Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications
Identifieur interne : 000590 ( Pmc/Curation ); précédent : 000589; suivant : 000591Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications
Auteurs : Jeong Ah Jang ; Hyun Suk Kim ; Han Byeog ChoSource :
- Sensors (Basel, Switzerland) [ 1424-8220 ] ; 2011.
Abstract
The use of newly emerging sensor technologies in traditional roadway systems can provide real-time traffic services to drivers through Telematics and Intelligent Transport Systems (ITSs). This paper introduces a smart roadside system that utilizes various sensors for driver assistance and traffic safety warnings. This paper shows two road application models for a smart roadside system and sensors: a red-light violation warning system for signalized intersections, and a speed advisory system for highways. Evaluation results for the two services are then shown using a micro-simulation method. In the given real-time applications for drivers, the framework and certain algorithms produce a very efficient solution with respect to the roadway type features and sensor type use.
Url:
DOI: 10.3390/s110807420
PubMed: 22164025
PubMed Central: 3231714
Links toward previous steps (curation, corpus...)
- to stream Pmc, to step Corpus: Pour aller vers cette notice dans l'étape Curation :000590
Links to Exploration step
PMC:3231714Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications</title><author><name sortKey="Jang, Jeong Ah" sort="Jang, Jeong Ah" uniqKey="Jang J" first="Jeong Ah" last="Jang">Jeong Ah Jang</name></author><author><name sortKey="Kim, Hyun Suk" sort="Kim, Hyun Suk" uniqKey="Kim H" first="Hyun Suk" last="Kim">Hyun Suk Kim</name></author><author><name sortKey="Cho, Han Byeog" sort="Cho, Han Byeog" uniqKey="Cho H" first="Han Byeog" last="Cho">Han Byeog Cho</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22164025</idno><idno type="pmc">3231714</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231714</idno><idno type="RBID">PMC:3231714</idno><idno type="doi">10.3390/s110807420</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">000590</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000590</idno><idno type="wicri:Area/Pmc/Curation">000590</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000590</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications</title><author><name sortKey="Jang, Jeong Ah" sort="Jang, Jeong Ah" uniqKey="Jang J" first="Jeong Ah" last="Jang">Jeong Ah Jang</name></author><author><name sortKey="Kim, Hyun Suk" sort="Kim, Hyun Suk" uniqKey="Kim H" first="Hyun Suk" last="Kim">Hyun Suk Kim</name></author><author><name sortKey="Cho, Han Byeog" sort="Cho, Han Byeog" uniqKey="Cho H" first="Han Byeog" last="Cho">Han Byeog Cho</name></author></analytic><series><title level="j">Sensors (Basel, Switzerland)</title><idno type="eISSN">1424-8220</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The use of newly emerging sensor technologies in traditional roadway systems can provide real-time traffic services to drivers through Telematics and Intelligent Transport Systems (ITSs). This paper introduces a smart roadside system that utilizes various sensors for driver assistance and traffic safety warnings. This paper shows two road application models for a smart roadside system and sensors: a red-light violation warning system for signalized intersections, and a speed advisory system for highways. Evaluation results for the two services are then shown using a micro-simulation method. In the given real-time applications for drivers, the framework and certain algorithms produce a very efficient solution with respect to the roadway type features and sensor type use.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Hirst, S" uniqKey="Hirst S">S Hirst</name></author><author><name sortKey="Graham, R" uniqKey="Graham R">R Graham</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Klein, La" uniqKey="Klein L">LA Klein</name></author><author><name sortKey="Mills, Mk" uniqKey="Mills M">MK Mills</name></author><author><name sortKey="Gibson, Drp" uniqKey="Gibson D">DRP Gibson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kim, J" uniqKey="Kim J">J Kim</name></author><author><name sortKey="Kwon, Oc" uniqKey="Kwon O">OC Kwon</name></author><author><name sortKey="Kim, H" uniqKey="Kim H">H Kim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pant, P" uniqKey="Pant P">P Pant</name></author><author><name sortKey="Xie, Y" uniqKey="Xie Y">Y Xie</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sunkari, S" uniqKey="Sunkari S">S Sunkari</name></author><author><name sortKey="Messer, C" uniqKey="Messer C">C Messer</name></author><author><name sortKey="Charara, H" uniqKey="Charara H">H Charara</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Carson, J" uniqKey="Carson