This paper is published in Volume-2, Issue-4, 2016
Area
Computer Science and Engineering
Author
Arun Sharma
Co-authors
Kapil Kapoor, Bodh Raj, Divya Jyoti
Org/Univ
Abhilashi Group of Institution School of Pharmacy and Engineering and Technology,(H.P.), India
Pub. Date
16 August, 2016
Paper ID
V2I4-1152
Publisher
Keywords
VANET, PDR, AODV, NS2, END TO END DELAY

Citationsacebook

IEEE
Arun Sharma, Kapil Kapoor, Bodh Raj, Divya Jyoti. A Novel Approach for Detection of Traffic Congestion in NS2, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Arun Sharma, Kapil Kapoor, Bodh Raj, Divya Jyoti (2016). A Novel Approach for Detection of Traffic Congestion in NS2. International Journal of Advance Research, Ideas and Innovations in Technology, 2(4) www.IJARIIT.com.

MLA
Arun Sharma, Kapil Kapoor, Bodh Raj, Divya Jyoti. "A Novel Approach for Detection of Traffic Congestion in NS2." International Journal of Advance Research, Ideas and Innovations in Technology 2.4 (2016). www.IJARIIT.com.

Abstract

Traffic congestions are formed by many factors; some are predictable like road construction, rush hour or bottle-necks. Drivers, unaware of congestion ahead eventually join it and increase the severity of it. The more severe the congestion is, the more time it will take to clear. In order to provide drivers with useful information about traffic ahead a system must: Identify the congestion, its location, severity and boundaries and Relay this information to drivers within the congestion and those heading towards it. To form the picture of congestion they need to collaborate their information using vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communication. Once a clear picture of the congestion has formed, this information needs to be relayed to vehicles away from the congestion so that vehicles heading towards it can take evasive actions avoiding further escalation its severity. Initially, a source vehicle initiates a number of queries, which are routed by VANETs along different paths toward its destination. During query forwarding, the real-time road traffic information in each road segment is aggregated from multiple participating vehicles and returned to the source after the query reaches the destination. This information enables the source to calculate the shortest-time path. By allowing data exchange between vehicles about route choices, congestions and traffic alerts, a vehicle makes a decision on the best course of action.
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