Article
Transportation Science & Technology
Yu Han, Meng Wang, Linghui Li, Claudio Roncoli, Jinda Gao, Pan Liu
Summary: This paper proposes a physics-informed reinforcement learning-based ramp metering strategy, which combines historic data and synthetic data to train the RL model and updates the optimal policy through an iterative training process. The strategy shows significant improvements in traffic performance and outperforms classical and existing RL-based ramp metering strategies.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Henrick J. Haule, Priyanka Alluri, Thobias Sando
Summary: This study estimates the mobility benefits of ramp metering by leveraging system breakdowns and finds significant reductions in buffer indices during different levels of congestion. These results can assist transportation agencies in evaluating operational performance and comparing the mobility impact of ramp metering with other alternatives.
JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS
(2022)
Article
Ergonomics
Henrick J. Haule, Sultan Ali, Priyanka Alluri, Thobias Sando
Summary: The study evaluated the impact of ramp metering on the safety performance of freeway mainline, showing that ramp metering significantly reduces crash risk on segments downstream of entrance ramps.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Article
Engineering, Civil
Yao Cheng, Yen-Yu Chen, Gang-Len Chang
Summary: This study presents an arterial-friendly local ramp metering control system for time-of-day operations during recurrent congestion, which outperforms traditional real-time ramp control models in various traffic scenarios.
TRANSPORTATION RESEARCH RECORD
(2022)
Review
Transportation Science & Technology
Zhaoqi Zang, Xiangdong Xu, Kai Qu, Ruiya Chen, Anthony Chen
Summary: This paper introduces the importance of modeling travel time reliability (TTR) in transportation networks and provides an integrated framework for summarizing the methodological developments and applications of TTR. By adopting a network perspective, a better understanding of TTR characterization, evaluation and valuation, and traffic assignment can be achieved. The paper also discusses some common challenges in TTR modeling and potential directions for future research.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Computer Science, Artificial Intelligence
Zhi Liu, Wendi Shu, Guojiang Shen, Xiangjie Kong
Summary: This article proposes a coordinated ramp signal optimization method based on mainline traffic states, which successfully reduces the density of mainline bottlenecks and improves the efficiency of mainline traffic through traffic flow-series flux-correlation analysis and novel multifactorial matric design.
PEERJ COMPUTER SCIENCE
(2021)
Article
Transportation Science & Technology
Apostolos Kotsialos
Summary: This paper introduces a coordinated ramp metering strategy design based on a newly developed multi-class second-order macroscopic traffic flow model coupled with a pollutant emissions model. An optimal control problem is formulated to achieve environmentally sustainable, efficient, and equitable ramp metering strategy. The static large-scale optimization problem is solved using the Differential Evolution algorithm, and a small case study is provided to analyze the multiclass flow model and strategy application.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Civil
Mo Zhao, Xiaoxiao Zhang, Justice Appiah, Michael D. Fontaine
Summary: This study developed machine learning models to predict travel time reliability, using random forest algorithms and multiple data sources. The results showed that both models accurately predicted travel time reliability, with the GRF model performing better for predicting the 50th percentile travel time and the QRF model achieving slightly better predictions for the 90th percentile. A case study demonstrated the use of these models for estimating the impact of improvement projects on travel time reliability. Both models captured the trend in reliability change, with the GRF model preferred for estimating the level of travel time reliability.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Automation & Control Systems
Kimia Chavoshi, Antonella Ferrara, Anastasios Kouvelas
Summary: This paper presents a control solution for reducing congestion in highway traffic systems. The goal is to develop a control strategy with low computational cost for real-time implementation. The METANET model is used to describe traffic dynamics, and a spatio-temporal derivative relationship is highlighted, which serves as the basis for a feedback linearization-based control law. A linear MPC is employed to comply with physical constraints. The proposed method is evaluated through comprehensive simulations and is shown to provide satisfactory coordination of ramp metering and variable speed limits in highway systems, compatible with real-time implementation.
CONTROL ENGINEERING PRACTICE
(2023)
Review
Engineering, Civil
Hanna Grzybowska, Kasun Wijayaratna, Sajjad Shafiei, Nima Amini, S. Travis Waller
Summary: This study focuses on the implementation of ramp metering strategies and provides a detailed overview of recent literature. It aims to provide a global perspective and historical context for future reference in academic research and practical applications.
JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS
(2022)
Article
Engineering, Civil
Lan Yang, Jiahao Zhan, Wen-Long Shang, Shan Fang, Guoyuan Wu, Xiangmo Zhao, Muhammet Deveci
Summary: This paper proposes a multi-lane centralized collaborative control strategy for ramp merging, which uses vehicle-to-infrastructure communication to achieve coordinated control. It aims to alleviate traffic congestion, accidents, and emissions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Wei Gu, Shixing Ding, Shuai Lu, Pengfei Zhao, Dehu Zou, Yue Qiu, Ruizhi Yu, Lina Sheng
Summary: The integration of information and communication infrastructures has increased the vulnerability of integrated energy systems to cyber-attacks. This paper introduces a destructive coordinated attack on the heat and electric integrated energy systems and examines its potential consequences. A bi-level attacker-operator model is formulated to identify the worst-case scenario caused by the attack. Simulation results demonstrate that the coordinated attack has significant impacts on the system, including economic losses and overload.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Minwu Chen, Meng Wang, Diya Zhang, Yingtao Chen, Wenjie Lu
Summary: This study establishes a cost model for PFCs based on the life cycle cost theory and proposes an improved coordinated control strategy to enhance the reliability and cost-effectiveness of the system.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Computer Science, Artificial Intelligence
Yi Yang, Siyu Huang, Meilin Wen, Xiao Chen, Qingyuan Zhang, Wei Liu
Summary: This study focuses on the reliability measurement method using travel time as a performance index and proposes the travel time belief reliability under uncertain random environment. The model considers the influence of cognitive and random uncertainty on reliability, establishes belief reliability model and route selection algorithm, and discusses the impact of road objective factors and driving state factors on travel time threshold using uncertainty regression analysis method. The feasibility and practicability of the model and algorithm are verified using actual travel tasks in Beijing as an example.
Article
Economics
Zheng Zhu, Atabak Mardan, Shanjiang Zhu, Hai Yang
Summary: Travel time reliability is crucial in travelers' route choice behaviors. This study proposes various types of perceived knowledge in a generalized Bayesian traffic model to analyze travelers' daily route choices regarding travel time reliability. The results show that different types of perceived knowledge may lead to distinct route choice dynamics, but all ultimately converge to fixed points.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Editorial Material
Transportation Science & Technology
Neila Bhouri, Nadir Farhi
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2014)
Article
Transportation
Mariano A. Risso, Neila Bhouri, Aldo J. Rubiales, Pablo A. Lotito
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2020)
Article
Management
Mouloud Khelf, Salim Boukebbab, Neila Bhouri
Summary: The main objective of this paper is to evaluate the performance of the tram intelligent system management by analyzing its key indicators. The results indicate that the tram is not operated well, leading to increased traffic congestion. Improving management can reduce traffic congestion without the need for additional infrastructure or technologies.
INTERNATIONAL JOURNAL OF SHIPPING AND TRANSPORT LOGISTICS
(2022)
Article
Engineering, Civil
Rihab Amghar, Sara Jaber, S. M. Hassan Mahdavi Moghaddam, Neila Bhouri, Mostafa Ameli
Summary: The structure and functionality of urban transportation systems can be affected by unexpected disruptions. This paper introduces the concept of "resilience as a service" (RaaS) to manage disruptions and maintain the system's resilience by integrating the available resources of different service providers. A numerical example in a real test case shows that implementing a RaaS solution can reduce the average travel delay of all users by 69%.
TRANSPORTATION RESEARCH RECORD
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Miaohang Hu, Neila Bhouri
2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
(2020)
Proceedings Paper
Automation & Control Systems
Jennie Lioris, Neila Bhouri
2020 AUSTRALIAN AND NEW ZEALAND CONTROL CONFERENCE (ANZCC 2020)
(2020)
Proceedings Paper
Transportation Science & Technology
Amine Melakhsou, Neila Bhouri
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON VEHICLE TECHNOLOGY AND INTELLIGENT TRANSPORT SYSTEMS (VEHITS 2019)
(2019)
Article
Transportation Science & Technology
Neila Bhouri, Maurice Aron, Habib Hajsalem
PROMET-TRAFFIC & TRANSPORTATION
(2019)
Article
Thermodynamics
N. Bhouri, A. Houngan, S. Bennasrallah, P. Perre
APPLIED THERMAL ENGINEERING
(2017)
Article
Computer Science, Artificial Intelligence
Flavien Balbo, Neila Bhouri, Suzanne Pinson
Proceedings Paper
Computer Science, Theory & Methods
Matthis Gaciarz, Samir Aknine, Neila Bhouri
2015 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT), VOL 2
(2015)
Article
Computer Science, Information Systems
Neila Bhouri, Fernando J. Mayorano, Pablo A. Lotito, Habib Haj Salem, Jean Patrick Lebacque
CYBERNETICS AND INFORMATION TECHNOLOGIES
(2015)
Proceedings Paper
Automation & Control Systems
Matthis Gaciarz, Samir Aknine, Neila Bhouri
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS (AAMAS'15)
(2015)
Proceedings Paper
Transportation
Neila Bhouri, Maurice Aron
17TH MEETING OF THE EURO WORKING GROUP ON TRANSPORTATION, EWGT2014
(2014)
Proceedings Paper
Transportation
Dihya Atmani, Jean-Patrick Lebacque, Neila Bhouri, Habib Haj-Salem
17TH MEETING OF THE EURO WORKING GROUP ON TRANSPORTATION, EWGT2014
(2014)
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
