Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion
Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge main...
Saved in:
| Published in | Traffic injury prevention Vol. 18; no. sup1; pp. S31 - S36 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Taylor & Francis
29.05.2017
Taylor & Francis Ltd |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.
Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO
2
) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO
2
. In the present investigation, alcohol and CO
2
were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.
Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO
2
and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated.
The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.
Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. |
|---|---|
| AbstractList | Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.
Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.
Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated.The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.
Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually. The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO ) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO . In the present investigation, alcohol and CO were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized. It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually. Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO 2 ) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO 2 . In the present investigation, alcohol and CO 2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO 2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized. Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.OBJECTIVEThe research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.METHODThe work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.RESULTSImprovement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design.CONCLUSIONSIt is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated.The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design. |
| Author | Allalou, Amin Ljungblad, Jonas Pettersson, Håkan Hök, Bertil |
| Author_xml | – sequence: 1 givenname: Jonas surname: Ljungblad fullname: Ljungblad, Jonas email: jonas.ljungblad@hokinstrument.com organization: Hök Instrument AB – sequence: 2 givenname: Bertil surname: Hök fullname: Hök, Bertil organization: Hök Instrument AB – sequence: 3 givenname: Amin surname: Allalou fullname: Allalou, Amin organization: Uppsala University, Centre for Image Analysis – sequence: 4 givenname: Håkan surname: Pettersson fullname: Pettersson, Håkan organization: Autoliv Development AB |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28368660$$D View this record in MEDLINE/PubMed https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-36633$$DView record from Swedish Publication Index https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-326377$$DView record from Swedish Publication Index |
