VNC 2015, IEEE Vehicular Networking Conference, December 16-18, 2015, Kyoto, Japan
Dedicated Short Range Communication (DSRC) based on the IEEE 802.11p standard is expected to stimulate Cooperative Positioning (CP) for emerging cooperative safety
applications. However, the trade-off includes high computational complexity and heavy communication loads while performing exhaustive particle-based information fusion. This paper addresses the problem of selecting the best subset of links to spatial neighbors for "ego" car positioning in a pure GPS-enabled Vehicular Ad hoc NETwork (VANET). Computationally efficient link selection algorithms based on Cram´er-Rao Lower Bound
(CRLB) indicators, including a formulation accounting for neighbors uncertainties, are proposed to cope with various realistic operating contexts. We show that selective fusion significantly reduces the computational complexity and required network traffic with a modest increase in the position error in most cases and an acceptable degradation in the worst-case long-term GPSdenied condition. We also illustrate a typical scenario where evaluating the dispersion of neighboring uncertainties helps to decide the best selection criterion, thus leading to the concept of context-aware selective information fusion.
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