Review
Transportation Science & Technology
Mansour Johari, Mehdi Keyvan-Ekbatani, Ludovic Leclercq, Dong Ngoduy, Hani S. Mahmassani
Summary: Network macroscopic fundamental diagrams and related traffic dynamics models have theoretical support and empirical validation, but their readiness for practical implementation is still uncertain. This paper reviews the history of macroscopic modeling, assesses remaining gaps, and discusses opportunities for further development in theory and applications.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Multidisciplinary
Jinghui Wang, Wei Lv, Yajuan Jiang, Guangchen Huang
Summary: This study proposes an improved cellular automata model for modeling mixed pedestrian-vehicle traffic scenes. The analysis of the model shows high simulation accuracy. By applying the model to simulate real-life situations, the research results reveal the impact of pedestrian intrusion behavior on traffic flow and the changes in vehicles' speed and flow rate caused by pedestrian intrusion behavior. Additionally, the study finds that lower speeds and wider sidewalks can effectively reduce the frequency of conflicts between pedestrians and vehicles.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Physics, Multidisciplinary
W. Marques Jr, A. R. Mendez, R. M. Velasco
Summary: Recent applications of a new methodology have shown that critical parameters of flow-density and speed-spacing diagrams on freeways are dependent on vehicle length. In response to this, the study presents a generalization of the Prigogine-Herman traffic equation for aggressive drivers, taking into account the effective length of vehicles. The approach is similar to that used for dense gases by Enskog and provides fundamental diagrams that align well with empirical traffic data.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Transportation Science & Technology
Ziyuan Gu, Meead Saberi
Summary: This paper addresses two toll pricing problems of different complexities in Melbourne using simulation-based optimization methods. It compares four computationally efficient SBO methods, showing that while the methods perform similarly in simple problems, regressing kriging emerges as the best-performing method for complex problems due to its ability to filter out numerical noise.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Automation & Control Systems
A. M. Ishtiaque Mahbub, Viet-Anh Le, Andreas A. Malikopoulos
Summary: This paper proposes a safety-prioritized receding horizon control framework for forming platoons of human-driven vehicles (HDVs) led by a connected and automated vehicle (CAV) in a mixed traffic environment. The framework indirectly controls the following HDVs by directly controlling the leading CAV, considering safety constraints. It utilizes a data-driven prediction model based on the recursive least squares algorithm and the constant time headway relative velocity car-following model to predict future trajectories of HDVs. Numerical simulations are conducted to demonstrate the effectiveness of the proposed framework, along with scalability, robustness, and performance analyses.
Article
Computer Science, Interdisciplinary Applications
Xiaoyang Li, Peng Zhang, Mingmin Guo, Zhiyang Lin, Wenchen Yang
Summary: This paper investigates a road tolling problem where a road user can choose to travel from point A to B either by paying for road 1 or for free using road 2. The choice of route also adheres to the user-equilibrium principle. However, the travel time is formulated as an increasing function of density based on the velocity-density relationship, which represents a significant improvement in the classical traffic assignment problem. Consequently, this paper analyzes in detail the impact of toll rates on the road users, administration department, and the road runner, assuming rigid user demand and maximizing total traffic flow and the runner's benefits from toll fees collection.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2023)
Article
Economics
Benjamin Coifman, Balaji Ponnu, Paul El Asmar
Summary: This paper conducts an empirical study on traffic dynamics on a freeway and finds that the dynamics determining the shape of the fundamental diagram may violate stationarity assumptions of classical traffic flow theories. The research establishes the fundamental diagram based on local conditions and analyzes the composition of vehicles using the single vehicle passage method. Correlation analysis reveals that traffic states between successive stations are inconsistent with classical theories. The findings have implications for other traffic flow models relying on the fundamental diagram.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Physics, Multidisciplinary
Linjie Zhou, Tiancheng Ruan, Ke Ma, Changyin Dong, Hao Wang
Summary: This paper explores the impact of CAV platoon management and control mode degradation on traffic flow, fuel consumption, and pollutant emissions. CAV platoons can significantly increase traffic capacity and reduce fuel consumption and emissions. Optimal platoon size for CAV management is suggested to be 5 vehicles.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Automation & Control Systems
Jack Haddad, Boris Mirkin
Summary: The pragmatic design method is developed for a class of uncertain systems considering different input channel delays and control saturation effects. By using auxiliary linear Smith-like dynamic units with adjustable gains for implicit time-delay prediction, the proposed control design overcomes the difficulty of directly predicting plant state and coping with various input delays. The design is unified to different time delay categories and various adaptive control feedback strategies are designed within this framework. Simulation results for perimeter control of two interacting urban traffic regions are presented.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Transportation Science & Technology
Ye Li, Mohsen Ramezani
Summary: This paper introduces a predictive congestion pricing method in cities that adjusts tolls based on regional differences, aiming to minimize total time spent in the network and achieve revenue neutrality. The proposed method utilizes model predictive control and a neural network to accurately estimate inter-region transfer flows. Numerical experiments show that the proposed congestion pricing method effectively achieves the two objectives simultaneously compared to other controllers.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Ergonomics
Xiaoxue Yang, Yajie Zou, Lei Chen
Summary: This study provides novel insights into the deployment of Connected and Autonomous Vehicles (CAVs) through the analysis of platoon strategy. The research finds that with increasing market penetration rate (MPR) of CAVs, road capacity increases and traffic oscillation reduces. However, the collision risk and severity of traffic conflicts also increase.