| BookMark | eNqNks1u1DAUhS1URH_gEUCW2LAggx2PnRuxoSoUkCrBAhA768Z2Zlwl9tROpurbk3Sms-gCWNm6-s7xlc85JUchBkfIS84WnAF7x6WAWgIsSsarBRe8VABPyMk8L2pZ_T463AGOyWnO14yVHJh8Ro5LEAqUYiek_Y45-62jPhRbt_amc9SmaZBokxwOa4qdievYUesGZwYfAx2zDyuKdovBOEuzCzkmmv0qYEfR3Iw--3sQg6XtRMfwnDxtscvuxf48Iz8vP_24-FJcffv89eL8qjCSy6HAJW-EhNqAsdhw5aRUXBnXWKxqwLZWDkCiqiwXLavQKVkuW1C8YRYFluKMvN355lu3GRu9Sb7HdKcjev3R_zrXMa30OGpRKlFV_4f3dq2FUkJM-JsdvknxZnR50L3PxnUdBhfHrDnAkisJDCb09SP0Oo5p-qCsp8CkZEsO87qv9tTY9M4e3n_IZwLkDjAp5pxce0A403MP9EMPZttK73sw6d4_0hk_4BzKkNB3_1R_2Kl9aGPq8TamzuoB77qY2jSl7rMWf7f4A312zEw |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2022_3221145 crossref_primary_10_3390_app13063478 crossref_primary_10_1039_D0NA00002G crossref_primary_10_3390_s22186819 crossref_primary_10_1145_3264956 crossref_primary_10_35633_inmateh_65_28 crossref_primary_10_1049_itr2_12520 crossref_primary_10_1109_TIV_2024_3382995 crossref_primary_10_3390_ijms24032980 crossref_primary_10_1016_j_sasc_2024_200078 crossref_primary_10_3389_fsens_2024_1375034 crossref_primary_10_3390_s20092442 crossref_primary_10_3390_ijerph20021319 crossref_primary_10_1542_peds_2023_062508 crossref_primary_10_1515_phys_2019_0015 crossref_primary_10_1016_j_fsisyn_2020_01_018 crossref_primary_10_2196_42823 crossref_primary_10_1177_1550147720905234 |
| Cites_doi | 10.1364/JOSA.32.000285 10.1016/j.uclim.2014.09.001 10.1007/s11517-010-0655-5 10.1109/JSEN.2009.2035204 10.3390/s16040469 |
| ContentType | Journal Article |
| Contributor | Allalou, Amin Pettersson, Håkan Hök, Bertil |
| Contributor_xml | – sequence: 1 givenname: Bertil surname: Hök fullname: Hök, Bertil organization: Hök Instrument AB – sequence: 2 givenname: Amin surname: Allalou fullname: Allalou, Amin organization: Uppsala Universitet – sequence: 3 givenname: Håkan surname: Pettersson fullname: Pettersson, Håkan organization: Autoliv Development AB |
| Copyright | 2017 The Author(s). Published with license by Taylor & Francis © Jonas Ljungblad, Bertil Hök, Amin Allalou, and Håkan Pettersson 2017 2017 The Author(s). Published with license by Taylor & Francis; © Jonas Ljungblad, Bertil Hök, Amin Allalou, and Håkan Pettersson |
| Copyright_xml | – notice: 2017 The Author(s). Published with license by Taylor & Francis © Jonas Ljungblad, Bertil Hök, Amin Allalou, and Håkan Pettersson 2017 – notice: 2017 The Author(s). Published with license by Taylor & Francis; © Jonas Ljungblad, Bertil Hök, Amin Allalou, and Håkan Pettersson |
| DBID | 0YH AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QF 7QQ 7SC 7SE 7SP 7SR 7T2 7TA 7TB 7U5 8BQ 8FD C1K F28 FR3 H8D H8G JG9 JQ2 KR7 L7M L~C L~D 7X8 ABGEM ADTPV AOWAS D8T DF7 ZZAVC ACNBI DF2 |
| DOI | 10.1080/15389588.2017.1312688 |
| DatabaseName | Taylor & Francis Free Journals (Free resource, activated by CARLI) CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Aluminium Industry Abstracts Ceramic Abstracts Computer and Information Systems Abstracts Corrosion Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts Health and Safety Science Abstracts (Full archive) Materials Business File Mechanical & Transportation Engineering Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database Environmental Sciences and Pollution Management ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database Copper Technical Reference Library Materials Research Database ProQuest Computer Science Collection Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional MEDLINE - Academic SWEPUB Mälardalens högskola full text SwePub SwePub Articles SWEPUB Freely available online SWEPUB Mälardalens högskola SwePub Articles full text SWEPUB Uppsala universitet full text SWEPUB