Article
Engineering, Mechanical
Masoumeh Parseh, Mikael Nybacka, Fredrik Asplund
Summary: This paper proposes a framework that incorporates the post-impact motion of an impacted vehicle into the decision-making process of severity minimisation motion planning. Through simulations and analysis, the effects of vehicle model complexity and collision parameters sensitivity are revealed, highlighting the importance of considering vehicle dynamics models and collision models in further research.
VEHICLE SYSTEM DYNAMICS
(2023)
Article
Computer Science, Artificial Intelligence
Cong Wang, Zhenpo Wang, Zhiqiang Zhang, Jizheng Liu, Wenbo Li, Yang Wu, Xiaoyu Li, Huilong Yu, Dongpu Cao
Summary: Reducing traffic accidents and improving vehicle safety have always been a matter of great concern. To avoid secondary and serial collision accidents, a planning-integrated active safety control system is developed for post-impact vehicles. This system considers the roll degree of freedom and establishes a vehicle dynamics model. It proposes constraint equivalent methods based on octagon and rhombus envelopes to linearize the road adhesion constraint and obstacle avoidance constraint, respectively. Moreover, it includes an obstacle avoidance decision strategy based on safe braking distance and a control allocator based on particle swarm optimization for efficient control allocation under extreme conditions. The proposed scheme is verified through hardware-in-loop tests under comprehensive driving scenarios.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Engineering, Civil
Chang Zhou, Yazhou Xie, Wenwei Wang, Yuzhou Zheng
Summary: This study uses machine learning (ML) methods to predict post-impact damage states of reinforced concrete (RC) bridge piers under vehicle collision. Six supervised ML models, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, eXtreme Gradient Boosting Trees (XGBoost), and Artificial Neural Network (ANN), are trained and tested using 251 datasets. The results show that SVM, Random Forest, XGBoost, and ANN have superior and comparable classification capabilities. The Shapley additive explanations (SHAP) algorithm is used to interpret and explain the prediction process of the ML models.
ENGINEERING STRUCTURES
(2023)
Article
Engineering, Mechanical
Shuming Shi, Fanyu Meng, Minghui Bai, Nan Lin
Summary: This study applied the Lyapunov exponents method to analyze the stability of nonlinear high-DOF vehicle models, revealing the differences in characteristics between different degrees of freedom models.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Engineering, Civil
Guokuan Yu, Pak Kin Wong, Jing Zhao, Xingtai Mei, Changqing Lin, Zhengchao Xie
Summary: This paper proposes a bi-directional collision avoidance system for multiple vehicles, aiming to minimize collision risk by switching vehicle-following modes and redistributing acceleration. The system adopts a hierarchical structure with an upper layer for strategy formulation and a lower layer for command tracking. By integrating with model predictive control (MPC) and applying a dynamic weighted tuning strategy, the system outperforms conventional collision avoidance systems in avoiding collisions or minimizing impact.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
W. Wang, J. Chen, R. X. Zhou, J. Zhong
Summary: Vehicle collision upon pier columns poses a significant threat to the structural safety and normal operation of highway bridges. This paper proposes a simplified mass-spring model and develops regression formulas to accurately predict the dynamic processes by coupling with a cantilever beam structure.
Article
Computer Science, Information Systems
Yeayoung Park, Juhui Gim, Changsun Ahn
Summary: This study tackles challenges in vehicle collisions, emphasizing the stabilization of vehicles during non-front or non-rear impacts, particularly in cornering and lane change maneuvers. By estimating collision forces and developing a sliding mode controller, the proposed methodology aims to improve collision stability control.
Article
Engineering, Mechanical
Cong Wang, Zhenpo Wang, Lei Zhang, Huilong Yu, Dongpu Cao
Summary: This paper proposes a post-impact motion planning and stability control method for autonomous vehicles to reduce traffic accidents and fatalities.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Menghua Zhang, Xingjian Jing
Summary: This article presents a novel saturated PD-SMC control method for tower crane systems, which achieves accurate positioning and rapid swing suppression with simple structure and strong robustness. Experimental results validate the superior control performance and stability of the designed control method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Mechanics
Mostafa Abouelsoud, Vinod A. Thale, Ahmed N. Shmroukh, Bofeng Bai
Summary: This study empirically and analytically examined the spreading and retraction phases during the impact of a coaxial drop with a sessile drop on a solid substrate. The effects of surface wettability on the impact outcomes were analyzed using various surfaces. It was found that the merged drop takes longer to attain its maximum spreading diameter at a higher contact angle. A model for predicting the maximum spreading diameter was presented, which considered the assumption of viscous energy loss during the merging process. Additionally, the maximum retraction height on the coated glass surface was investigated.
Article
Engineering, Marine
Miao Yang, Zhibin Sheng, Ge Yin, Haiwen Wang
Summary: A recurrent neural network-based fuzzy sliding mode control method is proposed in this paper for achieving stable movement of a remotely operated vehicle under uncertainty and external disturbance. The method estimates and compensates for the uncertainty of the vehicle model adaptively using offline training of a RNN. It employs a fuzzy logic system as the switching term for sliding mode control to reduce chattering phenomenon and automatically eliminate external disturbance.
