Article
Physics, Multidisciplinary
Zhihong Yao, Qiufan Gu, Yangsheng Jiang, Bin Ran
Summary: This paper studies the fundamental diagram and stability of mixed traffic flow in the connected automated vehicle platoon. The proportion of different types of vehicles in the mixed traffic flow is deduced based on platoon intensity and Markov chain. The general model framework of the fundamental diagram is established, and the influence factors under critical scenarios are discussed. The results show that platoon size and intensity have significant effects on traffic capacity and stability.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Run-Kun Liu, Hai-Yang Yu, Yi-Long Ren, Zhi-Yong Cui
Summary: This work proposes a dynamic topology-based car-following model to study the impact of communication failures on platoon stability. Numerical simulations are conducted to analyze the stability in different communication topology scenarios. The results show that communication failures reduce stability, but information from vehicles farther ahead and a larger desired time headway can improve it. The critical ratio of communication failures required to ensure stability for different driving parameters is also studied.
Article
Engineering, Civil
Jianzhong Chen, Huan Liang, Jing Li, Zekai Lv
Summary: This study focuses on the practical actuator constraints and spacing strategies in automated vehicle platoon control systems, proposing a new control approach that incorporates input saturation and VTH spacing strategy in the consensus algorithm. Numerical simulation results demonstrate the effectiveness of the proposed approach and the necessity of introducing these constraint strategies.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Physics, Multidisciplinary
Jianzhong Chen, Jing Li, Zhaoxin Xu, Xiaobao Wu
Summary: A novel cooperative optimal control method is proposed for CAV platooning on freeways in this paper. The method addresses the cooperation of followers, the motion synchronization, and energy consumption through designing a cost function and introducing a more flexible spacing strategy. Numerical simulations demonstrate the effectiveness of the method.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Transportation Science & Technology
Soomin Woo, Alexander Skabardonis
Summary: Connected Automated Vehicles (CAVs) can increase traffic capacity and energy efficiency by forming platoons with short headways on the road. However, platoon organization strategies may lead to more lane changes, potentially disrupting the flow and reducing capacity. A flow-aware platoon organization strategy can form longer CAV platoons without reducing flow, enhancing traffic efficiency.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Physics, Multidisciplinary
Yangsheng Jiang, Sichen Wang, Zhihong Yao, Bin Zhao, Yi Wang
Summary: The study introduces a cellular automata model of mixed traffic flow to analyze the impact of different car-following modes on traffic efficiency, and through numerical simulation, it is found that the penetration rate of CAVs has a significant impact on traffic flow.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Transportation Science & Technology
Yanyan Qin, Qinzhong Luo, Hua Wang
Summary: This paper investigates the stability of a mixed CAV-CV-RV flow, examines the impact of CVs on stability, and proposes a CV management strategy for achieving stable traffic flow. Results indicate that CVs are more effective than CAVs in ensuring stability, and the market proportion of CVs can be managed to achieve a stable mixed flow.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Yiyang Wang, Ruixuan Zhang, Neda Masoud, Henry X. Liu
Summary: In this study, a comprehensive framework is developed to model the impact of cyberattacks on connected and automated vehicular platoons. A general platoon dynamics model with heterogeneous time delays is proposed, and an augmented state extended Kalman filter (ASEKF) is developed to smooth sensor readings. Anomaly detectors, including the x2-detector and the one class support vector machine (OCSVM), are considered for detecting sensor anomalies. Pseudo string stability is introduced to measure the platoon's stability under cyberattacks and uncertainties, and its relationship with detection rate is demonstrated.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Electrical & Electronic
Zhiyun Deng, Jiaxin Fan, Yanjun Shi, Weiming Shen
Summary: This paper proposes a coevolutionary algorithm to optimize longitudinal trajectories of multiple vehicles during the cooperative platoon formation process. The algorithm adopts an adaptive encoding scheme to represent trajectories and decomposes the high-dimensional problem into smaller subproblems. The experimental results indicate the superiority of the proposed approach in optimality and stability for real-life applications.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Zhihong Yao, Yuqin Ma, Tingting Ren, Yangsheng Jiang
Summary: This paper proposes a capacity analysis model for a mixed traffic flow environment that takes into account the heterogeneity and maximum platoon size of connected vehicles. The study explores the car-following characteristics of different vehicle types and develops a probability distribution model for platoon size. The fundamental diagram of the mixed traffic flow is derived based on the probability distribution and car-following models. The capacity model is then proposed, and a numerical experiment is conducted to evaluate the impact of different penetration rates and maximum platoon sizes on road capacity. The results show that penetration rate and maximum platoon size have a significant impact on road capacity.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Chemistry, Analytical
Geonil Lee, Jae-il Jung
Summary: Cooperative driving is crucial in ITS, offering benefits such as improved safety, reduced accidents, optimized traffic flow, and decreased fuel consumption. CACC systems and platoon management systems are key components of vehicle platooning, enabling vehicles to maintain safe distances and perform platoon maneuvers based on V2V communication.
Article
Engineering, Civil
Yudong Lin, Anuj Tiwari, Brian Fabien, Santosh Devasia
Summary: This paper proposes an approach to improve the performance of constant-spacing vehicle platoons by mitigating large delays and communication loss. The approach achieves a significant reduction in settling time to consensus under large communication delays and minimizes steady-state errors under loss of communication.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Shuya Zhu, Deshi Li, Mingliu Liu
Summary: This study aims to improve traffic efficiency by proposing a hindrance-aware platoon formation scheme for mixed traffic. By establishing a vehicle connection model and designing a cross-vehicle matrix, the optimization of vehicle speed, safety, and energy efficiency is achieved.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Transportation
Huixin Gao, Xilong Ren, Zhijian You, Xia Li, Yuewen Xiao, Mengting Guo, Xinwei Ma
Summary: This paper aims to determine the optimal platoon size in the merge area through numerical analysis. The results show that the optimal platoon size is 4 to 6 when the CAV penetration rate is 10% to 30%. When the CAV penetration rate is 40% to 70%, the trend of merge success rate varies with increasing platoon size under different mainline traffic volumes and acceleration lane lengths. Finally, when the CAV penetration rate is 80% to 90%, the merging success rate tends to increase to the highest point and decrease as the platoon size increases, with the optimal platoon size being 3 to 5.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2023)
Article
Transportation Science & Technology
Weijie Yu, Dong Ngoduy, Xuedong Hua, Wei Wang
Summary: This study focuses on the stability of connected and automated vehicles (CAVs) in heterogeneous traffic environments, investigating the coexistence of CAVs and human-driven vehicles (HDVs). By establishing a comprehensive modeling framework and using quantitative stability metrics, the study reveals that multi-anticipation topologies outperform single-anticipation topologies in terms of head-to-tail stability. It also refines the stricter condition of L infinity stability compared to L2 stability.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(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)