Uppsala universitet |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Materials Research Database Civil Engineering Abstracts Aluminium Industry Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Ceramic Abstracts Materials Business File METADEX Environmental Sciences and Pollution Management Computer and Information Systems Abstracts Professional Aerospace Database Copper Technical Reference Library Engineered Materials Abstracts Health & Safety Science Abstracts Solid State and Superconductivity Abstracts Engineering Research Database Corrosion Abstracts Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering MEDLINE - Academic |
| DatabaseTitleList | MEDLINE MEDLINE - Academic Materials Research Database |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: 0YH name: Taylor & Francis Free Journals (Free resource, activated by CARLI) url: https://www.tandfonline.com sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Economics |
| EISSN | 1538-957X |
| EndPage | S36 |
| ExternalDocumentID | oai_DiVA_org_uu_326377 oai_DiVA_org_mdh_36633 28368660 10_1080_15389588_2017_1312688 1312688 |
| Genre | Article Research Support, U.S. Gov't, Non-P.H.S Research Support, Non-U.S. Gov't Journal Article |
| GroupedDBID | --- ..I .7F .QJ 0BK 0R~ 0YH 123 29Q 30N 36B 4.4 53G 5VS 6PF AAENE AAJMT AALDU AAMIU AAPUL AAQRR AAWTL ABCCY ABFIM ABHAV ABJNI ABLIJ ABPAQ ABPEM ABTAI ABXUL ABXYU ACGFS ACHQT ACIWK ACPRK ACTIO ADCVX ADGTB ADLRE ADXPE AEISY AENEX AEOZL AEPSL AEYOC AFKVX AFRAH AGDLA AGMYJ AHDZW AIJEM AJWEG AKBVH AKOOK ALMA_UNASSIGNED_HOLDINGS ALQZU AQRUH AVBZW AWYRJ BLEHA CCCUG CE4 CS3 DGEBU DKSSO DU5 EBD EBS EJD EMB EMOBN EV9 E~A E~B F5P GTTXZ H13 HF~ HZ~ H~P IPNFZ J.P KYCEM M4Z NA5 O9- PQQKQ RIG RNANH ROSJB RTWRZ S-T SNACF SV3 TBQAZ TDBHL TEN TFL TFT TFW TNC TTHFI TUROJ TWF UT5 UU3 ZGOLN ~S~ AAGDL AAHIA AAYXX ADYSH AFRVT AIYEW AMPGV CITATION CGR CUY CVF ECM EIF NPM TASJS 7QF 7QQ 7SC 7SE 7SP 7SR 7T2 7TA 7TB 7U5 8BQ 8FD C1K F28 FR3 H8D H8G JG9 JQ2 KR7 L7M L~C L~D 7X8 1TA ABGEM ACTTO ADTPV ADUMR AFBWG AFION AGVKY AGWUF ALRRR AOWAS BWMZZ CAG COF CYRSC D8T DAOYK DF7 LJTGL OPCYK ZZAVC ACNBI AGBKS DF2 |
| ID | FETCH-LOGICAL-c515t-a41b3589c8cdab16e55616cebda798af96e885a67d13f07ae6524f861b0da3a23 |
| IEDL.DBID | 0YH |
| ISSN | 1538-9588 1538-957X |
| IngestDate | Thu Aug 21 06:39:56 EDT 2025 Thu Jul 03 04:54:19 EDT 2025 Fri Jul 11 06:58:35 EDT 2025 Wed Aug 13 09:27:22 EDT 2025 Mon Jul 21 05:59:51 EDT 2025 Tue Jul 01 04:10:45 EDT 2025 Thu Apr 24 23:10:11 EDT 2025 Wed Dec 25 09:08:09 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | sup1 |
| Keywords | automotive safety infrared gas sensor Passive breath alcohol detection contactless measurement |
| Language | English |
| License | open-access: http://creativecommons.org/licenses/by-nc-nd/4.0/: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c515t-a41b3589c8cdab16e55616cebda798af96e885a67d13f07ae6524f861b0da3a23 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://www.tandfonline.com/doi/abs/10.1080/15389588.2017.1312688 |
| PMID | 28368660 |
| PQID | 2015504182 |
| PQPubID | 186141 |
| ParticipantIDs | proquest_journals_2015504182 crossref_primary_10_1080_15389588_2017_1312688 swepub_primary_oai_DiVA_org_mdh_36633 informaworld_taylorfrancis_310_1080_15389588_2017_1312688 swepub_primary_oai_DiVA_org_uu_326377 proquest_miscellaneous_1884165808 pubmed_primary_28368660 crossref_citationtrail_10_1080_15389588_2017_1312688 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2017-05-29 |
