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Title: Information collection algorithm for vehicular ad-hoc networks (application domain: Urban Traffic Wireless Vehicular Ad-Hoc Networks (VANETs))
Author: Gamati, E.
Awarding Body: Nottingham Trent University
Current Institution: Nottingham Trent University
Date of Award: 2013
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Vehicle to vehicle communication (V2VC) is one of the modern approaches for exchanging and generating traffic information with (yet to be realized) potential to improve road safety, driving comfort and traffic control. In this research, we present a novel algorithm which is based on V2V communication, uses in-vehicle sensor information and in collaboration with the other vehicles' sensor information can detect road conditions and determine the geographical area where this road condition exists – e.g. geographical area where there is traffic density, unusual traffic behaviour, a range of weather conditions (raining), etc. The algorithms' built-in automatic geographical restriction of the data collection, aggregation and dissemination mechanisms allows warning messages to be received by any car, not necessarily sharing the identified road condition, which may then be used to identify the optimum route taken by the vehicle e.g. avoid bottlenecks or dangerous areas including accidents or congestions on their current routes. This research covers the middle ground between MANET [1] and collaborative data generation based on knowledge granularity (aggregation). It investigates the possibility of designing, implementing and modelling of the functionality of an algorithm (as part of the design of an intelligent node in an Intelligent Transportation System - ITS) that ensures active participation in the formation, routing and general network support of MANETs and also helps in-car traffic information and real-time control generation and distribution. The work is natural extension of the efforts of several large EU projects like DRIVE [2], GST [3] and SAFESPOT [4]. The main difference between this research work and the research efforts outlined in these projects and related work is that they focus on V2I (Vehicle to Infrastructure) algorithms and node design, while all work related to ad-hoc wireless communication is mentioned, but not developed fully. In that respect this specific research domain is increasingly under active research consideration – utilizing ad-hoc networks algorithms for creating ad-hoc based wireless architectures and algorithms for building future intelligent information systems. The research challenge is to design, implement and investigate novel algorithms as part of an intelligent wireless information systems node design so that the functionality of the node has all the characteristics of the network node in parallel with all the characteristics of in-car data processing device. The project redefines the base line connectivity of the device and describes to what extend the functionality of the node will depend on external factors: e.g. connectivity based on the underlying wireless technology, support of the ad-hoc networks based on the speed and the type of mobility of the mobile node etc. The big difference between MANET as described so-far in the literature and the one which will be underlined by the functionality of the intelligent node described in this project is in the functionality of the active component of the MANET described here. The MANET designed in the project will be able to more effectively generate data (not network data – but user traffic data) and also will be able to take part in the on street control of the traffic lights. Although much research work worldwide is dedicated to the subject, the fact is that there are none implemented on the road traffic information systems based on ad-hoc networking, which shows that the principles of building such effective networks are yet to be discovered. The achievements of this research include introducing a novel algorithm based on the “Single Ripple” algorithm approach [5], investigating and reporting in papers the parameters transmission delay and number of hops for optimum working mode of the algorithm. The work includes also developing a simulation tool and tool for analyses of the data.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available