Large-scale traffic flow simulation based on intelligent PSO
With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2022-01-01
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| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2022/02/matecconf_icpcm2022_02010.pdf |
| _version_ | 1818939470218526720 |
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| author | Liu Zeyu Yang Gongping |
| author_facet | Liu Zeyu Yang Gongping |
| author_sort | Liu Zeyu |
| collection | DOAJ |
| description | With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time. |
| first_indexed | 2024-12-20T06:24:15Z |
| format | Article |
| id | doaj.art-a7eb3e6ffdb04067a1f80db880ef70ef |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-20T06:24:15Z |
| publishDate | 2022-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-a7eb3e6ffdb04067a1f80db880ef70ef2022-12-21T19:50:21ZengEDP SciencesMATEC Web of Conferences2261-236X2022-01-013550201010.1051/matecconf/202235502010matecconf_icpcm2022_02010Large-scale traffic flow simulation based on intelligent PSOLiu Zeyu0Yang Gongping1Jinan Foreign Language School International CenterSchool of Software, Shandong UniversityWith the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.https://www.matec-conferences.org/articles/matecconf/pdf/2022/02/matecconf_icpcm2022_02010.pdftraffic flow simulationintelligent psonetlogo |
| spellingShingle | Liu Zeyu Yang Gongping Large-scale traffic flow simulation based on intelligent PSO MATEC Web of Conferences traffic flow simulation intelligent pso netlogo |
| title | Large-scale traffic flow simulation based on intelligent PSO |
| title_full | Large-scale traffic flow simulation based on intelligent PSO |
| title_fullStr | Large-scale traffic flow simulation based on intelligent PSO |
| title_full_unstemmed | Large-scale traffic flow simulation based on intelligent PSO |
| title_short | Large-scale traffic flow simulation based on intelligent PSO |
| title_sort | large scale traffic flow simulation based on intelligent pso |
| topic | traffic flow simulation intelligent pso netlogo |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2022/02/matecconf_icpcm2022_02010.pdf |
| work_keys_str_mv | AT liuzeyu largescaletrafficflowsimulationbasedonintelligentpso AT yanggongping largescaletrafficflowsimulationbasedonintelligentpso |