| PublicationDateYYYYMMDD | 2017-05-29 |
| PublicationDate_xml | – month: 05 year: 2017 text: 2017-05-29 day: 29 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: Philadelphia |
| PublicationTitle | Traffic injury prevention |
| PublicationTitleAlternate | Traffic Inj Prev |
| PublicationYear | 2017 |
| Publisher | Taylor & Francis Taylor & Francis Ltd |
| Publisher_xml | – name: Taylor & Francis – name: Taylor & Francis Ltd |
| References | cit0012 cit0010 NHTSA (cit0014) 2014 Hök B (cit0003) 2014; 2 Hök B (cit0004) Zaouk A (cit0018) Hök B (cit0006) Kaisdotter Andersson A (cit0009) cit0008 Ljungblad J (cit0013) NHTSA (cit0015) 2015 Tang W (cit0016) cit0017 cit0007 Ljungblad J (cit0011) Blomberg RD (cit0001) 2005 cit0005 cit0002 |
| References_xml | – volume-title: Paper presented at: Intelligent Sensors, Sensor Networks and Information Processing ident: cit0011 – volume-title: Paper presented at: Transportation Research Board 90th Annual Meeting ident: cit0018 – ident: cit0008 – ident: cit0017 doi: 10.1364/JOSA.32.000285 – ident: cit0002 – volume-title: Paper presented at: International Conference on Alcohol, Drugs and Traffic Safety ident: cit0009 – volume-title: Paper presented at: International Conference on Alcohol, Drugs and Traffic Safety ident: cit0013 – volume-title: The Economic and Societal Impact of Motor Vehicle Crashes 2010 year: 2014 ident: cit0014 – volume: 2 start-page: 1 issue: 4 year: 2014 ident: cit0003 publication-title: Journal of Forensic Investigation – volume-title: The Economic and Societal Impact of Motor Vehicle Crashes 2010 (Revised) year: 2015 ident: cit0015 – ident: cit0007 doi: 10.1016/j.uclim.2014.09.001 – volume-title: Paper presented at: Micro Structure Workshop ident: cit0004 – volume-title: Paper presented at: 24th International Conference on the Enhanced Safety of Vehicles ident: cit0006 – ident: cit0010 doi: 10.1007/s11517-010-0655-5 – ident: cit0005 doi: 10.1109/JSEN.2009.2035204 – ident: cit0012 doi: 10.3390/s16040469 – volume-title: Paper presented at: Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA ident: cit0016 – volume-title: Crash Risk of Alcohol Involved Driving: A Case–Control Study year: 2005 ident: cit0001 |
| SSID | ssj0021805 |
| Score | 2.2349243 |
| Snippet | Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and... The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight... |
| SourceID | swepub proquest pubmed crossref informaworld |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | S31 |
| SubjectTerms | Alcohol Alcoholic Intoxication - diagnosis Alcohols Automobile Driving - statistics & numerical data Automotive parts automotive safety Body parts Breath tests Breath Tests - instrumentation Breathing Cameras Carbon dioxide Computer simulation contactless measurement Driving ability Drunk driving Ethanol - isolation & purification Geographical variations Head Human performance Human subjects Humans In vehicle Infrared detectors infrared gas sensor Infrared spectroscopy Low concentrations Passive breath alcohol detection Recording Ruggedness Sensors Substance Abuse Detection - methods Traffic accidents & safety |
