- Open Access
- Authors : Sree Sai Priya
- Paper ID : IJERTV10IS080203
- Volume & Issue : Volume 10, Issue 08 (August 2021)
- Published (First Online): 30-08-2021
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Solution for Traffic Congestion to Prevent Accidents in Vehicular Ad-Hoc Network
Sree Sai PriyaÂ¹
Computer Science Department,
Jawaharlal Nehru Technological University, Anantapuram, Andhra Pradesh, India.
Abstract–Vehicular adhoc network is a part of mobile ad hoc network which is unstructured formation wireless network for the transmission of data to field vehicles. In existing system , the last few years ago the invention of mobile networks given a new experience to drive the vehicle on roads high ways by reducing risk of accidents and also road accidents and traffic congestion increases a number of technical challenges such as improving VANET connectivity and current application in the network of vehicular ad hoc network . In proposed system to improve connectivity betweenvehicle to vehicle as long as they are connected with urban areas andhighways to reducing the road accidents by applying to corresponding nodes which are connected vehicle network and vehicle to vehicle infrastructure. To enhance VANET connectivity with the help of some different paths, with the help of some different simulation, The Project analyzed number of parametersincluding vehicle density, message delay and RSU communication. The different protocols to avoid hidden node problems. The communication is fast moving between two nodes the message transferred to another vehicle without delay and receiver responds immediately, in this hidden node problem is decreased for simulation purpose use interface with NETSIM.
Keywords VANET,MANET SUMO,NETSIM.
In recent times, the use of VehicularAd Hoc Networks (VANETs) for safe driving support systems is gaining attention. Using VANETs, vehicles canconfigure the network and communicate with each other without infrastructure support. Using the aforementioned vehicle-to-vehicle communication effectively, road traffic safety and transportation efficiency can be improved. For example, in the Cooperative Collision Warning (CCW) application, periodic information exchange among vehicles, such as their location and speed, is used bya decision making module to assess possible accident situations and warn drivers about these in advance. Similarly, in the case of Congested Road Notification(CRN) applications, vehicles can alert vehicles and road-side units in other regions about road congestion to allow for route and trip planning ensuring acomfortable drive.
Many VANET applications use broadcast communications to transmit information to surrounding vehicles in the network. Further, when a vehiclebroadcasts a message, the surrounding vehicles that receive the message mightattempt to relay the message further by rebroadcasting it. Although broadcasting is an effective way to disseminate data to a large number of vehicles, it can lead to some problems in certain situations. For example, when all vehicles in a high vehicle density area broadcastsimultaneously, a large number of broadcast transmissions are generated, which lead to redundant broadcasts, packet collision, and contention among vehicles. This is called Broadcast Storm Problem.
The Storm Problem is also important in the case of real-time vehicle visualization, which requires frequent exchange of location information among vehicles. Vehicle visualization is an effective way to support safe driving, because depicting hidden vehicles on navigation maps of in- vehicle display devices can strongly compensate for the restricted view field of the driver, and this can lead to lesser accidents caused because of the driverslimited view. Furthermore, at a crowded intersection or a narrow road with an unclear path, it is difficult to detect surrounding vehicles using only on-vehiclesensors and cameras.
The VANET topology changes rapidly because of the high mobility of vehicles, which serve as network nodes. To support highspeed and reliable communication, VANETs need quick delivery of packets while coveringa wide transmission range. For this reason, broadcasting is an effective approach to disseminate information in VANETs. A variety of broadcasting algorithms exist, such as probability based, location based, andcluster based algorithms.
A Decision Making Module for Cooperative Collision Warning Systems Using Vehicular Ad-Hoc Networks(VANET) communication for cooperative collision warning system can increase safety, convenience and efficiency in driving. Intelligent vehicles can collect information about the driving environment, the driver situation and more importantly other vehicles' information using wirelesscommunication. However, deciding what data to considered, what data to ignore and if and what action should be taken in different situations is a significant issue. In this work, we explore the use of a decision making
module for accident situations which processesinformation from VANET communication andadvises the driver based on the situation.
Our decision making algorithm is a simpleand effective algorithm that can be implement in each vehicle to assist the driver in certainsituations. Rerouting to avoid traffic congestion caused by the accident is the major part of our decision making algorithm. This module has been implemented and evaluated using the Veins simulation.
Towards Characterizing and Classifying Communication-based Automotive Applications from a Wireless Networking PerspectiveTogether, the Dedicated Short Range Communication (DSRC) and Vehicular Ad Hoc Network (VANET) technologies providea unique opportunity to develop various types of communication-based automotive applications. To date, many applications have been identified by the automotive community.