ACCIDENT ANALYSIS AND PREVENTION
(2022)
Article
Transportation Science & Technology
Yiru Jiao, Simeon C. Calvert, Sander van Cranenburgh, Hans van Lint
Summary: This study presents a new method to infer the average two-dimensional spacing between vehicles in urban traffic using trajectory data. The method focuses on the relative movement between vehicles and aggregates the presence of vehicles in similar scenarios. By applying this method, a new empirical relation between the average spacing and relative speeds is obtained, known as the interaction Fundamental Diagram (iFD). These iFD relations contribute to understanding vehicle interaction in urban traffic and can provide new insights for designing safer and more efficient urban intersections.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Xiaowei Shi, Xiaopeng Li
Summary: This paper investigates the impact of commercial AVs on traffic flow and proposes a methodology that combines empirical experiments and theoretical models to construct a fundamental diagram for AV traffic. The traditional triangular fundamental diagram structure remains applicable to describe the traffic flow characteristics of AV traffic, with different headway settings affecting road capacity and traffic flow stability.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Transportation Science & Technology
Ziyuan Gu, Zelin Wang, Zhiyuan Liu, Meead Saberi
Summary: This paper investigates the impact of connected and/or automated vehicles on network traffic stability due to turning and merging maneuvers. The results suggest that the presence of CAVs improves network flow stability when the turning probability is low, but AVs without cooperation worsen the stability when the turning probability is high. Additionally, the effectiveness of delaying NFD bifurcation is higher when the penetration rate of CAVs is moderate.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Automation & Control Systems
Walter Lucia, Giuseppe Franze, Domenico Famularo
Summary: This paper addresses intelligent traffic management within a smart city environment using an ad-hoc model predictive control strategy based on an event-driven formulation. A low-demanding receding horizon controller is derived through set-theoretic arguments for safety verification, and simulations on the train-gate benchmark system demonstrate the effectiveness and benefits of the proposed methodology.
DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS
(2021)
Article
Transportation Science & Technology
Ye Li, Mehmet Yildirimoglu, Mohsen Ramezani
Summary: This paper investigates the accumulation-based and trip-based Macroscopic Fundamental Diagram (MFD) models, and proposes a robust perimeter control method based on Sliding Mode Control that can effectively alleviate congestion and improve network efficiency during traffic rush hours.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Economics
Ye Li, Reza Mohajerpoor, Mohsen Ramezani
Summary: This study introduces a new perimeter control method that adjusts region boundaries in real-time to tackle the propagation of local congestion, significantly reducing total travel time for vehicles in the network.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Operations Research & Management Science
Sakitha Kumarage, Mehmet Yildirimoglu, Mohsen Ramezani, Zuduo Zheng
Summary: This paper introduces a cooperative demand redistribution strategy to optimize urban traffic network performance by minimizing total time spent and minimizing disruption to traveler departure times. The model combines two traffic models based on macroscopic fundamental diagram, and utilizes nonlinear optimization to address observed and unobserved demand, reaching a constrained system optimum while ensuring applicability at full and partial user compliance conditions.
