Jingbo Zhao

To address the ‘mechanical’ return to original lane and similar non-humanized lane-changing issues that may occur in existing intelligent driving systems after completing overtaking maneuvers, this study proposes a humanized lane-changing decision method that incorporates driving style characteristics. First, based on the NGSIM dataset, we employ cluster analysis to systematically dissect human drivers’ lane-changing behavior patterns, laying the theoretical foundation for constructing a human-like decision framework. Second, a game model is established to precisely represent diverse driving styles by adjusting the weights of safety, efficiency, and comfort objectives. A reference line dynamic switching mechanism is then proposed to optimize lane-change paths by integrating vehicle speed and safety distance. Joint simulation results demonstrate superiority over dynamic programming (DP) methods in multiple aspects: under conservative driving mode, dual safety thresholds for following distance and speed significantly enhance safety and reliability. In general driving mode, driving stability and smoothness improved by 2.64% and 75.28%, respectively; in aggressive driving mode, lane-change speed increased by 7.06%. These improvements demonstrate that the human-like lane-changing strategy can autonomously achieve the optimal dynamic balance between safety, comfort, and efficiency tailored to different driving styles, providing an effective pathway for constructing high-performance autonomous driving decision systems.

The primary motivation of this study is to develop a sensor-less, easily controlled, and passively adaptive robotic gripper. A back-drivable pneumatic underactuated robotic gripper (PURG), based on the pneumatic cylinder and underactuated finger mechanism, is presented to accomplish the above goals. A feedforward grasping force control method, based on the learned kinematics of the underactuated finger mechanism, is proposed to achieve sensor-less grasping force control. To enhance the grasping force control accuracy, a state-based actuating force modeling method is presented to compensate the hysteresis error which exists in the transmission mechanism. Actuating force control experiment is performed to validate the effectiveness of the state-based actuating pressure modeling method. Results reveal that compared with the non-state-based modeling method, the proposed state-based actuating force modeling method could reduce the modeling error and control error by about 37.0% and 77.2%, respectively. Results of grasping experiments further reveal that grasping force could be accurately controlled by the state-based feedforward control model in a sensor-less approach. Adaptive grasping experiments are performed to exhibit the effectiveness of the sensor-less grasping force control approach.

The primary motivation of this study is to develop a cost-effective, safe, easily controlled, and passively adaptive robotic gripper. A novel linear series elastic actuated robotic gripper (LSEA-RG) is proposed to accomplish the aforementioned goals. The LSEA-RG has the ability to adaptively grasp objects with different shapes and sizes by grasping force control. First, the mechanical design, including the transmission scheme, the finger mechanism, and the actuating mechanism is presented. Subsequently, the kinematic analysis is performed to explore the transmission characteristic of the actuating displacement and force. Then a model-free control method based on the lookup functions of the kinematic transmission characteristics is presented to achieve the grasping range and force control. Finally, several grasping experiments are carried out based on the LSEA-RG prototype to evaluate the grasping performance. The results demonstrate that the presented grasping control method which based on the lookup functions is valid. The LSEA-RG could estimate the grasping force without the help of a fingertip force sensor and grasp objects with different shapes and hardness adaptively.

Journal provides a multidisciplinary forum for scientists, researchers and engineers involved in research and design of nonlinear processes and phenomena, including the nonlinear modelling of phenomena of the nature.

In this paper, the existence of positive solutions for Caputo fractional differential equations boundary value problem with infnite points contained in the boundary value condition, and based on Green's function and its properties, the existence of multiple positive solutions are obtained by AveryPeterson fxed point theorem.

To evaluate the dynamic properties of a coupled structure based on the dynamic properties of its substructures, this paper investigates the dynamic substructuring issue from the perspective of response prediction. The main idea is that the connecting forces at the interface of substructures can be expressed by the unknown coupled structural responses, and the responses can be solved rather easily. Not only rigidly coupled structures but also resiliently coupled structures are investigated. In order to further comprehend and visualize the nature of coupling problems, the Neumann series expansion for a matrix describing the relation between the coupled and uncoupled substructures is also introduced in this paper. Compared with existing response prediction methods, the proposed method does not have to measure any forces, which makes it easier to apply than the others. Clearly, the frequency response function matrix of coupled structures can be derived directly based on the response prediction method. Compared with existing frequency response function synthesis methods, it is more straightforward and comprehensible. Through demonstration of two examples, it is concluded that the proposed method can deal with structural coupling problems very well.