Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity
Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2020-04, Vol.21 (4), p.1677-1686 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1686 |
---|---|
container_issue | 4 |
container_start_page | 1677 |
container_title | IEEE transactions on intelligent transportation systems |
container_volume | 21 |
creator | Makridis, Michail Mattas, Konstantinos Ciuffo, Biagio |
description | Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller's theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller's response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity. |
doi_str_mv | 10.1109/TITS.2019.2948646 |
format | Article |
fullrecord | <record><control><sourceid>proquest_webof</sourceid><recordid>TN_cdi_webofscience_primary_000523478400029</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8884686</ieee_id><sourcerecordid>2384314557</sourcerecordid><originalsourceid>FETCH-LOGICAL-c336t-3327e0dd5550046c205f255c14d449a58a32d48abddc95b5cae0cb751ce281ce3</originalsourceid><addsrcrecordid>eNqNkEtLAzEUhQdR8PkDxE3ApUzNc5pZlsFHQVC0roc0uYORNhmT1FKX_nJTR3TrJjm553w3cIrilOARIbi-nE1nTyOKST2iNZcVr3aKAyKELDEm1e5WU17WWOD94jDG1zzlgpCD4vMRYu9dBDSzS0DKmUHcgjJrtUG-yzM0MapP9h1QE1Y2ZxvvUvCLEZo4dLXsbbBaLVDzooLSCYL9UMl6973twSdwyWZ7uuyzG1E2Hr0yqFH5bdPmuNjr1CLCyc99VDxfX82a2_Lu_mbaTO5KzViVSsboGLAxQgiMeaUpFh0VQhNuOK-VkIpRw6WaG6NrMRdaAdbzsSAaqMwHOyrOh7198G8riKl99avg8pctZZKz3IgY5xQZUjr4GAN0bR_sUoVNS3C7rbrdVt1uq25_qs7MxcCsYe67qC04Db8cxlhQxseSZ0XrnJb_Tzc2fXfZ-JVLGT0bUAvwh0gpeSUr9gVocZu_</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2384314557</pqid></control><display><type>article</type><title>Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity</title><source>Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /></source><source>IEEE Electronic Library (IEL)</source><creator>Makridis, Michail ; Mattas, Konstantinos ; Ciuffo, Biagio</creator><creatorcontrib>Makridis, Michail ; Mattas, Konstantinos ; Ciuffo, Biagio</creatorcontrib><description>Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller's theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller's response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity.</description><identifier>ISSN: 1524-9050</identifier><identifier>EISSN: 1558-0016</identifier><identifier>DOI: 10.1109/TITS.2019.2948646</identifier><identifier>CODEN: ITISFG</identifier><language>eng</language><publisher>PISCATAWAY: IEEE</publisher><subject>Acceleration ; Adaptive control ; Adaptive cruise control ; Automation ; Car following ; Controllers ; Cruise control ; Delays ; Engineering ; Engineering, Civil ; Engineering, Electrical & Electronic ; Parameters ; Response time ; Roads ; Science & Technology ; Technology ; Time factors ; time headway ; Traffic capacity ; Traffic flow ; traffic simulation ; Transportation ; Transportation Science & Technology ; Vehicles</subject><ispartof>IEEE transactions on intelligent transportation systems, 2020-04, Vol.21 (4), p.1677-1686</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>80</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000523478400029</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c336t-3327e0dd5550046c205f255c14d449a58a32d48abddc95b5cae0cb751ce281ce3</citedby><cites>FETCH-LOGICAL-c336t-3327e0dd5550046c205f255c14d449a58a32d48abddc95b5cae0cb751ce281ce3</cites><orcidid>0000-0003-3734-4264 ; 0000-0001-7462-4674 ; 0000-0002-6463-2416</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8884686$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,797,27929,27930,28253,54763</link.rule.ids></links><search><creatorcontrib>Makridis, Michail</creatorcontrib><creatorcontrib>Mattas, Konstantinos</creatorcontrib><creatorcontrib>Ciuffo, Biagio</creatorcontrib><title>Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity</title><title>IEEE transactions on intelligent transportation systems</title><addtitle>TITS</addtitle><addtitle>IEEE T INTELL TRANSP</addtitle><description>Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller's theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller's response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity.</description><subject>Acceleration</subject><subject>Adaptive control</subject><subject>Adaptive cruise control</subject><subject>Automation</subject><subject>Car following</subject><subject>Controllers</subject><subject>Cruise control</subject><subject>Delays</subject><subject>Engineering</subject><subject>Engineering, Civil</subject><subject>Engineering, Electrical & Electronic</subject><subject>Parameters</subject><subject>Response time</subject><subject>Roads</subject><subject>Science & Technology</subject><subject>Technology</subject><subject>Time factors</subject><subject>time headway</subject><subject>Traffic capacity</subject><subject>Traffic flow</subject><subject>traffic simulation</subject><subject>Transportation</subject><subject>Transportation