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
Engineering, Electrical & Electronic
Apostolos Kousaridas, Ramya P. Manjunath, Jose Perdomo, Chan Zhou, Ernst Zielinski, Steffen Schmitz, Andreas Pfadler
Summary: A 5G communication system is capable of meeting the QoS requirements for V2X use cases, with recent developments enabling the prediction and notification of QoS changes to help vehicles avoid or mitigate sudden disruptions. The feasibility of a QoS prediction scheme is analyzed using tele-operated driving as an example, with recommendations provided for the development of such a solution and identification of open research topics.
IEEE COMMUNICATIONS MAGAZINE
(2021)
Article
Automation & Control Systems
Robert Austin Dollar, Ardalan Vahidi
Summary: The study demonstrates that vehicle-to-vehicle connectivity combined with anticipative control can improve lane change decisions by automated vehicles. The new control method enhances energy and time efficiency in road networks, resulting in reduced energy consumption and travel time.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Review
Green & Sustainable Science & Technology
Jie Li, Abbas Fotouhi, Yonggang Liu, Yuanjian Zhang, Zheng Chen
Summary: With the development of communication and automation technologies, the energy-saving potential of connected and automated vehicles (CAVs) has been highlighted. This study systematically summarizes the state-of-the-art in eco-driving, which is the automatic planning of ecological driving behaviors to reduce energy consumption. The study discusses the basic principles of eco-driving, classifies related studies, and emphasizes the potential for cooperative eco-driving in terms of energy saving. The study provides potential development trends for eco-driving techniques.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Engineering, Electrical & Electronic
Chunjie Zhai, Chuqiao Chen, Xiangyu Yang, Guangyu Liu, Chenggang Yan, Fei Luo, Jianmin Xu
Summary: This paper proposes an eco-driving algorithm that takes into account the queue effects at unsaturated intersections for connected and automated vehicles (CAVs), aiming to reduce fuel consumption and travel time. By predicting queue length and implementing real-time control, the algorithm is able to simultaneously decrease fuel consumption and travel time, as demonstrated through extensive simulations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Pei-Jarn Chen, Szu-Yueh Yang, Yen-Pei Chen, Muslikhin Muslikhin, Ming-Shyan Wang
Summary: This paper proposes a slip estimation and compensation control method for an omnidirectional Mecanum-wheeled automated guided vehicle, which adjusts the speed of the four omnidirectional wheels to accurately track the predetermined motion trajectory. Experimental results demonstrate a significant reduction in tracking errors and improved tracking accuracy using this method.
Article
Transportation Science & Technology
Tianlu Pan, Renzhong Guo, William H. K. Lam, Renxin Zhong, Weixi Wang, Biao He
Summary: This paper proposes an integrated freeway traffic flow control framework aiming to minimize total travel cost, improve greenness and safety by combining various control strategies for connected automated vehicles (CAVs) and regular human-piloted vehicles (RHVs). The feasibility and effectiveness of the proposed framework are demonstrated through numerical examples under different traffic conditions. The integrated control strategy can reduce total travel cost by minimizing lane changing maneuvers and vehicles queueing at bottlenecks while ensuring smoother traffic flow and mitigating shockwaves. Speed harmonization and lane changing control are more effective integrated control strategies with high CAVs penetration rates.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Electrical & Electronic
Rafael Molina-Masegosa, Sergei S. Avedisov, Miguel Sepulcre, Yashar Z. Farid, Javier Gozalvez, Onur Altintas
Summary: This study proposes V2X message generation rules for maneuver coordination between connected automated vehicles, which efficiently support maneuver coordination and offer a balance between frequent updates of driving intentions and control of V2X communications load. The proposed rules detect potential safety risks and significant modifications of planned trajectories to generate coordination messages.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
Article
Chemistry, Multidisciplinary
Wenbo Wang, Songhua Fan, Zijian Wang, Xinpeng Yao, Kenan Mu
Summary: In this study, a wireless charging scheme using variable-scale elements is proposed to optimize the performance of electric freight vehicles in urban transport systems. The results show that the charging benefits and passing efficiency can be significantly improved by implementing the balanced priority strategy.
APPLIED SCIENCES-BASEL
(2023)
Article
Psychology, Applied
Davide Maggi, Richard Romano, Oliver Carsten
Summary: Lane Keeping Assist can help drivers keep the vehicle in the center of the lane when control is handed back to them. However, assistance at an operational level does not improve their ability to handle more complex tasks. Task-specific assistance, such as Blind-spot assist, is more effective for tackling tactical decisions.
TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR
(2022)
Article
Engineering, Civil
Tao Zhang, Yuan Zou, Xudong Zhang, Ningyuan Guo, Wenwei Wang
Summary: This article introduces the application of cyber-physical systems in intelligent transportation and presents a distributed CPS application for the safety-following driving control of connected and automated vehicles. By building vehicle behavior prediction models and dynamic driving system models using historical data, as well as proposing a new range strategy, the safety of vehicles can be improved.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Civil
Zhengwei Bai, Peng Hao, Wei Shangguan, Baigen Cai, Matthew J. Barth
Summary: This study proposes a hybrid reinforcement learning framework to support connected eco-driving in mixed traffic. Through experiments, it shows that the proposed method can reduce energy consumption and save travel time compared to a state-of-the-art model-based approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Fengchen Wang, Yan Chen
Summary: A novel hierarchical flocking control framework is proposed for multiple connected and automated vehicles to address traffic fatality and congestion issues, integrating path planning, speed profile generation, and nonlinear vehicle dynamics control. The framework can accommodate complicated vehicle dynamics with a self-organizing feature, showcasing successful completion of 2D flocking coordination in highway simulations for five CAVs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Mechanical
Yang Ding, Weichao Zhuang, Liangmo Wang, Jingxing Liu, Levent Guvenc, Zhen Li
Summary: This paper proposes an integrated lane-change trajectory planning method for advanced driver assistance system of connected and automated vehicles. The method combines a time-based lane-change model and constraints induced by surrounding vehicles to achieve safer and more comfortable lane changes.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Automation & Control Systems
Xiaohua Ge, Qing-Long Han, Qing Wu, Xian-Ming Zhang
Summary: This paper proposes a distributed platooning control method for CAVs that can accommodate various uncertainties and ensure stability, safety, and scalability.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(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)