TRANSPORTATION SCIENCE
(2021)
Article
Transportation Science & Technology
Mehmet Yildirimoglu, Mohsen Ramezani, Mahyar Amirgholy
Summary: This paper proposes an optimal staggered work schedules problem to minimize network total travel time and prevent delays in commuter trips during morning peaks in a bicentric network. By using a multi-objective optimization program and macroscopic fundamental diagrams, the method's accuracy and effectiveness are analyzed through solving the optimization problem for a test network. Results demonstrate that implementing this strategy can significantly reduce traffic congestion in urban networks.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Transportation Science & Technology
Mohammad Noaeen, Reza Mohajerpoor, Behrouz H. Far, Mohsen Ramezani
Summary: This paper introduces a decentralized network-level traffic signal control method to handle queue spillbacks. The method strives to maximize the overall throughput of the network by estimating queue lengths with shockwave models and utilizing real-time data for control decisions.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Transportation Science & Technology
Linji Chen, Amir Hosein Valadkhani, Mohsen Ramezani
Summary: This paper proposes a novel decentralised cooperative cruising method for offline operation of autonomous taxi fleets, which uses historical trip data to estimate road centralities for route planning in order to maximize service to passengers.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Transportation
Mohsen Ramezani, Yue Yang, Jacob Elmasry, Porsiem Tang
Summary: This paper characterizes the attributes of the supply of e-hailing markets based on the labor characteristics of the drivers. By clustering analysis, the drivers are categorized into three groups, and the consistency of these supply characteristics over different days is verified. The results demonstrate the effectiveness of the clustering method for supply prediction.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2023)
Article
Transportation Science & Technology
Guipeng Jiao, Mohsen Ramezani
Summary: Ridesourcing services from transportation network companies (TNCs) have been found to worsen traffic conditions by increasing the number of unoccupied vehicles. As an alternative, ridesharing combines similar itineraries to counteract the negative effects of ridesourcing. This study proposes a dynamic discount pricing strategy to incentivize ridesharing, showing substantial economic benefits for the platform and drivers in both short and long terms.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Reza Mohajerpoor, Chen Cai, Mohsen Rainezani
Summary: This paper proposes an analytical signal control algorithm for optimal traffic signal control at oversaturated intersections. It incorporates spillback avoidance and achieves significant reduction in total vehicle delay compared to other signal control methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Transportation Science & Technology
Ye Li, Mohsen Ramezani
Summary: This paper introduces a predictive congestion pricing method in cities that adjusts tolls based on regional differences, aiming to minimize total time spent in the network and achieve revenue neutrality. The proposed method utilizes model predictive control and a neural network to accurately estimate inter-region transfer flows. Numerical experiments show that the proposed congestion pricing method effectively achieves the two objectives simultaneously compared to other controllers.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Transportation
Ang Ji, Mohsen Ramezani, David Levinson
Summary: This study presents a model for lane-changing events, consisting of two interconnected phases: 'stay' and 'execution'. The model incorporates stochastic duration of the 'stay' phase based on external traffic conditions, and models the 'execution' phase using longitudinal speed profiles. Bayesian survival analysis is used to predict the probability of the stay duration before a new execution phase, addressing the censoring issue. Using real-world vehicle trajectory data, the study identifies factors influencing driver behavior in lane-keeping and lane-changing execution, such as surrounding conditions, lane-changing purpose, directions, and departure lanes. The findings highlight the impact of urgency and patience on lane-changing decisions, as well as the influence of distances and relative speeds with surrounding vehicles on acceleration behavior during the execution phase.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation Science & Technology
Ang Ji, Mohsen Ramezani, David Levinson
Summary: A lane-changing pricing scheme is proposed to penalize risky and aggressive lane changes on highways, reducing congestion and improving driving safety. The scheme models driver behavior using game theory and identifies optimal lane-changing strategies. Through calibration and validation with real-world vehicular trajectory data, the model is found to be effective. Two types of lane-changing tolls are introduced to align individual preferences with social benefits, achieving a "win-win" situation by reducing aggressive lane changes and compensating delayed drivers.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Mohsen Ramezani, Amir Hosein Valadkhani
Summary: The ubiquity of smart devices enables emerging ride-sourcing companies to challenge traditional taxi services. This paper proposes a macroscopic model to investigate the efficiency of vehicle-passenger matching and idle vehicle repositioning in ride-sourcing systems. A spatio-temporal matching method is introduced to minimize passengers' waiting time while considering network congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Amir Hosein Valadkhani, Mohsen Ramezani
Summary: The emergence of ride-sourcing systems has completely transformed the market for on-demand mobility services. The service quality and impact of these systems rely on effectively matching and redistributing idle vehicles. This paper proposes a control method that repositions idle vehicles to meet the demand of passengers by transferring them to locations with a higher possibility of faster pickups. The designed controller improves the performance of the ride-sourcing system by reducing waiting times, increasing the number of served trip requests, and optimizing fleet size.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Civil
Yue Yang, Mohsen Ramezani
Summary: This paper proposes a real-time repositioning method that takes into account both the responsiveness to immediate demand and the long-term operational efficiency. Experimental results show that the proposed method outperforms other methods in terms of platform efficiency, passenger experience, and driver gains.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
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)