Given the large number and diverse nature of these applications, it is advantageous to develop a systematic classification methodology to facilitate future DSRC and VANET research. Toward this objective, we present a study that goes through two major steps: characterization and classification. First, we focus on a rich set of representative applications and characterize them withrespect to plausible application- and networking-related attributes.
The characterization process not only strengthens our understanding of the applications but also sets the stage for the classification step since it reveals numerousapplication commonalities.
Thus, we havecategorized the given applications into seven generic classes, with the consideration of balancing the trade-off between exploiting as many application similarities as possible whilepreserving their salient differences.
In existing system cannot detect hidden vehicles, e.g., vehicles behind othervehicles or structures, which can pose an added risk. In this section, we propose the vehicle visualization system that displays surrounding vehicles on a map on an iOS device, including those hidden by other vehicles or building features. The purpose of this system is to complement thedrivers view field and extend the visual range of the driver with respect to approaching vehicles.
The vehicle visualization system and describe the optimization mechanism used in the system. we present the results of the evaluation of our proposed system we provide concluding remarks for our study.
The proposed system is intended to support safe driving by displaying the surrounding vehicles on a map on an iOS device. In addition, this system implements an optimized mechanism to reduce broadcast packets used for vehicle visualization. We evaluate the proposed system using a real-world VANET experiment. Thi is structured as follows. In Section II, we introduce some of thebroadcast algorithms used in VANETs. In we propose the vehicle visualization system and describe the optimization mechanism used in the system. In Section IV, we present the results of the evaluationof our proposed system.
We discussed the advantage of the cancellation mechanism in. we discuss the negative impact of the cancellation mechanism.
To evaluate the negative impact, we investigate the importance of canceled location information
UML stands for Unified Modeling Language. UML is a standardized general- purpose modeling language in the field of object-oriented software engineering.
The standard is managed, and was created by, the Object Management Group.
Provide users a ready-to-use, expressivevisual modeling Language so that they candevelop and exchange meaningful models.
Provide extendibility and specialization mechanisms to extend the core concepts.
Be independent particular programminglanguages and development process.
Provide a formal basis for understandingthe modeling language.
Encourage the growth OO tools market.
Support high level development conceptssuch a collaborations,frameworks, patternsand components.
Integrate best practices.
Fig (1)SUMO-NETSIM- INTERFACING
. Its purpose is to present a graphical overview of the functionality provided bya system in terms of actors, their goals (represented as use cases), and any dependencies between those use cases. Themain purpose of a use case diagram is to show what system functions are performedfor which actor. Roles of the actors in the system can be depicted.
SUMO file is a combination of Edge and node file, network file vehicles route file SUMO configured file is called a mobility file. Final mobility file of SUMO is given input for NETSIM. NETSIM Simulate Result with help of SUMO mobility file
SUMO Basically it is an open- source software for traffic simulation. Thisparticular sumo helps in the controlling of the traffic simulation and it provides easement to the command of the certain routes and the departure times of vehicles. By the help of this software we design a VANET path for urban areas and also we export the map with the help of an open street map.
NETEDIT-It is a visual network editor. To modify all aspects of existing network and create a network from scratch it is being used to process these. It is a GUI application an inputs as chosen through thehelp of menus.
Given blow are the input formats-
Net files- SUMOOSM files Configuration file- NETCONERTOutput Net file- SUMO XML files plain
NETSIM- NETSIM is a networksimulation tool that allows you to create network scenario model traffic, design protocol, and analyze network performance. The various network technologies covered in NETSIM include:
-Wireless sensor networks
-Long term Evolution
We are using NETSIM v9 standard versionin our paper we interface sumo with NETSIM with the help of generatingmobility txt file. In NETSIM v10 we have VANET option so we directly export the file from sumo and give as input for NETSIM
Location Based Broadcast in LocationBased Broadcast, each vehicle uses its location information to decide whether it should rebroadcast a receiving packet. Thisalgorithm can eliminate unnecessary rebroadcasting by choosing a suitable relayvehicle (e.g., in front, behind, left lane, distance, of the sender vehicle). Because each vehicle needs to know the location of the neighboring vehicles, it is necessary to exchange location information frequently among them. Cluster Based Broadcast in Cluster Based Broadcast, vehicles are grouped into clusters and a cluster head is selected from amongst the members of a cluster in the group; these cluster heads arethe only nodes permitted to broadcast. In general, the vehicles present in the same cluster have similar features, e.g., speed. Because only cluster heads are permitted to broadcast, the number of packets transmitted in the network is reduced. Although several broadcast algorithms have been proposed in VANETs, these existing algorithms are designed for general-purpose VANETs and not optimized for specific applications. There are various kinds of applications of VANETs such as a safety, infotainment, and traffic monitoring. Broadcast algorithms should be optimized based on the application characteristics. In this paper, we propose a broadcast algorithm suitable for vehicle visualization.
