A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem
SUMMARY In this study, we consider that inter‐day traffic flow fluctuations in a network are caused by stochastic travel behavior. We treat route traffic flows at each time interval as random variables. Therefore, the solution of the stochastic assignment problem should be the conditional joint prob...
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| Veröffentlicht in: | Journal of advanced transportation 2012-07, Vol.46 (3), p.222-235 |
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| container_title | Journal of advanced transportation |
| container_volume | 46 |
| creator | Wei, Chong Asakura, Yasuo Iryo, Takamasa |
| description | SUMMARY
In this study, we consider that inter‐day traffic flow fluctuations in a network are caused by stochastic travel behavior. We treat route traffic flows at each time interval as random variables. Therefore, the solution of the stochastic assignment problem should be the conditional joint probability distribution of the route flows given that the network is in stochastic user equilibrium. We formulate the conditional joint distribution and develop a Gibbs sampler to draw samples from the conditional joint distribution. The characteristics of the route flows at each time interval during the time horizon can be estimated on the basis of the simulated samples. Copyright © 2012 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/atr.214 |
| format | Article |
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In this study, we consider that inter‐day traffic flow fluctuations in a network are caused by stochastic travel behavior. We treat route traffic flows at each time interval as random variables. Therefore, the solution of the stochastic assignment problem should be the conditional joint probability distribution of the route flows given that the network is in stochastic user equilibrium. We formulate the conditional joint distribution and develop a Gibbs sampler to draw samples from the conditional joint distribution. The characteristics of the route flows at each time interval during the time horizon can be estimated on the basis of the simulated samples. Copyright © 2012 John Wiley & Sons, Ltd.</description><identifier>ISSN: 0197-6729</identifier><identifier>EISSN: 2042-3195</identifier><identifier>DOI: 10.1002/atr.214</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Bayes' theorem ; Computer networks ; directed acyclic graph ; Gibbs sampler ; Intervals ; Networks ; Routing (telecommunications) ; Sampling ; stochastic user equilibrium ; Stochasticity ; Traffic flow ; Transportation</subject><ispartof>Journal of advanced transportation, 2012-07, Vol.46 (3), p.222-235</ispartof><rights>Copyright © 2012 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4704-3dab47d7c34db2cec86a368efb14534ab09a0f635c0035844912ffaf0287cf683</citedby><cites>FETCH-LOGICAL-c4704-3dab47d7c34db2cec86a368efb14534ab09a0f635c0035844912ffaf0287cf683</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fatr.214$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fatr.214$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Wei, Chong</creatorcontrib><creatorcontrib>Asakura, Yasuo</creatorcontrib><creatorcontrib>Iryo, Takamasa</creatorcontrib><title>A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem</title><title>Journal of advanced transportation</title><addtitle>J. Adv. Transp</addtitle><description>SUMMARY
In this study, we consider that inter‐day traffic flow fluctuations in a network are caused by stochastic travel behavior. We treat route traffic flows at each time interval as random variables. Therefore, the solution of the stochastic assignment problem should be the conditional joint probability distribution of the route flows given that the network is in stochastic user equilibrium. We formulate the conditional joint distribution and develop a Gibbs sampler to draw samples from the conditional joint distribution. The characteristics of the route flows at each time interval during the time horizon can be estimated on the basis of the simulated samples. Copyright © 2012 John Wiley & Sons, Ltd.</description><subject>Bayes' theorem</subject><subject>Computer networks</subject><subject>directed acyclic graph</subject><subject>Gibbs sampler</subject><subject>Intervals</subject><subject>Networks</subject><subject>Routing (telecommunications)</subject><subject>Sampling</subject><subject>stochastic user equilibrium</subject><subject>Stochasticity</subject><subject>Traffic flow</subject><subject>Transportation</subject><issn>0197-6729</issn><issn>2042-3195</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp10EtLxDAUBeAgCo4P_AvZKUg1rzbtchBfMD5RBDfhNk1momk7JhGdf2-14s7V2XycezkI7VFyRAlhx5DCEaNiDU0YESzjtMrX0YTQSmaFZNUm2orxhRBe5ZWYoHqKl6GvoXbepRVu-8Z4DF2DI7RL77o5Bj_vg0uLFts-4LQw2HXJhKyBFY6p1wuIyWmcAlg7JMTo5l1ruvRT7E27gzYs-Gh2f3MbPZ6dPpxcZLOb88uT6SzTQhKR8QZqIRupuWhqpo0uC-BFaWxNRc4F1KQCYgue6-H5vBSiosxasISVUtui5NvoYOwd7r69m5hU66I23kNn-veoKGO0LEUhv-n-SHXoYwzGqmVwLYSVokR9r6iGFdWw4iAPR_nhvFn9x9T04X7U2ahdTObzT0N4VYXkMldP1-fqbMYv7q5uqXrmX7Nbg1Y</recordid><startdate>201207</startdate><enddate>201207</enddate><creator>Wei, Chong</creator><creator>Asakura, Yasuo</creator><creator>Iryo, Takamasa</creator><general>John Wiley & Sons, Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201207</creationdate><title>A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem</title><author>Wei, Chong ; Asakura, Yasuo ; Iryo, Takamasa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4704-3dab47d7c34db2cec86a368efb14534ab09a0f635c0035844912ffaf0287cf683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Bayes' theorem</topic><topic>Computer networks</topic><topic>directed acyclic graph</topic><topic>Gibbs sampler</topic><topic>Intervals</topic><topic>Networks</topic><topic>Routing (telecommunications)</topic><topic>Sampling</topic><topic>stochastic user equilibrium</topic><topic>Stochasticity</topic><topic>Traffic flow</topic><topic>Transportation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wei, Chong</creatorcontrib><creatorcontrib>Asakura, Yasuo</creatorcontrib><creatorcontrib>Iryo, Takamasa</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of advanced transportation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wei, Chong</au><au>Asakura, Yasuo</au><au>Iryo, Takamasa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem</atitle><jtitle>Journal of advanced transportation</jtitle><addtitle>J. Adv. Transp</addtitle><date>2012-07</date><risdate>2012</risdate><volume>46</volume><issue>3</issue><spage>222</spage><epage>235</epage><pages>222-235</pages><issn>0197-6729</issn><eissn>2042-3195</eissn><abstract>SUMMARY
In this study, we consider that inter‐day traffic flow fluctuations in a network are caused by stochastic travel behavior. We treat route traffic flows at each time interval as random variables. Therefore, the solution of the stochastic assignment problem should be the conditional joint probability distribution of the route flows given that the network is in stochastic user equilibrium. We formulate the conditional joint distribution and develop a Gibbs sampler to draw samples from the conditional joint distribution. The characteristics of the route flows at each time interval during the time horizon can be estimated on the basis of the simulated samples. Copyright © 2012 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/atr.214</doi><tpages>14</tpages></addata></record> |
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| ispartof | Journal of advanced transportation, 2012-07, Vol.46 (3), p.222-235 |
| issn | 0197-6729 2042-3195 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete; EZB-FREE-00999 freely available EZB journals |
| subjects | Bayes' theorem Computer networks directed acyclic graph Gibbs sampler Intervals Networks Routing (telecommunications) Sampling stochastic user equilibrium Stochasticity Traffic flow Transportation |
| title | A probability model and sampling algorithm for the inter-day stochastic traffic assignment problem |
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