  Accurate vehicular sensing is a basic and important operation in autonomous
driving. Unfortunately, the existing techniques have their own limitations. For
instance, the communication-based approach (e.g., transmission of GPS
information) has high latency and low reliability while the reflection-based
approach (e.g., RADAR) is incapable of detecting hidden vehicles (HVs) without
line-of-sight. This is arguably the reason behind some recent fatal accidents
involving autonomous vehicles. To address this issue, this paper presents a
novel HV-sensing technology that exploits multi-path transmission from a HV to
a sensing vehicle (SV). The powerful technology enables the SV to detect
multiple HV-state parameters including position, orientation of driving
direction, and size. Its implementation does not even require
transmitter-receiver synchronization like conventional mobile positioning
techniques. Our design approach leverages estimated information on multi-path
(AoA/AoD/ToA) and their geometric relations. As a result, a complex system of
equations or optimization problems, where the desired HV-state parameters are
variables, can be formulated for different channel-noise conditions. The
development of intelligent solution methods ranging from least-square estimator
to disk/box minimization yields a set of practical HV-sensing techniques. We
study their feasibility conditions in terms of the required number of paths.
Furthermore, practical solutions, including sequential path combining and
random directional beamforming, are proposed to enable HV-sensing given
insufficient paths. Last, realistic simulation of driving in both highway and
rural scenarios demonstrates the effectiveness of the proposed techniques. In
summary, the proposed technique will enhance the capabilities of existing
vehicular sensing technologies by enabling HV-sensing.
