Road traffic congestion measurement considering impacts on travelers
The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfact...
Gespeichert in:
| Veröffentlicht in: | Journal of modern transportation 2013-03, Vol.21 (1), p.28-39 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 39 |
|---|---|
| container_issue | 1 |
| container_start_page | 28 |
| container_title | Journal of modern transportation |
| container_volume | 21 |
| creator | Ye, Liang Hui, Ying Yang, Dongyuan |
| description | The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion. |
| doi_str_mv | 10.1007/s40534-013-0005-z |
| format | Article |
| fullrecord | <record><control><sourceid>wanfang_jour_proqu</sourceid><recordid>TN_cdi_wanfang_journals_xnjtdxxb_e201301005</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cqvip_id>45429389</cqvip_id><wanfj_id>xnjtdxxb_e201301005</wanfj_id><sourcerecordid>xnjtdxxb_e201301005</sourcerecordid><originalsourceid>FETCH-LOGICAL-c454t-7bf118ea1ede89d4a133796a288f6f2d2e0c4c1452bd65f94d39bf224e3a03933</originalsourceid><addsrcrecordid>eNp9kV1LwzAYhYsoOOZ-gHcVbwSp5jvNpcxPGAii4F3I2jezY023pNO5X29qZYgXXiWE55z3zTlJcozRBUZIXgaGOGUZwjRDCPFsu5cMCFYiQ1zK_XhHimcol6-HySiEeWSwEILwfJBcPzWmTFtvrK2KtGjcDEJbNS6twYS1hxpc2z2HqgRfuVla1UtTtCGNSFS9wwJ8OEoOrFkEGP2cw-Tl9uZ5fJ9NHu8exleTrGCctZmcWoxzMBhKyFXJDKZUKmFInlthSUkAFazAjJNpKbhVrKRqaglhQA2iitJhct77fhhnjZvpebP2Lk7UGzdvy81mqoHEFFBMhUf6rKeXvlmt47d0XYUCFgvjoFkHjWUusKT5t_HpH3TnjAUnSjKFUaRwTxW-CcGD1Utf1cZ_aox0V4Tui9BxBd0VobdRQ3pNWHbxgf_l_I_o5GfQWyxkFXW7STFIorqdvwAB-ZYX</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1652974910</pqid></control><display><type>article</type><title>Road traffic congestion measurement considering impacts on travelers</title><source>DOAJ Directory of Open Access Journals</source><source>Alma/SFX Local Collection</source><creator>Ye, Liang ; Hui, Ying ; Yang, Dongyuan</creator><creatorcontrib>Ye, Liang ; Hui, Ying ; Yang, Dongyuan</creatorcontrib><description>The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.</description><identifier>ISSN: 2095-087X</identifier><identifier>ISSN: 2662-4745</identifier><identifier>EISSN: 2196-0577</identifier><identifier>EISSN: 2662-4753</identifier><identifier>DOI: 10.1007/s40534-013-0005-z</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Automotive Engineering ; Congestion ; Engineering ; Estimates ; Foundations ; Geoengineering ; Hydraulics ; Indicators ; Logit模型 ; Mathematical models ; Policies ; Principal components analysis ; Regional/Spatial Science ; Traffic ; Traffic engineering ; Traffic flow ; Transportation ; Transportation policy ; 主成分分析 ; 交通拥堵 ; 出行时间 ; 旅客 ; 测量 ; 线性回归模型 ; 道路</subject><ispartof>Journal of modern transportation, 2013-03, Vol.21 (1), p.28-39</ispartof><rights>The Author(s) 2013</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c454t-7bf118ea1ede89d4a133796a288f6f2d2e0c4c1452bd65f94d39bf224e3a03933</citedby><cites>FETCH-LOGICAL-c454t-7bf118ea1ede89d4a133796a288f6f2d2e0c4c1452bd65f94d39bf224e3a03933</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/85396A/85396A.jpg</thumbnail><link.rule.ids>314,780,784,864,27923,27924</link.rule.ids></links><search><creatorcontrib>Ye, Liang</creatorcontrib><creatorcontrib>Hui, Ying</creatorcontrib><creatorcontrib>Yang, Dongyuan</creatorcontrib><title>Road traffic congestion measurement considering impacts on travelers</title><title>Journal of modern transportation</title><addtitle>J. Mod. Transport</addtitle><addtitle>Journal of Modern Transportation</addtitle><description>The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.</description><subject>Automotive Engineering</subject><subject>Congestion</subject><subject>Engineering</subject><subject>Estimates</subject><subject>Foundations</subject><subject>Geoengineering</subject><subject>Hydraulics</subject><subject>Indicators</subject><subject>Logit模型</subject><subject>Mathematical models</subject><subject>Policies</subject><subject>Principal components analysis</subject><subject>Regional/Spatial Science</subject><subject>Traffic</subject><subject>Traffic engineering</subject><subject>Traffic flow</subject><subject>Transportation</subject><subject>Transportation