Blind Cancellation in Radar-Based Self Driving Vehicles.

Mutual interference among the radar sensors has become a serious concern due to the extensive growth of self driving vehicles (SDV) equipped with such sensors. The problem becomes more severe with the increase in traffic density, where a large number of SDVs gather within the proximity of inter-vehicular radars. Thereby, the number of resources required to maintain the neighbourhood orthogonality increases with traffic density and further leads to the problem of radar blindness. In this paper, we propose a graph-based resource allocation (GRA) scheme to assign resources to the running SDV pool. GRA assures that two closely located SDVs may not simultaneously use the same resource. Also, we integrate the notion of traffic-based dynamic-range approach (TDA) with GRA. Then, through simulation results, it is shown that GRA outperforms the state of art random allocation approach. Further, it is shown that GRA, along with TDA, may eliminate the problem of radar blindness. [ABSTRACT FROM AUTHOR]