelligence, Elsevier, 2008, 172,

1613-1643.

7

Opasanon,

S. & Miller-Hooks, E., “Multicriteria adaptive paths in stochastic,

time-varying networks”, European Journal of Operational Research,

Elsevier, 2006, 173, 72-91.

8

Psaraftis,

H. & Tsitsiklis, J., “Dynamic shortest paths in acyclic networks with

Markovian arc costs”, Operations Research, JSTOR, 1993, 41, 91-101.

9

Feldman,

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.

13

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.

14

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.

15

Viswarani.C.D,Vijayakumar.D,Subbaraj.L,S.Umashankar,Kathirvelan.J,”Optimization

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

16

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