[HTML][HTML] Trajectory data-based traffic flow studies: A revisit
In this paper, we review trajectory data-based traffic flow studies that have been conducted
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
微观交通仿真模型参数标定研究综述.
刘昕， 刘志远， 聂品， 顾子渊 - Journal of Railway Science & …, 2022 - search.ebscohost.com
交通仿真在解析复杂交通网络供需平衡机理和推演交通时空运行状态等方面具有显著优势,
合理的仿真模型参数标定方法可确保模型的复现能力. 为帮助交通仿真使用者了解与掌握仿真 …
合理的仿真模型参数标定方法可确保模型的复现能力. 为帮助交通仿真使用者了解与掌握仿真 …
Bayesian optimization techniques for high-dimensional simulation-based transportation problems
Bayesian optimization (BO) is an attractive method for tackling transportation optimization
problems due to its ability to balance exploitation and exploration. However, scaling BO to …
problems due to its ability to balance exploitation and exploration. However, scaling BO to …
[HTML][HTML] Calibration of microscopic traffic simulation models using metaheuristic algorithms
This paper presents several metaheuristic algorithms to calibrate a microscopic traffic
simulation model. The genetic algorithm (GA), Tabu Search (TS), and a combination of the …
simulation model. The genetic algorithm (GA), Tabu Search (TS), and a combination of the …
Multi-objective deep reinforcement learning approach for adaptive traffic signal control system with concurrent optimization of safety, efficiency, and decarbonization at …
This study introduces a novel approach to adaptive traffic signal control (ATSC) by
leveraging multi-objective deep reinforcement learning (DRL) techniques. The proposed …
leveraging multi-objective deep reinforcement learning (DRL) techniques. The proposed …
Metamodel-based calibration of large-scale multimodal microscopic traffic simulation
AUZ Patwary, W Huang, HK Lo - Transportation Research Part C …, 2021 - Elsevier
Agent-based microscopic traffic simulation models are gaining popularity over traditional trip-
based traffic models due to their superiority in modeling household member interaction, car …
based traffic models due to their superiority in modeling household member interaction, car …
A mesoscopic integrated urban traffic flow-emission model
A Jamshidnejad, I Papamichail… - … Research Part C …, 2017 - Elsevier
Due to the noticeable environmental and economical problems caused by traffic congestion
and by the emissions produced by traffic, analysis and control of traffic is essential. One of …
and by the emissions produced by traffic, analysis and control of traffic is essential. One of …
Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model
X Hou, R Zhang, M Yang, S Cheng - Physica A: Statistical Mechanics and …, 2024 - Elsevier
Using traffic marking to separate non-motorized lane from the adjacent motorized lane is a
common traffic design method for urban road segments. With the increase in non-motorized …
common traffic design method for urban road segments. With the increase in non-motorized …
Sustainable model-predictive control in urban traffic networks: Efficient solution based on general smoothening methods
A Jamshidnejad, I Papamichail… - … on Control Systems …, 2017 - ieeexplore.ieee.org
Traffic-responsive control approaches, including model-predictive control (MPC), are
efficient methods for making the best use of the available network capacity. Moreover …
efficient methods for making the best use of the available network capacity. Moreover …
A cross-entropy method and probabilistic sensitivity analysis framework for calibrating microscopic traffic models
Car following modeling framework seeks for a more realistic representation of car following
behavior in complex driving situations to improve traffic safety and to better understand …
behavior in complex driving situations to improve traffic safety and to better understand …