| Title | Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion |
| URI | https://www.tandfonline.com/doi/abs/10.1080/15389588.2017.1312688 https://www.ncbi.nlm.nih.gov/pubmed/28368660 https://www.proquest.com/docview/2015504182 https://www.proquest.com/docview/1884165808 https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-36633 https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-326377 |
| Volume | 18 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagHOBSlffSgowExxQ7Thz7WLVUKyQqDhTByfKzu1LJwibp72cmL1EE2gOXRJHtPDwz8Tf25xlC3ijBnC2KmPlY2ayIvMh0lXwW8hRLCyoiBW5O_nghl5fFh6_lxCZsRlol-tBpCBTR_6vRuK1rJkbcOzRSXaqemFUdc8FzqdRdci9HbQWVZt-Ws8_FVc9iHOwa2kybeP51m1vD063gpX-DoH_EF-3HpPMDsj-CSXoySP8huRPrR-T-tNe4eUzSJ8DG8D-j6zq7iSusRcMWqRjUIVpcUTukyKUhtj0pq6bIhL-iEzeANuDnbrYUeR7wKOt_duuB5kWh_2jqcLbtCbk8f__5dJmNmRUyD_ilzWzBnSiV9soH67iMmCRT-uiCrbSyScuoVGllFbhIrLJRlnmRlOSOBStsLp6SvXpTx-eEMu0rn4IXyoGvKAPALaGiY0nAmem4IMXUocaPYccx-8W14WN00kkOBuVgRjksyPHc7McQd2NXA_27tEzbT3ikITuJETvaHk2iNaMJN1gBvLcC_K8FeT0Xg_Hhioqt46ZrDFe4alsqBrd4NqjE_LaA26SSki3I20FH5hKM6H22_nJiNtsr8z2sjADYJ3bU6zoDSFtU1Yv_-NBD8gAvkf2Q6yOy1267-BJAVete9WYDR8EufgHaxRfJ |
| linkProvider | Taylor & Francis |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagHMqFN2WhgJHgmCWOEz-OFVAt0K44tKg3y8_uCsjCbsKBX48nTqK2Au2hpxz8SOzM2N_Y38wg9FrQ3Oiy9Jn1XGelJ2UmebCZK4KvdBQRRsE5-XjOZqflp7Pq7IIvDNAqwYYOKVBEt1aDcsNh9ECJewtaKivRMbP4lFBSMCFuoluVZByyGNB8PhpdRHQ0xqTYsc3gxfO_bi7tT5eil_4Lg14JMNptSod3kR2Gk7go36ZtY6b2z5VIj9cb7z10p8es-CAJ2X10w9cP0O7g0rx5iMKXCMHjsomXdfbbL6AWdmtgfGADoHSBdcrEi51vOu5XjYFwf44HCgLeRHN6tcZAJ4mv0vZXu0xsMhw_G4cWDvUeodPDDyfvZlmfwCGzESY1mS6JoZWQVlinDWEecnEy643TXAodJPNCVJpxR2jIufasKsogGDG501QX9DHaqVe1f4JwLi23wVkqTDRJmYuojgpv8kDjM5d-gsrhtynbRzeHJBvfFemDoA6TqGASVT-JEzQdm_1M4T22NZAXZUI13blKSElQFN3Sdn8QINWvFBuoEI3EMpp5E_RqLI46Dhc3uvardqOIgMvhSuSxi70keOPXRnjIBGP5BL1JkjiWQODw98uvB2q1Plc_3ELRiC7plnptqyKgp5w_vcZAX6Ld2cnxkTr6OP_8DN2GIiBcFHIf7TTr1j-POK4xLzpF_QtPYjqF |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagSNAL78dCASPBMds4ThznWFFW5bXqgSJulp_dFTRbNgkHfj0zcbKiFWgPPeVgO4mdGecb-_M3hLyWPDU6z31ifamT3LM8qcpgE5cFX2gwEcHxcPLnuTg6yT98K0Y2YTPQKjGGDlEoop-r0bnPXRgZcfvopFUhe2JWOWWcZULK6-SGQPFwPMWRzjcxF5M9izH6NbQZD_H87zYXfk8XxEv_BUEv6Yv2_6TZHWLG3kQqyvdp15qp_X1J6PFK3b1Lbg-IlR5EE7tHrvn6Prk1HmhuHpBwDAAcJk26rJNffoG1qFsj34MahKQLqmMeXup82zO_aop0-1M6EhBoA8H0ak2RTAKP0vZnt4xcMgpvTUOHS3oPycns3Ze3R8mQviGxAJLaROfM8EJWVlqnDRMeM3EK643TZSV1qISXstCidIyHtNReFFkepGAmdZrrjD8iO_Wq9k8ITStb2uAslwYCUuEA03HpTRo4XNPKT0g-fjVlB21zTLHxQ7FBAnUcRIWDqIZBnJDpptl5FPfY1qD62yRU26-qhJgCRfEtbfdG-1HDPNFgBQgRcwjyJuTVphg8HLdtdO1XXaOYxK3hQqZwi8fR7jZvC-BQSCHSCXkTDXFTgrLhh8uvB2q1PlVnbqE4YEu-pV7XKYDzvCyfXqGjL8nN48OZ-vR-_vEZ2cUSZFtk1R7Zadedfw4grjUvejf9Azp4OSk |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Passive+in-vehicle+driver+breath+alcohol+detection+using+advanced+sensor+signal+acquisition+and+fusion&rft.jtitle=Traffic+injury+prevention&rft.au=Ljungblad%2C+Jonas&rft.au=H%C3%B6k%2C+Bertil&rft.au=Allalou%2C+Amin&rft.au=Pettersson%2C+H%C3%A5kan&rft.date=2017-05-29&rft.issn=1538-957X&rft.eissn=1538-957X&rft.volume=18&rft.issue=sup1&rft.spage=S31&rft_id=info:doi/10.1080%2F15389588.2017.1312688&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1538-9588&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1538-9588&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1538-9588&client=summon |