J">J Carson</name></author><author><name sortKey="Mannering, F" uniqKey="Mannering F">F Mannering</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Elvik, R" uniqKey="Elvik R">R Elvik</name></author><author><name sortKey="Christensen, P" uniqKey="Christensen P">P Christensen</name></author><author><name sortKey="Amundsen, A" uniqKey="Amundsen A">A Amundsen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jang, J" uniqKey="Jang J">J Jang</name></author><author><name sortKey="Kim, H" uniqKey="Kim H">H Kim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jang, J" uniqKey="Jang J">J Jang</name></author><author><name sortKey="Choi, K" uniqKey="Choi K">K Choi</name></author><author><name sortKey="Moon, Yj" uniqKey="Moon Y">YJ Moon</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Jang, J" uniqKey="Jang J">J Jang</name></author><author><name sortKey="Kim, H" uniqKey="Kim H">H Kim</name></author><author><name sortKey="Cho, Hb" uniqKey="Cho H">HB Cho</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Sensors (Basel)</journal-id><journal-title-group><journal-title>Sensors (Basel, Switzerland)</journal-title></journal-title-group><issn pub-type="epub">1424-8220</issn><publisher><publisher-name>Molecular Diversity Preservation International (MDPI)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">22164025</article-id><article-id pub-id-type="pmc">3231714</article-id><article-id pub-id-type="doi">10.3390/s110807420</article-id><article-id pub-id-type="publisher-id">sensors-11-07420</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Jang</surname><given-names>Jeong Ah</given-names></name><xref ref-type="corresp" rid="c1-sensors-11-07420">*</xref></contrib><contrib contrib-type="author"><name><surname>Kim</surname><given-names>Hyun Suk</given-names></name></contrib><contrib contrib-type="author"><name><surname>Cho</surname><given-names>Han Byeog</given-names></name></contrib><aff id="af1-sensors-11-07420">Vehicle-Ship IT Convergence Research Department, ETRI (Electronics and Telecommunications Research Institute), 161 Gajeong-dong, Yuseong-gu, Daejeon 305-350, Korea; E-Mails:<email>hyskim@etri.re.kr</email> (H.S.K.);<email>hbcho@etri.re.kr</email> (H.B.C.)</aff></contrib-group><author-notes><corresp id="c1-sensors-11-07420"><label>*</label>Author to whom correspondence should be addressed; E-Mail: <email>azang@etri.re.kr</email>; Tel.: +82-42-860-5636; Fax: +82-42-860-1085.</corresp></author-notes><pub-date pub-type="collection"><year>2011</year></pub-date><pub-date pub-type="epub"><day>25</day><month>7</month><year>2011</year></pub-date><volume>11</volume><issue>8</issue><fpage>7420</fpage><lpage>7436</lpage><history><date date-type="received"><day>22</day><month>6</month><year>2011</year></date><date date-type="rev-recd"><day>15</day><month>7</month><year>2011</year></date><date date-type="accepted"><day>18</day><month>7</month><year>2011</year></date></history><permissions><copyright-statement>© 2011 by the authors; licensee MDPI, Basel, Switzerland.</copyright-statement><copyright-year>2011</copyright-year><license><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link>).</license-p></license></permissions><abstract><p>The use of newly emerging sensor technologies in traditional roadway systems can provide real-time traffic services to drivers through Telematics and Intelligent Transport Systems (ITSs). This paper introduces a smart roadside system that utilizes various sensors for driver assistance and traffic safety warnings. This paper shows two road application models for a smart roadside system and sensors: a red-light violation warning system for signalized intersections, and a speed advisory system for highways. Evaluation results for the two services are then shown using a micro-simulation method. In the given real-time applications for drivers, the framework and certain algorithms produce a very efficient solution with respect to the roadway type features and sensor type use.</p></abstract><kwd-group><kwd>ITS (Intelligent Traffic Systems)</kwd><kwd>smart roadside server</kwd><kwd>infrastructure-based sensor</kwd><kwd>vehicle sensor</kwd></kwd-group></article-meta></front><floats-group><fig id="f1-sensors-11-07420" position="float"><label>Figure 1.</label><caption><p>Roadway system and ITS technology.</p></caption><graphic xlink:href="sensors-11-07420f1"></graphic></fig><fig id="f2-sensors-11-07420" position="float"><label>Figure 2.</label><caption><p>Examples of infrastructure-based sensors and procedures at an intersection.</p></caption><graphic xlink:href="sensors-11-07420f2"></graphic></fig><fig id="f3-sensors-11-07420" position="float"><label>Figure 3.</label><caption><p>OBDII-based vehicle sensor.</p></caption><graphic xlink:href="sensors-11-07420f3"></graphic></fig><fig id="f4-sensors-11-07420" position="float"><label>Figure 4.