With the topics related to the intelligent AUV, control and navigation have become one of the key researching fields. This paper presents a concise and reliable path planning method for AUV based on the improved APF method. AUV can make the decision on obstacle avoidance in terms of the state of itself and the motion of obstacles. The artificial potential field (APF) method has been widely applied in static real-time path planning. In this study, we present the improved APF method to solve some inherent shortcomings, such as the local minima and the inaccessibility of the target. A distance correction factor is added to the repulsive potential field function to solve the GNRON problem. The regular hexagon-guided method is proposed to improve the local minima problem. Meanwhile, the relative velocity method about the moving objects detection and avoidance is proposed for the dynamic environment. This method considers not only the spatial location but also the magnitude and direction of the velocity of the moving objects, which can avoid dynamic obstacles in time. So the proposed path planning method is suitable for both static and dynamic environments. The virtual environment has been built, and the emulation has been in progress in MATLAB. Simulation results show that the proposed method has promising feasibility and efficiency in the AUV real-time path planning. We demonstrate the performance of the proposed method in the real environment. Experimental results show that the proposed method is capable of avoiding the obstacles efficiently and finding an optimized path.

The Dempster–Shafer evidence theory has been widely applied in multisensor information fusion. Nevertheless, illogical results may occur when fusing highly conflicting evidence. To solve this problem, a new method of the grouping of evidence is proposed in this paper. This method uses a combination of the belief entropy and the degree of conflict of the evidence as the judgment rule and divides the entire body of evidence into two separate groups. For the grouped evidence, both the credibility weighted factor based on the belief entropy function and the support weighted factor based on the Jousselme distance function are taken into consideration. The two determined weighted factors are integrated to adjust the evidence before applying the DS combination rule. Numerical examples are provided to demonstrate the theoretical feasibility and rationality of the proposed method. The fusion results indicate that the proposed method is more accurate than the compared algorithms in handling the paradoxes. A decision-making case analysis of the biological system is performed to validate the practical applicability of the proposed method. The results confirm that the proposed method has the highest belief degree of the target concentration (50.98%) and has superior accuracy compared to other related methods.

The micro rotor aircraft has the advantages of small noise, good concealment and so on, which make it has wide application potential in both military and civilian applications. Aiming at the problems of public security organs such as counter-terrorism, anti-drugs, and disaster relief, a single-rotor wing micro-reconnaissance aircraft was designed. In this paper, the structure of the aircraft is analyzed and designed. Secondly, the aerodynamic characteristics and adsorption capacity of the aircraft are analyzed. Finally, the work flow of the UAV is introduced. The UAV can achieve multi-directional flight, vertical take-off and landing and hovering, and has good prospects for investigation and surveillance.

This paper mainly describes the research progress of Cooperative Vehicle Infrastructure System (CVIS) communication technology in freeway. The application status of short-range real-time communication technology and intermediate-range interactive communication technology in different scenarios of freeway CVIS are discussed respectively. This paper summarizes the existing problems in the research of CVIS communication technology from two aspects of technology application and network security. The research shows that in the future, machine learning, deep learning and other methods can be used to automatically detect network intrusion and deal with unknown attacks; In the future, the CVIS communication technology will adopt channel coding technology and encryption technology to improve the security of wireless network; With the development of 5G technology, the Internet of Vehicles(IOV) will usher in new opportunities. In the future, the freeway communication network will be a heterogeneous wireless network with multiple access networks, which can meet the application requirements in different road traffic scenarios, effectively promote the construction of freeway informatization and accelerate the construction process of smart freeway.

The development and application of pinning control methods create conditions for traffic area control, and the objective of possessing global control of the road network is achieved by controlling a small number of intersections in the road network. Based on this, an urban road network pinning control strategy is designed in this paper. Firstly, this paper establishes the state equation of the urban road traffic network according to the characteristics of traffic flow, and proposes an associated state equation for road sections and key intersections. Secondly, by adjusting the signal timing scheme of key intersections as the target of pinning control, it can restrain the road network to achieve the state with the minimum difference between the actual flow and the desired flow on each road section. At the same time, considering the dynamic nature of traffic flow and the fact that the flow rate on the road section changes continuously, a feedback control mechanism is established in order to determine the threshold value at which each road section enters the congestion state. In addition, when the flow rate of a road section exceeds its threshold value to reach the congestion state, the signal timing scheme of the key intersection needs to be adjusted again to ensure that the flow rate on the road section is always lower than the threshold value at which it enters the congestion state. The results show that the average delay time and average stopping time of the road network are reduced by 35.03s and 18.37s, respectively, compared with the original control scheme, proving that the control strategy can effectively reduce congestion and improve the operational efficiency of the road network.