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Accurate vehicular sensing is a basic and important operation in autonomousdriving. Unfortunately, the existing techniques have their own limitations. Forinstance, the communication-based approach (e.g., transmission of GPSinformation) has high latency and low reliability while the reflection-basedapproach (e.g., RADAR) is incapable of detecting hidden vehicles (HVs) withoutline-of-sight. This is arguably the reason behind some recent fatal accidentsinvolving autonomous vehicles. To address this issue, this paper presents anovel HV-sensing technology that exploits multi-path transmission from a HV toa sensing vehicle (SV). The powerful technology enables the SV to detectmultiple HV-state parameters including position, orientation of drivingdirection, and size. Its implementation does not even requiretransmitter-receiver synchronization like conventional mobile positioningtechniques. Our design approach leverages estimated information on multi-path(AoA/AoD/ToA) and their geometric relations. As a result, a complex system ofequations or optimization problems, where the desired HV-state parameters arevariables, can be formulated for different channel-noise conditions. Thedevelopment of intelligent solution methods ranging from least-square estimatorto disk/box minimization yields a set of practical HV-sensing techniques. Westudy their feasibility conditions in terms of the required number of paths.Furthermore, practical solutions, including sequential path combining andrandom directional beamforming, are proposed to enable HV-sensing giveninsufficient paths. Last, realistic simulation of driving in both highway andrural scenarios demonstrates the effectiveness of the proposed techniques. Insummary, the proposed technique will enhance the capabilities of existingvehicular sensing technologies by enabling HV-sensing.

Hidden Vehicle Sensing via Asynchronous V2V Transmission: A Multi-Path-Geometry Approach