Article
Computer Science, Interdisciplinary Applications
Tuo Xu, Ping Xu, Hui Zhao, Chengxing Yang, Yong Peng
Summary: This paper proposes a vehicle running attitude prediction model based on Artificial Neural Network-Parallel Connected (ANN-PL), which predicts the longitudinal and vertical displacements of the vehicle body, the vehicle head-up angle, and the overriding risk. The model is validated using a 3D multibody dynamics model and exhibits excellent computational efficiency and prediction accuracy compared to traditional methods. The study explores the relationship between input variables and vehicle running attitude, and the findings provide a research method for solving complex engineering issues.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Article
Computer Science, Artificial Intelligence
Xiaohui Hou, Minggang Gan, Junzhi Zhang, Shiyue Zhao, Yuan Ji
Summary: This paper proposes a novel controller to prevent secondary crashes after an initial rear-end collision. By combining pre-collision control and post-collision control, it reduces the initial crash loss and subsequent control difficulty. Experimental results validate the superiority of this controller in different rear-end collision scenarios.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Computer Science, Information Systems
Minsung Kim, Donggil Lee, Joonwoo Ahn, Minsoo Kim, Jaeheung Park
Summary: The proposed algorithm utilizes various time intervals for path-following and collision avoidance, effectively improving both path-following performance and obstacle avoidance range while maintaining fixed computational complexity.
Article
Automation & Control Systems
Chunyu Song, Xianku Zhang, Guoqing Zhang
Summary: This research presents a 4-DOF ship maneuvering modeling based on full-scale trial data and proposes a new multi-innovation least squares algorithm for identifying nonlinear innovations in ship maneuvering motion. The design scheme shows significant computational advantages, higher accuracy, and faster identification speed.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Civil
Sanghyun Hong, Jianbo Lu, Smruti R. Panigrahi, Jonathan Scott, Dimitar P. Filev
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2019)
Article
Automation & Control Systems
Zhaojian Li, Ilya Kolmanovsky, Ella Atkins, Jianbo Lu, Dimitar P. Filev, John Michelini
IEEE TRANSACTIONS ON CYBERNETICS
(2016)
Article
Automation & Control Systems
Zhaojian Li, Ilya V. Kolmanovsky, Uros V. Kalabic, Ella M. Atkins, Jianbo Lu, Dimitar P. Filev
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2017)
Article
Engineering, Civil
Zhaojian Li, Dimitar P. Filev, Ilya Kolmanovsky, Ella Atkins, Jianbo Lu
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2017)
Article
Automation & Control Systems
Zhaojian Li, Ilya V. Kolmanovsky, Ella M. Atkins, Jianbo Lu, Dimitar P. Filev, Yuchen Bai
IEEE TRANSACTIONS ON CYBERNETICS
(2017)
Article
Computer Science, Artificial Intelligence
Changxi You, Jianbo Lu, Panagiotis Tsiotras
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2017)
Article
Engineering, Civil
Sanghyun Hong, Jianbo Lu, Dimitar P. Filev
Summary: This paper proposes an online estimation approach based on transition probabilities to monitor virtual drivers of autonomous and non-autonomous vehicles for safety control system performance. The method addresses numerical issues and is validated through experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Automation & Control Systems
Lin He, Feilong Li, Chaolu Guo, Bingzhao Gao, Jianbo Lu, Qin Shi
Summary: In this article, a novel steer-by-wire system architecture called iSteer is designed to achieve high performance steering angle tracking for self-driving vehicles. An adaptive proportional-integral controller is developed with parameters tuning by particle swarm optimization. The control law takes into account self-aligning torque and ground resistance torque. The stability and convergence of the steering control system are proven through analysis and experiments.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Electrical & Electronic
Ke Wang, Shengjie Luo, Tao Chen, Jianbo Lu
Summary: This article proposes a salient visual place recognition method that combines image retrieval, semantic information, and saliency cues for accurate estimations. The method uses a novel formulation to combine local semantic features into global descriptors and predicts saliency descriptors to learn the representation of static objects. A late-fusion module is introduced to increase the stability of the descriptor.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Ke Wang, Sai Ma, Fan Ren, Jianbo Lu
Summary: This article proposes to mimic the mechanism of visual saliency or visual attention in the visual SLAM framework by using the saliency prediction model. By re-computing the saliency map to solve the center bias of the generic salient dataset, the salient bundle adjustment (SBA) algorithm is introduced. Experimental results demonstrate that the proposed SBA algorithm outperforms existing algorithms such as DSO and ORB-SLAM3 in both indoor and outdoor environments.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Civil
Changxi You, Jianbo Lu, Dimitar Filev, Panagiotis Tsiotras
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Sanghyun Hong, Jianbo Lu, Dimitar P. Filev
2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
(2017)
Article
Transportation Science & Technology
Jianbo Lu, Sanghyun Hong, Jonathan Sullivan, Guopeng Hu, Edward Dai, Dennis Reed, Ryan Baker
SAE INTERNATIONAL JOURNAL OF ENGINES
(2017)
Proceedings Paper
Computer Science, Cybernetics
Changxi You, Jianbo Lu, Panagiotis Tsiotras
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
(2016)
Article
Automation & Control Systems
Lin He, Feilong Li, Chaolu Guo, Bingzhao Gao, Jianbo Lu, Qin Shi
Summary: This article introduces a novel steer-by-wire system architecture named iSteer, aiming to achieve high performance steering angle tracking for self-driving vehicles. An adaptive proportional-integral controller with parameters tuning by particle swarm optimization is developed to ensure fast and efficient computation with consideration of disturbances. Experimental results validate the effectiveness of the designed architecture and the high performance of the developed control law in steering angle tracking for self-driving vehicles.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