</label><caption><p>Framework of smart road server and sensor system.</p></caption><graphic xlink:href="sensors-11-07420f4"></graphic></fig><fig id="f5-sensors-11-07420" position="float"><label>Figure 5.</label><caption><p>Red-light violation warning system at a signalized intersection.</p></caption><graphic xlink:href="sensors-11-07420f5"></graphic></fig><fig id="f6-sensors-11-07420" position="float"><label>Figure 6.</label><caption><p>Flowchart for the red-light violation warning model.</p></caption><graphic xlink:href="sensors-11-07420f6"></graphic></fig><fig id="f7-sensors-11-07420" position="float"><label>Figure 7.</label><caption><p>Signalized intersection test: red-light violation warning at signalized intersection.</p></caption><graphic xlink:href="sensors-11-07420f7"></graphic></fig><fig id="f8-sensors-11-07420" position="float"><label>Figure 8.</label><caption><p>Advisory speed provisioning in a highway system.</p></caption><graphic xlink:href="sensors-11-07420f8"></graphic></fig><fig id="f9-sensors-11-07420" position="float"><label>Figure 9.</label><caption><p>Simulation results. (<bold>a</bold>) Freeway-accident01 (Good traffic condition-accident-dry); (<bold>b</bold>) Freeway-accident11 (Good traffic condition-accident-wet); (<bold>c</bold>) Freeway-accident21 (Good traffic condition-accident-ice).</p></caption><graphic xlink:href="sensors-11-07420f9a"></graphic><graphic xlink:href="sensors-11-07420f9b"></graphic></fig><fig id="f10-sensors-11-07420" position="float"><label>Figure 10.</label><caption><p>Example of a Telematics device with normal information.</p></caption><graphic xlink:href="sensors-11-07420f10"></graphic></fig><fig id="f11-sensors-11-07420" position="float"><label>Figure 11.</label><caption><p>Example of a Telematics device with advisory speed and ice surface information.</p></caption><graphic xlink:href="sensors-11-07420f11"></graphic></fig><table-wrap id="t1-sensors-11-07420" position="float"><label>Table 1.</label><caption><p>Simulation input data.</p></caption><table frame="box" rules="all"><thead><tr><th align="left" valign="middle" rowspan="1" colspan="1"><bold>Categories</bold></th><th colspan="2" align="center" valign="middle" rowspan="1"><bold>Detailed Description</bold></th></tr></thead><tbody><tr><td align="left" valign="middle" rowspan="3" colspan="1">Traffic conditions</td><td align="left" valign="middle" rowspan="1" colspan="1">Input volume (vehicles/h)</td><td align="left" valign="middle" rowspan="1" colspan="1">100, 200, 300, 400, 500, 600, 700, 800, 900, 1,000, 1,100, 1,200, 1,300, 1,400, 1,500 (Total of 15 cases)</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Turning rates</td><td align="left" valign="middle" rowspan="1" colspan="1">Left turn-through-Right turn: 15%–70%–15%</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Classification</td><td align="left" valign="middle" rowspan="1" colspan="1">Passenger cars: 90%, other vehicles: 10%</td></tr><tr><td align="left" valign="middle" rowspan="3" colspan="1">Road conditions</td><td align="left" valign="middle" rowspan="1" colspan="1">Number of lanes</td><td align="left" valign="middle" rowspan="1" colspan="1">4 lanes × 4 lanes</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Lane width</td><td align="left" valign="middle" rowspan="1" colspan="1">3.5 m</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Operation of lanes</td><td align="left" valign="middle" rowspan="1" colspan="1">Lane 1: left turn only, lanes 2–3: through only, lane 4: right turn only</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Signal control</td><td colspan="2" align="left" valign="middle" rowspan="1">Cycle: 120 s, Green time in each direction: 27 s, Yellow time: 3 s, Red time: 90 s, Phase: Simultaneously with Left + Through direction</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Sensing point</td><td colspan="2" align="left" valign="middle" rowspan="1">A total of 50 point sensors in lanes 2 and 3.<break></break>First location is the stop line, with 5 m intervals for further sensors</td></tr></tbody></table></table-wrap><table-wrap id="t2-sensors-11-07420" position="float"><label>Table 2.</label><caption><p>Verification of the model results.