A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy
Intelligent transportation systems (ITSs) present new opportunities for enhanced traffic management by leveraging advanced driving behavior sensors and real-time information exchange via vehicle-based and cloud–vehicle communication technologies. Specifically, onboard sensors can effectively detect...
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MDPI AG
2024-11-01
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| author | Xiao Liang Chuan-Zhi Thomas Xie Hui-Fang Song Yong-Jie Guo Jian-Xin Peng |
| author_facet | Xiao Liang Chuan-Zhi Thomas Xie Hui-Fang Song Yong-Jie Guo Jian-Xin Peng |
| author_sort | Xiao Liang |
| collection | DOAJ |
| description | Intelligent transportation systems (ITSs) present new opportunities for enhanced traffic management by leveraging advanced driving behavior sensors and real-time information exchange via vehicle-based and cloud–vehicle communication technologies. Specifically, onboard sensors can effectively detect whether human-driven vehicles are adhering to traffic management directives. However, the formulation and validation of effective strategies for vehicle implementation rely on accurate driving behavior models and reliable model-based testing; in this paper, we focus on large roundabouts as the research scenario. To address this, we proposed the Three-Stage Cellular Automata (TSCA) model based on empirical observations, dividing the vehicle journey over roundabouts into three stages: entrance, following, and exit. Furthermore, four optimization strategies were developed based on empirical observations and simulation results, using the traffic efficiency, delay time, and dangerous interaction frequency as key evaluation indicators. Numerical tests reveal that dangerous interactions and delays primarily occurred when the roundabout Road Occupancy Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math></inline-formula>) ranged from 0.12 to 0.24, during which times the vehicle speed also decreased rapidly. Among the strategies, the Path Selection Based on Road Occupancy Rate Recognition Strategy (Simulation 4) demonstrated the best overall performance, increasing the traffic efficiency by 15.65% while reducing the delay time, dangerous interactions, and frequency by 6.50%, 28.32%, and 38.03%, respectively. Additionally, the Entrance Facility Optimization Strategy (Simulation 1) reduced the delay time by 6.90%. While space-based optimization strategies had a more moderate overall impact, they significantly improved the local traffic efficiency at the roundabout by approximately 25.04%. Our findings hold significant practical value, particularly with the support of onboard sensors, which can effectively detect non-compliance and provide real-time warnings to guide drivers in adhering to the prescribed traffic management strategies. |
| format | Article |
| id | doaj-art-1bf7106bbc814a14b0507733d3c5731d |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-1bf7106bbc814a14b0507733d3c5731d2025-08-20T01:55:41ZengMDPI AGSensors1424-82202024-11-012423767210.3390/s24237672A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing StrategyXiao Liang0Chuan-Zhi Thomas Xie1Hui-Fang Song2Yong-Jie Guo3Jian-Xin Peng4School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430205, ChinaYangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, ChinaSchool of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430205, ChinaYangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, ChinaIntelligent transportation systems (ITSs) present new opportunities for enhanced traffic management by leveraging advanced driving behavior sensors and real-time information exchange via vehicle-based and cloud–vehicle communication technologies. Specifically, onboard sensors can effectively detect whether human-driven vehicles are adhering to traffic management directives. However, the formulation and validation of effective strategies for vehicle implementation rely on accurate driving behavior models and reliable model-based testing; in this paper, we focus on large roundabouts as the research scenario. To address this, we proposed the Three-Stage Cellular Automata (TSCA) model based on empirical observations, dividing the vehicle journey over roundabouts into three stages: entrance, following, and exit. Furthermore, four optimization strategies were developed based on empirical observations and simulation results, using the traffic efficiency, delay time, and dangerous interaction frequency as key evaluation indicators. Numerical tests reveal that dangerous interactions and delays primarily occurred when the roundabout Road Occupancy Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math></inline-formula>) ranged from 0.12 to 0.24, during which times the vehicle speed also decreased rapidly. Among the strategies, the Path Selection Based on Road Occupancy Rate Recognition Strategy (Simulation 4) demonstrated the best overall performance, increasing the traffic efficiency by 15.65% while reducing the delay time, dangerous interactions, and frequency by 6.50%, 28.32%, and 38.03%, respectively. Additionally, the Entrance Facility Optimization Strategy (Simulation 1) reduced the delay time by 6.90%. While space-based optimization strategies had a more moderate overall impact, they significantly improved the local traffic efficiency at the roundabout by approximately 25.04%. Our findings hold significant practical value, particularly with the support of onboard sensors, which can effectively detect non-compliance and provide real-time warnings to guide drivers in adhering to the prescribed traffic management strategies.https://www.mdpi.com/1424-8220/24/23/7672intelligent transportation systems (ITSs)onboard vehicle sensorsThree-Stage Cellular Automata (TSCA) modelroundabout traffic optimization |
| spellingShingle | Xiao Liang Chuan-Zhi Thomas Xie Hui-Fang Song Yong-Jie Guo Jian-Xin Peng A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy Sensors intelligent transportation systems (ITSs) onboard vehicle sensors Three-Stage Cellular Automata (TSCA) model roundabout traffic optimization |
| title | A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy |
| title_full | A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy |
| title_fullStr | A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy |
| title_full_unstemmed | A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy |
| title_short | A Three-Stage Cellular Automata Model of Complex Large Roundabout Traffic Flow, with a Flow-Efficiency- and Safety-Enhancing Strategy |
| title_sort | three stage cellular automata model of complex large roundabout traffic flow with a flow efficiency and safety enhancing strategy |
| topic | intelligent transportation systems (ITSs) onboard vehicle sensors Three-Stage Cellular Automata (TSCA) model roundabout traffic optimization |
| url | https://www.mdpi.com/1424-8220/24/23/7672 |
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