GAMATI, E., 2013. Information collection algorithm for vehicular ad-hoc networks (application domain: Urban Traffic Wireless Vehicular Ad-Hoc Networks (VANETs)). PhD, Nottingham Trent University.
Download (7MB) | Preview
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  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 , GST  and SAFESPOT .
|Divisions:||Schools > School of Science and Technology|
|Depositing User:||EPrints Services|
|Date Added:||09 Oct 2015 09:33|
|Last Modified:||09 Oct 2015 09:33|
Actions (login required)
Views per month over past year
Downloads per month over past year