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Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops
Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersec...
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Published in: | Systems (Basel) 2023-07, Vol.11 (7), p.366 |
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description | Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. The importance of considering location planning of BRT stops when optimizing the offset is thereby verified. |
doi_str_mv | 10.3390/systems11070366 |
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This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. The importance of considering location planning of BRT stops when optimizing the offset is thereby verified.</description><identifier>ISSN: 2079-8954</identifier><identifier>EISSN: 2079-8954</identifier><identifier>DOI: 10.3390/systems11070366</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Automobiles ; BRT ; bus stop location ; Buses ; Buses (vehicles) ; Carbon ; Combinatorial analysis ; Emissions ; Energy consumption ; Local transit ; Mathematical programming ; offset optimization ; Optimization ; Optimization models ; Planning ; Prediction models ; Programming languages ; Public transportation ; Rapid transit systems ; Signal delay ; signalized intersection ; Traffic congestion ; Traffic control ; Traffic flow ; Traffic intersections ; Travel time ; Veins & arteries</subject><ispartof>Systems (Basel), 2023-07, Vol.11 (7), p.366</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c369t-45fd17a605fce97dae811d36f010a309c5568fa163cae4fcc5b876a7de14d0c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2843119753/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2843119753?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,74998</link.rule.ids></links><search><creatorcontrib>Wu, Wei</creatorcontrib><creatorcontrib>Luo, Xiaoyu</creatorcontrib><creatorcontrib>Shi, Baiying</creatorcontrib><title>Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops</title><title>Systems (Basel)</title><description>Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. The importance of considering location planning of BRT stops when optimizing the offset is thereby verified.</description><subject>Automobiles</subject><subject>BRT</subject><subject>bus stop location</subject><subject>Buses</subject><subject>Buses (vehicles)</subject><subject>Carbon</subject><subject>Combinatorial analysis</subject><subject>Emissions</subject><subject>Energy consumption</subject><subject>Local transit</subject><subject>Mathematical programming</subject><subject>offset optimization</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>Planning</subject><subject>Prediction models</subject><subject>Programming languages</subject><subject>Public transportation</subject><subject>Rapid transit systems</subject><subject>Signal delay</subject><subject>signalized intersection</subject><subject>Traffic congestion</subject><subject>Traffic control</subject><subject>Traffic flow</subject><subject>Traffic intersections</subject><subject>Travel time</subject><subject>Veins & arteries</subject><issn>2079-8954</issn><issn>2079-8954</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkUFrGzEQhZfSQkOSc6-Cnp1Illa7OqYmaQ0OLiR3MR6NXJn1ypHkQ_Lrq-2GUqqDNMy892mYaZovgt9Iafhtfs2FjlkI3nGp9YfmYsk7s-hNqz7-E39urnM-8HqMkL1WF81x632mwranEo7hDUqII3uMjgbmY2JPYT_CEN7IsfVYKGXCSZHZql7BUQrjnpVfNPthYJuIM-PnAOM4VaNn386ZPZV4ylfNJw9Dpuv397J5frh_Xv1YbLbf16u7zQKlNmWhWu9EB5q3Hsl0DqgXwkntueAgucG21b0HoSUCKY_Y7vpOQ-dIKMdRXjbrGesiHOwp1c7Sq40Q7J9ETHsLqQQcyCIgaOd6Z3Y7Rbg05HvHJSrUUH-UlfV1Zp1SfDlTLvYQz6kOJdtlr6QQpmsn1c2s2kOFhtHHkmBiOzoGjCP5UPN3XWuWUnNlquF2NmCKOSfyf9sU3E4rtf-tVP4GusWYAQ</recordid><startdate>20230701</startdate><enddate>20230701</enddate><creator>Wu, Wei</creator><creator>Luo, Xiaoyu</creator><creator>Shi, Baiying</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>DOA</scope></search><sort><creationdate>20230701</creationdate><title>Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops</title><author>Wu, Wei ; Luo, Xiaoyu ; Shi, Baiying</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-45fd17a605fce97dae811d36f010a309c5568fa163cae4fcc5b876a7de14d0c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Automobiles</topic><topic>BRT</topic><topic>bus stop location</topic><topic>Buses</topic><topic>Buses (vehicles)</topic><topic>Carbon</topic><topic>Combinatorial analysis</topic><topic>Emissions</topic><topic>Energy consumption</topic><topic>Local transit</topic><topic>Mathematical programming</topic><topic>offset optimization</topic><topic>Optimization</topic><topic>Optimization models</topic><topic>Planning</topic><topic>Prediction models</topic><topic>Programming languages</topic><topic>Public transportation</topic><topic>Rapid transit systems</topic><topic>Signal delay</topic><topic>signalized intersection</topic><topic>Traffic congestion</topic><topic>Traffic control</topic><topic>Traffic flow</topic><topic>Traffic intersections</topic><topic>Travel time</topic><topic>Veins & arteries</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Wei</creatorcontrib><creatorcontrib>Luo, Xiaoyu</creatorcontrib><creatorcontrib>Shi, Baiying</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</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>ProQuest Central Basic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Systems (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Wei</au><au>Luo, Xiaoyu</au><au>Shi, Baiying</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops</atitle><jtitle>Systems (Basel)</jtitle><date>2023-07-01</date><risdate>2023</risdate><volume>11</volume><issue>7</issue><spage>366</spage><pages>366-</pages><issn>2079-8954</issn><eissn>2079-8954</eissn><abstract>Existing offset optimization methods for signalized intersections are mainly focused on regular traffic flow, which cannot accommodate cars and public transit (e.g., Bus Rapid Transit (BRT)) simultaneously. This study proposes a delay prediction model to formulate the signal delay of BRT at intersections. The relation among the green wave bandwidth, signal timing plans, speed of the BRT vehicles, distance between the intersections, and the offset is also modeled. A combinatorial optimization model is then established, which takes the location planning of BRT stops and the offset of intersections at both directions along the artery as the decision variables. The proposed model is programmed with Mathematical Programming Language (AMPL) and solved efficiently by the Gurobi solver. The proposed optimization method is compared with seven different methods. The results show that the average BRT travel time is reduced by at least 19% and the green wave bandwidth is increased by around 30.2%. 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subjects | Automobiles BRT bus stop location Buses Buses (vehicles) Carbon Combinatorial analysis Emissions Energy consumption Local transit Mathematical programming offset optimization Optimization Optimization models Planning Prediction models Programming languages Public transportation Rapid transit systems Signal delay signalized intersection Traffic congestion Traffic control Traffic flow Traffic intersections Travel time Veins & arteries |
title | Offset Optimization Model for Signalized Intersections Considering the Optimal Location Planning of Bus Stops |
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