City Research Online

Abstract

The main contribution of this thesis is the LA mechanism - an intelligent, locationaware data aggregation mechanism for real-time observation, estimation and efficient dissemination of messages in VANETs. The proposed mechanism is based on a generic modelling approach which makes it applicable to any type of VANET applications. The data aggregation mechanism proposed in this thesis introduces location awareness technique which provides dynamic segmentation of the roads enabling efficient spatiotemporal database indexing. It further provides the location context to the messages without the use of advanced positioning systems like satellite navigation and digital maps. The mechanism ensures that the network load is significantly reduced by using the passive clustering and adaptive broadcasting to minimise the number of exchanged messages. The incoming messages are fused by Kalman filter providing the optimal estimation particularly useful in urban environment where incoming measurements are very frequent and can cause the vehicle to interpret them as noisy measurements. The scheme allows the comparison of aggregates and single observations which enables their merging and better overall accuracy. Old information in aggregates is removed by realtime database refreshing leaving only newer relevant information for a driver to make real-time decisions in traffic. The LA mechanism is evaluated by extensive simulations to show efficiency and accuracy.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HE Transportation and Communications Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	Doctoral Theses School of Science & Technology > School of Science & Technology Doctoral Theses

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