MDDV: A Mobility-Centric DataDissemination Algorithm for Vehicular Networks,
In this, we present the MDDV algorithm. In V2V networks, opportunities to forward messages are created by vehicle movement, so it is natural to focus on vehicle mobility. MDDV is a mobility centric approach that combines opportunistic forwarding, geographicalforwarding, and trajectory based forwarding. A forwarding trajectory is specified extending from the source to the destination (trajectory base forwarding) along which a message will be moved geographically closer to the destination (geographical forwarding). With anopportunistic forwarding approach, rules must be defined to determine who is eligible to forward a message, when a copyof the message should be passed to another vehicle and when a vehicle should hold/drop a message To support its decision making, a vehicle needs some approximate knowledge about the status of the dissemination . We motivate the design by reference to a test scenario, geographical-temporal multicast. Later we will show how to extend MDDV to cover all the services defined in Geographical- temporal multicast is formally defined as: deliver a message to all vehicles in/entering region r before time t while the data source s is outside of r. A region is defined as a set of connected road segments (for two-way roads, both directions are included). Two road segments are connected if they share an intersection. We place the source outsideof the destination region to make the problem non-trivial. We assume a vehicle knows the road topology through a digital map and its own location in the roadnetwork via a GPS device. We assume vehicles know the existence of their neighbors through some link level mechanism. But we do not assume a vehicle knows the location of its neighbors(unlike most geographic forwarding algorithms). In this way, a vehicles knowledge of other vehicles is limited, in order to help alleviate privacy and security concerns. Further it is assumed that all instrumented vehicles communicate using the same wireless channel. The message dissemination information, e.g., source id, source location, generation time, destination region, expiration time and forwarding trajectory, etc, is specified by the data source and is placed in the message header.
RESULT AND SIMULATION
Vehicle No 50
In this scenario, we have designed through NETSIM. we show in this figure the communication between each vehicle application. These applications are given some result as like, data transfer successfully, packet collided, a packettransmitted, and simulation time.
Throughput for 70 No.of vehicles
Time of simulation (ms) = 100000.00Transmitted packets = 159441 Errored packets = 20114 Collided packets= 40612 Transmitted bytes (in Bytes) =26453922.00
Transmitted payload (in Bytes) =7367160.00 Transmitted overhead (in Bytes) =19086762.00
Results and Discussion for 70 vehicles
Fig (3): VANET path on NETEDIT sumo
Above fig (3) Shows the NETEDIT pathfor 70 vehicles in this figure we design apath for 70 vehicles which shows nodes
,edges and traffic signa system.
Fig(4): 70 Vehicles Connectivity scenario on Netsim
Above fig shows the vehicle connectivity scenario on NETSIM this is the NETSIM scenario for 70 vehicles we created in NETSIM in this process we connected vehicles through application layer with specific vehicle ID.
Fig (5): 70 vehicles connectivity scenario according to mobility file
Above fig(5) Shows the vehicle connectivity according to the mobility file which we create with the help of sumo configuration file thisfig shows the simulation between vehicles
Fig(6): Overall 70 vehicle network graph
Above fig shows that the overall graph of 70 vehicles network which shows that the maximum throughput is 82.795206mbps for overall scenario of 70 vehicles.
In this paper, we have analyzed Vehicle connectivity and Traffic Congestion to Prevent Accidents in Vehicular Ad-Hoc Network link and junction of sumo path for safety and security purpose. We have taken one scenario of vehicle such as 70, vehicle.
We have simulated the result with the help of sumo and interface withNETSIM based on throughput and timeand identify the traffic Jam in each junctions.
- . Hartenstein, annes.VANET:vehicularapplications and inter-networking technologies.Edited by Kenneth Laberteaux. Volume. 1. 2010.
- . Zhang, Jie. Trust management for VANETs: challenges, desired properties and future directions. International Journal of Distributed Systems and Technologies (IJDST), volume. 3, Number. 1, pageNo. 48-62, 2012.
- . Berradj, Adel, and Zoubir Mammeri. Multi-Hop Broadcasting in VANET for Safety Applications: Review & of Protocols.