policy</subject><subject>主成分分析</subject><subject>交通拥堵</subject><subject>出行时间</subject><subject>旅客</subject><subject>测量</subject><subject>线性回归模型</subject><subject>道路</subject><issn>2095-087X</issn><issn>2662-4745</issn><issn>2196-0577</issn><issn>2662-4753</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kV1LwzAYhYsoOOZ-gHcVbwSp5jvNpcxPGAii4F3I2jezY023pNO5X29qZYgXXiWE55z3zTlJcozRBUZIXgaGOGUZwjRDCPFsu5cMCFYiQ1zK_XhHimcol6-HySiEeWSwEILwfJBcPzWmTFtvrK2KtGjcDEJbNS6twYS1hxpc2z2HqgRfuVla1UtTtCGNSFS9wwJ8OEoOrFkEGP2cw-Tl9uZ5fJ9NHu8exleTrGCctZmcWoxzMBhKyFXJDKZUKmFInlthSUkAFazAjJNpKbhVrKRqaglhQA2iitJhct77fhhnjZvpebP2Lk7UGzdvy81mqoHEFFBMhUf6rKeXvlmt47d0XYUCFgvjoFkHjWUusKT5t_HpH3TnjAUnSjKFUaRwTxW-CcGD1Utf1cZ_aox0V4Tui9BxBd0VobdRQ3pNWHbxgf_l_I_o5GfQWyxkFXW7STFIorqdvwAB-ZYX</recordid><startdate>20130301</startdate><enddate>20130301</enddate><creator>Ye, Liang</creator><creator>Hui, Ying</creator><creator>Yang, Dongyuan</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>Transport Planning and Research Institute, Ministry of Transport of China, Beijing 10028, China%School of Transportation Engineering, Tongji University,Shanghai 201804, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>7SU</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20130301</creationdate><title>Road traffic congestion measurement considering impacts on travelers</title><author>Ye, Liang ; Hui, Ying ; Yang, Dongyuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c454t-7bf118ea1ede89d4a133796a288f6f2d2e0c4c1452bd65f94d39bf224e3a03933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Automotive Engineering</topic><topic>Congestion</topic><topic>Engineering</topic><topic>Estimates</topic><topic>Foundations</topic><topic>Geoengineering</topic><topic>Hydraulics</topic><topic>Indicators</topic><topic>Logit模型</topic><topic>Mathematical models</topic><topic>Policies</topic><topic>Principal components analysis</topic><topic>Regional/Spatial Science</topic><topic>Traffic</topic><topic>Traffic engineering</topic><topic>Traffic flow</topic><topic>Transportation</topic><topic>Transportation policy</topic><topic>主成分分析</topic><topic>交通拥堵</topic><topic>出行时间</topic><topic>旅客</topic><topic>测量</topic><topic>线性回归模型</topic><topic>道路</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ye, Liang</creatorcontrib><creatorcontrib>Hui, Ying</creatorcontrib><creatorcontrib>Yang, Dongyuan</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Journal of modern transportation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ye, Liang</au><au>Hui, Ying</au><au>Yang, Dongyuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Road traffic congestion measurement considering impacts on travelers</atitle><jtitle>Journal of modern transportation</jtitle><stitle>J. Mod. Transport</stitle><addtitle>Journal of Modern Transportation</addtitle><date>2013-03-01</date><risdate>2013</risdate><volume>21</volume><issue>1</issue><spage>28</spage><epage>39</epage><pages>28-39</pages><issn>2095-087X</issn><issn>2662-4745</issn><eissn>2196-0577</eissn><eissn>2662-4753</eissn><abstract>The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40534-013-0005-z</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2095-087X |
| ispartof | Journal of modern transportation, 2013-03, Vol.21 (1), p.28-39 |
| issn | 2095-087X 2662-4745 2196-0577 2662-4753 |
| language | eng |
| recordid | cdi_wanfang_journals_xnjtdxxb_e201301005 |
| source | DOAJ Directory of Open Access Journals; Alma/SFX Local Collection |
| subjects | Automotive Engineering Congestion Engineering Estimates Foundations Geoengineering Hydraulics Indicators Logit模型 Mathematical models Policies Principal components analysis Regional/Spatial Science Traffic Traffic engineering Traffic flow Transportation Transportation policy 主成分分析 交通拥堵 出行时间 旅客 测量 线性回归模型 道路 |
| title | Road traffic congestion measurement considering impacts on travelers |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T19%3A55%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wanfang_jour_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Road%20traffic%20congestion%20measurement%20considering%20impacts%20on%20travelers&rft.jtitle=Journal%20of%20modern%20transportation&rft.au=Ye,%20Liang&rft.date=2013-03-01&rft.volume=21&rft.issue=1&rft.spage=28&rft.epage=39&rft.pages=28-39&rft.issn=2095-087X&rft.eissn=2196-0577&rft_id=info:doi/10.1007/s40534-013-0005-z&rft_dat=%3Cwanfang_jour_proqu%3Exnjtdxxb_e201301005%3C/wanfang_jour_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1652974910&rft_id=info:pmid/&rft_cqvip_id=45429389&rft_wanfj_id=xnjtdxxb_e201301005&rfr_iscdi=true |