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BioTraffic: a bio-inspired behavioral model to vehicle traffic simulation
This paper presents a new microscopic model to simulate the behavior of vehicle traffic through a bio-inspired agent-based method. The proposed model reinterprets a biologically-motivated method for generating leaf venation patterns in order to propose terrain reasoning, a technique that has been wi...
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creator | de Quadros, Carlos Eduardo Pereira Adamatti, Diana Francisca de Lima Bicho, Alessandro |
description | This paper presents a new microscopic model to simulate the behavior of vehicle traffic through a bio-inspired agent-based method. The proposed model reinterprets a biologically-motivated method for generating leaf venation patterns in order to propose terrain reasoning, a technique that has been widely used in simulations and games. The main idea is to represent unoccupied spaces through abstract markers distributed in the environment. These markers identify free regions for the movement of vehicles in the simulated traffic environment. The markers provide space information and report the vehicular flow of the simulated scenario, including flow density and velocity. Typical behaviors observed in real traffic, including inhomogeneous driver models, lane changing and merging trajectories, are emergent properties of the proposed model. We demonstrate the flexibility and robustness of our model on simulation environments, comparing the statistical results with a commercial software used for traffic simulation. |
doi_str_mv | 10.1109/SBGames54170.2021.00014 |
format | conference_proceeding |
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We demonstrate the flexibility and robustness of our model on simulation environments, comparing the statistical results with a commercial software used for traffic simulation.</description><subject>agent-based systems</subject><subject>Analytical models</subject><subject>behavioral models</subject><subject>Biological system modeling</subject><subject>Computational modeling</subject><subject>Games</subject><subject>lane changing</subject><subject>lane merging</subject><subject>Merging</subject><subject>Space vehicles</subject><subject>terrain reasoning</subject><subject>traffic simulation</subject><subject>Visualization</subject><issn>2159-6662</issn><isbn>9781665401890</isbn><isbn>1665401893</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2021</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjM1KAzEURqMgWOo8gQvzAjPm5j_ubNFaKLiwrksySeiVmU6ZjAXf3kK7-hbnnI-QJ2ANAHPPX4uV71NREgxrOOPQMMZA3pDKGQtaK8nAOnZLZhyUq7XW_J5UpfycNQHGOGlnZL3AYTv6nLF9oZ4GHGo8lCOOKdKQ9v6Ew-g72g8xdXQa6Cntse0SnS4NLdj_dn7C4fBA7rLvSqquOyff72_b5Ue9-Vytl6-bGjkTUy1lisaKYL0ynDvhnJJRWMtz5NEJZrhos9A2a5Zk67MPPoCBMwMjVAhiTh4vv5hS2h1H7P34t3NaGGVA_AODk08E</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>de Quadros, Carlos Eduardo Pereira</creator><creator>Adamatti, Diana Francisca</creator><creator>de Lima Bicho, Alessandro</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>202110</creationdate><title>BioTraffic: a bio-inspired behavioral model to vehicle traffic simulation</title><author>de Quadros, Carlos Eduardo Pereira ; Adamatti, Diana Francisca ; de Lima Bicho, Alessandro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i203t-44ed783b8a5722939954d3882fd2d930723cf368f60e4cafabab1712d91735bb3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2021</creationdate><topic>agent-based systems</topic><topic>Analytical models</topic><topic>behavioral models</topic><topic>Biological system modeling</topic><topic>Computational modeling</topic><topic>Games</topic><topic>lane changing</topic><topic>lane merging</topic><topic>Merging</topic><topic>Space vehicles</topic><topic>terrain reasoning</topic><topic>traffic simulation</topic><topic>Visualization</topic><toplevel>online_resources</toplevel><creatorcontrib>de Quadros, Carlos Eduardo Pereira</creatorcontrib><creatorcontrib>Adamatti, Diana Francisca</creatorcontrib><creatorcontrib>de Lima Bicho, Alessandro</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>de Quadros, Carlos Eduardo Pereira</au><au>Adamatti, Diana Francisca</au><au>de Lima Bicho, Alessandro</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>BioTraffic: a bio-inspired behavioral model to vehicle traffic simulation</atitle><btitle>2021 20th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames)</btitle><stitle>SBGAMES</stitle><date>2021-10</date><risdate>2021</risdate><spage>29</spage><epage>38</epage><pages>29-38</pages><eissn>2159-6662</eissn><eisbn>9781665401890</eisbn><eisbn>1665401893</eisbn><coden>IEEPAD</coden><abstract>This paper presents a new microscopic model to simulate the behavior of vehicle traffic through a bio-inspired agent-based method. The proposed model reinterprets a biologically-motivated method for generating leaf venation patterns in order to propose terrain reasoning, a technique that has been widely used in simulations and games. The main idea is to represent unoccupied spaces through abstract markers distributed in the environment. These markers identify free regions for the movement of vehicles in the simulated traffic environment. The markers provide space information and report the vehicular flow of the simulated scenario, including flow density and velocity. Typical behaviors observed in real traffic, including inhomogeneous driver models, lane changing and merging trajectories, are emergent properties of the proposed model. We demonstrate the flexibility and robustness of our model on simulation environments, comparing the statistical results with a commercial software used for traffic simulation.</abstract><pub>IEEE</pub><doi>10.1109/SBGames54170.2021.00014</doi><tpages>10</tpages></addata></record> |
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identifier | EISSN: 2159-6662 |
ispartof | 2021 20th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), 2021, p.29-38 |
issn | 2159-6662 |
language | eng |
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source | IEEE Xplore All Conference Series |
subjects | agent-based systems Analytical models behavioral models Biological system modeling Computational modeling Games lane changing lane merging Merging Space vehicles terrain reasoning traffic simulation Visualization |
title | BioTraffic: a bio-inspired behavioral model to vehicle traffic simulation |
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