Science & Technology</subject><subject>Vehicles</subject><issn>1524-9050</issn><issn>1558-0016</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>AOWDO</sourceid><recordid>eNqNkEtLAzEUhQdR8PkDxE3ApUzNc5pZlsFHQVC0roc0uYORNhmT1FKX_nJTR3TrJjm553w3cIrilOARIbi-nE1nTyOKST2iNZcVr3aKAyKELDEm1e5WU17WWOD94jDG1zzlgpCD4vMRYu9dBDSzS0DKmUHcgjJrtUG-yzM0MapP9h1QE1Y2ZxvvUvCLEZo4dLXsbbBaLVDzooLSCYL9UMl6973twSdwyWZ7uuyzG1E2Hr0yqFH5bdPmuNjr1CLCyc99VDxfX82a2_Lu_mbaTO5KzViVSsboGLAxQgiMeaUpFh0VQhNuOK-VkIpRw6WaG6NrMRdaAdbzsSAaqMwHOyrOh7198G8riKl99avg8pctZZKz3IgY5xQZUjr4GAN0bR_sUoVNS3C7rbrdVt1uq25_qs7MxcCsYe67qC04Db8cxlhQxseSZ0XrnJb_Tzc2fXfZ-JVLGT0bUAvwh0gpeSUr9gVocZu_</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Makridis, Michail</creator><creator>Mattas, Konstantinos</creator><creator>Ciuffo, Biagio</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AOWDO</scope><scope>BLEPL</scope><scope>DTL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-3734-4264</orcidid><orcidid>https://orcid.org/0000-0001-7462-4674</orcidid><orcidid>https://orcid.org/0000-0002-6463-2416</orcidid></search><sort><creationdate>20200401</creationdate><title>Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity</title><author>Makridis, Michail ; Mattas, Konstantinos ; Ciuffo, Biagio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c336t-3327e0dd5550046c205f255c14d449a58a32d48abddc95b5cae0cb751ce281ce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Acceleration</topic><topic>Adaptive control</topic><topic>Adaptive cruise control</topic><topic>Automation</topic><topic>Car following</topic><topic>Controllers</topic><topic>Cruise control</topic><topic>Delays</topic><topic>Engineering</topic><topic>Engineering, Civil</topic><topic>Engineering, Electrical & Electronic</topic><topic>Parameters</topic><topic>Response time</topic><topic>Roads</topic><topic>Science & Technology</topic><topic>Technology</topic><topic>Time factors</topic><topic>time headway</topic><topic>Traffic capacity</topic><topic>Traffic flow</topic><topic>traffic simulation</topic><topic>Transportation</topic><topic>Transportation Science & Technology</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Makridis, Michail</creatorcontrib><creatorcontrib>Mattas, Konstantinos</creatorcontrib><creatorcontrib>Ciuffo, Biagio</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on intelligent transportation systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Makridis, Michail</au><au>Mattas, Konstantinos</au><au>Ciuffo, Biagio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity</atitle><jtitle>IEEE transactions on intelligent transportation systems</jtitle><stitle>TITS</stitle><stitle>IEEE T INTELL TRANSP</stitle><date>2020-04-01</date><risdate>2020</risdate><volume>21</volume><issue>4</issue><spage>1677</spage><epage>1686</epage><pages>1677-1686</pages><issn>1524-9050</issn><eissn>1558-0016</eissn><coden>ITISFG</coden><abstract>Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller's theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller's response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity.</abstract><cop>PISCATAWAY</cop><pub>IEEE</pub><doi>10.1109/TITS.2019.2948646</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3734-4264</orcidid><orcidid>https://orcid.org/0000-0001-7462-4674</orcidid><orcidid>https://orcid.org/0000-0002-6463-2416</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1524-9050 |
ispartof | IEEE transactions on intelligent transportation systems, 2020-04, Vol.21 (4), p.1677-1686 |
issn | 1524-9050 1558-0016 |
language | eng |
recordid | cdi_webofscience_primary_000523478400029 |
source | Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; IEEE Electronic Library (IEL) |
subjects | Acceleration Adaptive control Adaptive cruise control Automation Car following Controllers Cruise control Delays Engineering Engineering, Civil Engineering, Electrical & Electronic Parameters Response time Roads Science & Technology Technology Time factors time headway Traffic capacity Traffic flow traffic simulation Transportation Transportation Science & Technology Vehicles |
title | Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-15T02%3A38%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_webof&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Response%20Time%20and%20Time%20Headway%20of%20an%20Adaptive%20Cruise%20Control.%20An%20Empirical%20Characterization%20and%20Potential%20Impacts%20on%20Road%20Capacity&rft.jtitle=IEEE%20transactions%20on%20intelligent%20transportation%20systems&rft.au=Makridis,%20Michail&rft.date=2020-04-01&rft.volume=21&rft.issue=4&rft.spage=1677&rft.epage=1686&rft.pages=1677-1686&rft.issn=1524-9050&rft.eissn=1558-0016&rft.coden=ITISFG&rft_id=info:doi/10.1109/TITS.2019.2948646&rft_dat=%3Cproquest_webof%3E2384314557%3C/proquest_webof%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2384314557&rft_id=info:pmid/&rft_ieee_id=8884686&rfr_iscdi=true |