Real time path planning based onhybrid-vanet-enhanced transportation system

CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: sunsid1989@gmail.com, praveen@nexgenproject.com
Web: www.nexgenproject.com, www.finalyear-ieeeprojects.com
REAL-TIME PATH PLANNING BASED ONHYBRID-VANET-ENHANCED
TRANSPORTATION SYSTEM
ABSTRACT
Real-time path planning can efficiently relieve trafficcongestion in urban
scenarios. However, how to design an efficientpath planning algorithm to achieve
a globally optimal vehicle traffic control still remains a challenging problem,
especiallywhen we take drivers’ individual preferences into consideration.In this
paper, we first establish a hybrid intelligent transportationsystem (ITS), i.e., a
hybrid-VANET-enhanced ITS, whichutilizes both vehicular ad hoc networks
(VANETs) and cellularsystems of the public transportation system to enable real-
timecommunications among vehicles, road-side units (RSUs), and avehicle-traffic
server in an efficient way.
we propose areal-time path planning algorithm, which not only improves
theoverall spatial utilization of a road network but also reducesaverage vehicle
travel cost for avoiding vehicles from gettingstuck in congestion. Stochastic
Lyapunov optimization techniqueis exploited to address the globally optimal path
planningproblem. Finally, the transmission delay of the hybrid VANETenhancedITS
is evaluated in VISSIM to show the timeliness ofthe proposed communication
framework. Besides, system-levelsimulations conducted in Java demonstrate that

the proposedpath planning algorithm outperforms the traditional distributedpath
planning in terms of balancing the spatial utilization anddrivers’ travel
cost.Proposed system:Specifically, the contributions ofthis paper are threefold:•
First, to facilitate the application of real-time path planning,we propose a hybrid-
VANET-enhanced ITS framework,exploiting both the VANETs and the public
transportationsystem. Based on the proposed hybrid ITSframework, a multi-hop
message forwarding mechanismis designed to collect the real-time traffic
informationor the emergent warning messages, which usually havestrict delay
bounds. A theoretical analysis on the end-toendtransmission delay performance
of the mechanism ispresented as well;• Second, we design a real-time global path
planningalgorithm to not only improve network spatial utilizationbut also reduce
average vehicle travel cost per trip. A lowcomplexityalgorithm is developed based
on Lyapunovoptimization to make real-time path planning decisions.With the
proposed path planning algorithm, the tradeoffbetween the overall network
spatial utilization and drivers’preferences can be well balanced; and• Finally, the
transmission performance of the hybrid-VANETs is first evaluated under different
vehicle densitiesvia VISSIM, and then extensive simulations validatethe
effectiveness and efficiency of the proposed pathplanning algorithm. The results
confirm that our proposedpath planning algorithm is able to find alternative

pathsfor vehicles to bypass congestion areas while reducing theaverage travel
cost in an efficient, timely and coordinatedway.
EXISTING WORK:
Traffic congestion, caused by unbalanced traffic flow or asudden
accident/incident, can cause late arrivals and additionalcost for drivers and
becomes a major problem in the transportation.However, this cost due to traffic
congestion can bereduced by route navigation or path planning with
congestionavoidance. For example, the paths of vehicles can be replannedwith
the shortest-path-based global positioning system (GPS)navigation [15], the
accident duration prediction [16] and theroute reservation in advance [17].
However, these approachescannot make quick response to an emergency or
congestiondue to a sudden accident, since a timely update on the
trafficconditionis lacking. Thus, the real-time traffic informationbecomes
indispensable to support the vehicular real-time pathplanning algorithm.To
collect time-varying traffic-condition information, mostexisting works in
conventional ITS usually rely on cellularsystems or loop detectors. In [18]–[21],
cellphones or mobilesensors with cellular access have been investigated to
collectreal-time traffic information for traffic forecast or reconstructionin
experimental research. In [8], authors introduceatraffic management systemwith
loop detectors for continuoustraffic measurement and monitoring along arterials.

However,inevitable drawbacks cast a shadow on the application ofcellular
systems and loop detectors. For cellular systems, asthey are not dedicated for
traffic data collection, the collectionservices can be highly costly; the high volume
of trafficdata may also cause congestion for other cellular services.For the loop
detectors, the deployment expense can also bevery high. Besides, the inaccuracy
of position measurementbecomes a problem for short-distance transmissions
especiallyin dense networks, which will degrade the performance of pathplanning
[22], [23].
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System : Pentium IV 2.4 GHz.
 Hard Disk : 40 GB.
 Floppy Drive : 1.44 Mb.
 Monitor : 15 VGA Colour.
 Mouse : Logitech.
 Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
 Operating system : Windows XP/7/LINUX/UBUNTU

 Implementation : NS2
 NS2 Version : NS2.2.28
 Front End : OTCL (Object Oriented Tool Command
Language)
 Tool : Cygwin (To simulate in Windows OS)
CONCLUSIONS
In this paper, we have developed a hybrid-VANET-enhancedreal-time path
planning for vehicles to avoid congestion inan ITS. We first propose a hybrid-
VANET-enhanced ITSframework with functionalities of real-time traffic
informationcollection, involving both V2V and V2Rcommunications inVANETs and
cellular communications in public transportationsystem. Then, a globally optimal
real-time path planningalgorithm is designed to improve overall spatial
utilizationand reduce average vehicle travel cost, by means of
Lyapunovoptimization. Extensive simulations have been conducted
todemonstrate that the proposed path planning algorithm canachieve better
performance than that without real-time pathplanning in terms of average
moving delay as well as theadaptability to different accident durations and traffic
densities.In our futurework, we intend to find large-scale real-worldvehicle traffic
traces to further validate benefits of the proposedalgorithmin practical scenarios.

REFERENCES
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[8] A. Skabardonis and N. Geroliminis, “Real-time monitoring and controlon
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