In the Vehicular Ad hoc NETwork (VANET), vehicles are clustered to construct many small networks (clusters) so that channel interferences and flooding messages can be limited. This work presents a novel Multi-resolution Relative Speed Detection (MRSD) model to improve the clustering algorithm in VANET without using a Global Positioning System (GPS). MRSD uses the Moving Average Convergence Divergence (MACD), the Momentum of Received Signal Strength (MRSS) and an Artificial Neural Network (ANN) to estimate the motion state and the relative speed of a vehicle based purely on Received Signal Strength (RSS). With the speed information, vehicles in a cluster are grouped by their speeds and a vehicle in the largest group is elected as a cluster leader. Moreover, MRSD can detect relative speed among vehicles without GPS and thus can offer better privacy for users. Simulation results show that MRSD can classify accurately vehicles speed without GPS assistance.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    GPS-less speed detection in VANET


    Contributors:


    Publication date :

    2010


    Size :

    7 Seiten, 8 Bilder, 5 Tabellen, 12 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    A speed-based vertical handover algorithm for VANET

    Vegni, Anna Maria / Esposito, Flavio | Tema Archive | 2010


    A speed-based vertical handover algorithm for VANET

    Vegni,A.M. / Esposito,F. / Univ.di Roma III,IT et al. | Automotive engineering | 2010



    Intelligent Advisory Speed Limit Dedication in Highway Using VANET

    Ali Jalooli / Erfan Shaghaghi / Mohammad Reza Jabbarpour et al. | DOAJ | 2014

    Free access

    Fault Detection for VANET Using Vehicular Cloud

    Senapati, Biswa Ranjan / Mohapatra, Santoshinee / Khilar, Pabitra Mohan | Springer Verlag | 2020