For the constant distance spacing policy,the existing researches of the string stability focus on the single-predecessor information framework（SPIF） and predecessor-successor information framework（PSIF）.The resear...For the constant distance spacing policy,the existing researches of the string stability focus on the single-predecessor information framework（SPIF） and predecessor-successor information framework（PSIF）.The research results demonstrated that the string stability could not be guaranteed with the SPIF,and then the PSIF was proposed to resolve this string instability.But the issue,whether the string stability can be guaranteed when applying the PSIF,is still controversial.Meanwhile,most of the previous researches on the string stability were conducted without consideration of the parasitic time delays and lags.In this paper,the practical longitudinal vehicle dynamics model is built with consideration of the parasitic time delays and lags existing in the actuators,sensors or the communication systems.Secondly,the detailed theoretical analysis of string stability in frequency domain is conducted to demonstrate that the classical linear control laws can not ensure the string stability when applying both the symmetrical PSIF（SPSIF） and asymmetrical PSIF（APSIF）.Thirdly,a control law,which adds the position and velocity information of the leading vehicle,is proposed to guarantee string stability for small/medium platoon,and the other control law,which adds the acceleration information of the controlled vehicle,is proposed to guarantee string stability for large platoon as well as small/medium platoon.Finally,the comparative simulation is conducted to confirm the conducted analysis and the proposed control laws.The conducted research completes the means to analyze the string stability in frequency domain,provides the parameters＇ reference for the design and implementation of the practical automatic following controllers,and improves the reliability and stability of the platoon of automatic vehicles.展开更多
The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The ...The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.展开更多
The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo transportation.This study addresses the limitat...The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo transportation.This study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control(ESS-MPC)method.This approach includes a multi-constraint strategy for improved stability and safety.The kinematic model for a single front steeringwheel forklift vehicle is constructed with all known state quantities,including the steering angle,resulting in a more accurate model description and trajectory prediction.To ensure vehicle safety,the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS-MPC tracking.The optimisation constraints are also updated with the key kinematic and dynamic parameters of the forklift.The ESSMPC method improved the position and pose accuracy and stability by 57.93%,37.83%,and 57.51%,respectively,as demonstrated through experimental validation using simulation and real-world environments.This study provides significant support for the development of autonomous navigation systems for industrial forklifts.展开更多
基金supported by Doctoral Foundation of Ministry of Education of China (Grant No.20070006011)
文摘For the constant distance spacing policy,the existing researches of the string stability focus on the single-predecessor information framework（SPIF） and predecessor-successor information framework（PSIF）.The research results demonstrated that the string stability could not be guaranteed with the SPIF,and then the PSIF was proposed to resolve this string instability.But the issue,whether the string stability can be guaranteed when applying the PSIF,is still controversial.Meanwhile,most of the previous researches on the string stability were conducted without consideration of the parasitic time delays and lags.In this paper,the practical longitudinal vehicle dynamics model is built with consideration of the parasitic time delays and lags existing in the actuators,sensors or the communication systems.Secondly,the detailed theoretical analysis of string stability in frequency domain is conducted to demonstrate that the classical linear control laws can not ensure the string stability when applying both the symmetrical PSIF（SPSIF） and asymmetrical PSIF（APSIF）.Thirdly,a control law,which adds the position and velocity information of the leading vehicle,is proposed to guarantee string stability for small/medium platoon,and the other control law,which adds the acceleration information of the controlled vehicle,is proposed to guarantee string stability for large platoon as well as small/medium platoon.Finally,the comparative simulation is conducted to confirm the conducted analysis and the proposed control laws.The conducted research completes the means to analyze the string stability in frequency domain,provides the parameters＇ reference for the design and implementation of the practical automatic following controllers,and improves the reliability and stability of the platoon of automatic vehicles.
文摘The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.
基金Natural Science Foundation of Shenyang Municipality,Grant/Award Number:22-315-6‐-02111 Project,Grant/Award Number:D23005。
文摘The advancements in intelligent manufacturing have made high-precision trajectory tracking technology crucial for improving the efficiency and safety of in-factory cargo transportation.This study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control(ESS-MPC)method.This approach includes a multi-constraint strategy for improved stability and safety.The kinematic model for a single front steeringwheel forklift vehicle is constructed with all known state quantities,including the steering angle,resulting in a more accurate model description and trajectory prediction.To ensure vehicle safety,the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS-MPC tracking.The optimisation constraints are also updated with the key kinematic and dynamic parameters of the forklift.The ESSMPC method improved the position and pose accuracy and stability by 57.93%,37.83%,and 57.51%,respectively,as demonstrated through experimental validation using simulation and real-world environments.This study provides significant support for the development of autonomous navigation systems for industrial forklifts.