</p></caption><table frame="box" rules="all"><thead><tr><th colspan="2" align="center" valign="middle" rowspan="2"><bold>Classification</bold></th><th colspan="2" align="center" valign="middle" rowspan="1"><bold>Real running vehicle status (no. of vehicles)(%) at simulation scenarios</bold></th><th align="center" valign="middle" rowspan="2" colspan="1"><bold>Total no. of vehicles (%)</bold></th></tr><tr><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Red-light violation vehicles</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Non-red-light violation vehicles</bold></th></tr></thead><tbody><tr><td align="center" valign="middle" rowspan="2" colspan="1">Results of prediction (no. of vehicles in %) through suggested algorithms</td><td align="center" valign="middle" rowspan="1" colspan="1">Red-light violation vehicles</td><td align="center" valign="middle" content-type="background-color:#D9D9D9" rowspan="1" colspan="1"><bold>25.3 (4.6%)</bold></td><td align="center" valign="middle" rowspan="1" colspan="1">5.1 (0.9%)</td><td align="center" valign="middle" rowspan="1" colspan="1">30.4 (5.5%)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Non-red-light violation vehicles</td><td align="center" valign="middle" rowspan="1" colspan="1">3.3 (0.6%)</td><td align="center" valign="middle" content-type="background-color:#D9D9D9" rowspan="1" colspan="1"><bold>521.1 (93.9%)</bold></td><td align="center" valign="middle" rowspan="1" colspan="1">524.4 (94.5%)</td></tr><tr><td colspan="2" align="center" valign="middle" rowspan="1">Total no. of vehicles (%)</td><td align="center" valign="middle" content-type="background-color:#D9D9D9" rowspan="1" colspan="1"><bold>28.6 (5.1%)</bold></td><td align="center" valign="middle" rowspan="1" colspan="1">526.3 (94.9%)</td><td align="center" valign="middle" rowspan="1" colspan="1">554.9 (100%)</td></tr></tbody></table></table-wrap><table-wrap id="t3-sensors-11-07420" position="float"><label>Table 3.</label><caption><p>Simulation scenarios.</p></caption><table frame="box" rules="all"><thead><tr><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Traffic condition</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Accident status</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Road surface status (<italic>f<sub>j</sub></italic> (<italic>k</italic>) )</bold></th><th align="center" valign="middle" rowspan="1" colspan="1"><bold>Scenario ID</bold></th></tr></thead><tbody><tr><td align="center" valign="middle" rowspan="6" colspan="1">LOS = C (Input Volume = 1,500 pcphpl)</td><td align="center" valign="middle" rowspan="3" colspan="1">without accident</td><td align="center" valign="middle" rowspan="1" colspan="1">Dry (f = 0.8)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic01</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Wet (f = 0.4)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic11</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Iced (f = 0.2)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic21</td></tr><tr><td align="center" valign="middle" rowspan="3" colspan="1">with accident (accident time = 1,200–2,400 s)</td><td align="center" valign="middle" rowspan="1" colspan="1">Dry (f = 0.8)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-accident01</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Wet (f = 0.4)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-accident11</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Iced (f = 0.2)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-acciden21</td></tr><tr><td align="center" valign="middle" rowspan="6" colspan="1">LOS = F (Input Volume = 2,300 pcphpl)</td><td align="center" valign="middle" rowspan="3" colspan="1">without accident</td><td align="center" valign="middle" rowspan="1" colspan="1">Dry (f = 0.8)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic02</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Wet (f = 0.4)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic12</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Iced (f = 0.2)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-Basic22</td></tr><tr><td align="center" valign="middle" rowspan="3" colspan="1">with accident (accident time = 1,200–2,400 s)</td><td align="center" valign="middle" rowspan="1" colspan="1">Dry (f = 0.8)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-accident02</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Wet (f = 0.4)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-accident12</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Iced (f = 0.2)</td><td align="left" valign="middle" rowspan="1" colspan="1">Freeway-accident22</td></tr></tbody></table></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/TelematiV1/Data/Pmc/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000590 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Curation/biblio.hfd -nk 000590 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= TelematiV1
|flux= Pmc
|étape= Curation
|type= RBID
|clé= PMC:3231714
|texte= Smart Roadside System for Driver Assistance and Safety Warnings: Framework and Applications
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Curation/RBID.i -Sk "pubmed:22164025" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Curation/biblio.hfd \
| NlmPubMed2Wicri -a TelematiV1
| This area was generated with Dilib version V0.6.31. |  |