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

TitleHidden Vehicle Sensing via Asynchronous V2V Transmission: A Multi-Path-Geometry Approach
Authors
KeywordsSensors
Synchronization
Laser radar
Global Positioning System
Reliability
Issue Date2019
PublisherInstitute of Electrical and Electronics Engineers (IEEE): OAJ. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639
Citation
IEEE Access, 2019, v. 7, p. 169399-169416 How to Cite?
AbstractAccurate 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 synchronization like conventional mobile positioning techniques. Our design approach leverages estimated information on multi-path [namely their angles-of-arrival (AoA), angles-of-departure (AoD), and time-of-arrival (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 (e.g., RADAR and LIDAR) by enabling HV-sensing.
Persistent Identifierhttp://hdl.handle.net/10722/290569
ISSN
2019 Impact Factor: 3.745
2015 SCImago Journal Rankings: 0.947
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, K-
dc.contributor.authorHan, K-
dc.contributor.authorKo, S-
dc.contributor.authorChae, H-
dc.contributor.authorKim, B-
dc.date.accessioned2020-11-02T05:44:06Z-
dc.date.available2020-11-02T05:44:06Z-
dc.date.issued2019-
dc.identifier.citationIEEE Access, 2019, v. 7, p. 169399-169416-
dc.identifier.issn2169-3536-
dc.identifier.urihttp://hdl.handle.net/10722/290569-
dc.description.abstractAccurate 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 synchronization like conventional mobile positioning techniques. Our design approach leverages estimated information on multi-path [namely their angles-of-arrival (AoA), angles-of-departure (AoD), and time-of-arrival (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 (e.g., RADAR and LIDAR) by enabling HV-sensing.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE): OAJ. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639-
dc.relation.ispartofIEEE Access-
dc.rightsIEEE Access. Copyright © Institute of Electrical and Electronics Engineers (IEEE): OAJ.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectSensors-
dc.subjectSynchronization-
dc.subjectLaser radar-
dc.subjectGlobal Positioning System-
dc.subjectReliability-
dc.titleHidden Vehicle Sensing via Asynchronous V2V Transmission: A Multi-Path-Geometry Approach-
dc.typeArticle-
dc.identifier.emailHuang, K: huangkb@eee.hku.hk-
dc.identifier.authorityHuang, K=rp01875-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ACCESS.2019.2954858-
dc.identifier.scopuseid_2-s2.0-85077758219-
dc.identifier.hkuros318042-
dc.identifier.volume7-
dc.identifier.spage169399-
dc.identifier.epage169416-
dc.identifier.isiWOS:000560454900013-
dc.publisher.placeUnited States-
dc.identifier.issnl2169-3536-

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