Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads
This thesis focused on the issue of lane change behavior and prediction, which is directly related to the safety of intelligent driving and intelligent vehicles in smart cities. By analyzing actual data, the study investigated the characteristics of lane-changing behavior and developed a model to fo...
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Nanyang Technological University
2023
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sg-ntu-dr.10356-1671542023-07-04T16:44:44Z Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads Zhang, Jialu Su Rong School of Electrical and Electronic Engineering RSu@ntu.edu.sg Engineering::Electrical and electronic engineering This thesis focused on the issue of lane change behavior and prediction, which is directly related to the safety of intelligent driving and intelligent vehicles in smart cities. By analyzing actual data, the study investigated the characteristics of lane-changing behavior and developed a model to forecast lane changes. The research compared a number of lane change prediction methods based on different algorithms and confirmed the effectiveness of SVM and MLP methods. It also highlighted the importance of understanding the different types of lane-changing behavior and the factors that influence it, including the lane’s position in relation to highway entrances and exits. Master of Science (Computer Control and Automation) 2023-05-15T06:52:39Z 2023-05-15T06:52:39Z 2023 Thesis-Master by Coursework Zhang, J. (2023). Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167154 https://hdl.handle.net/10356/167154 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Zhang, Jialu Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
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This thesis focused on the issue of lane change behavior and prediction, which is directly related to the safety of intelligent driving and intelligent vehicles in smart cities. By analyzing actual data, the study investigated the characteristics of lane-changing behavior and developed a model to forecast lane changes. The research compared a number of lane change prediction methods based on different algorithms and confirmed the effectiveness of SVM and MLP methods. It also highlighted the importance of understanding the different types of lane-changing behavior and the factors that influence it, including the lane’s position in relation to highway entrances and exits. |
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Su Rong |
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Su Rong Zhang, Jialu |
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Thesis-Master by Coursework |
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Zhang, Jialu |
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Zhang, Jialu |
title |
Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
title_short |
Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
title_full |
Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
title_fullStr |
Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
title_full_unstemmed |
Simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
title_sort |
simulation and modeling for mixed traffic flow with autonomous connected vehicles and human drivers on urban roads |
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Nanyang Technological University |
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2023 |
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https://hdl.handle.net/10356/167154 |
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1772828274591793152 |