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Browse AllTo address the limitations of the traditional A* algorithm in lane-level navigation, we propose an autonomous vehicle path planning algorithm based on high-precision maps and an improved A* algorithm to ensure effective application in complex traffic environments. We construct a hierarchical high-precision map based on the Lanelet2 framework to achieve structured modeling of complex road environments. To address the adaptability issues of the A* algorithm in lane-level navigation, we propose optimization schemes, including heuristic function improvements, path segment division, and target point validity verification, to ensure that vehicles can autonomously change lanes on multi-lane roads. By combining dynamic programming (DP) and quadratic programming (QP), we ensure the safety and smoothness of the path. Simulation results demonstrate that the optimized algorithm enables smooth stopping and starting at traffic lights in structured road environments and autonomous lane changes on
According to the working characteristics of the tire changer, the movement characteristics of its rim clamping mechanism are analyzed, and the complex movement structure is abstracted and simplified into four identical six-bar mechanism subunits. One of the subunits is taken as the research object, and the mathematical model of kinematic analysis is established. Using MATLAB software to simulate and analyze the motion law of each component, the mechanical characteristics of the component are analyzed. The optimization of the design parameters of the “six-bar mechanism subunit” is realized, the rim clamping mechanism becomes more stable, and the clamping force follows the diameter of the rim more closely.
In order to reduce traffic accidents caused by cars straying from lanes, a lane line recognition and deviation warning system based on machine vision is designed. It mainly includes image preprocessing, lane line detection, and the design of a deviation warning model. “In this study, an ROS-based intelligent vehicle-mounted camera is adopted for road image collection. To reduce the computational load of data processing while guaranteeing the algorithm’s accuracy and reliability, grayscale conversion and region of interest (ROI) extraction are implemented to finish the image preprocessing stage. Additionally, a fusion strategy of global and local thresholds is introduced to enhance both the operational speed and detection accuracy of the algorithm” use the Canny operator for the edge feature extraction; and complete the fitted lane lines with the improved Hough transform. Finally, based on the Kalman filter and camera viewpoint conversion coefficient algorithm, the lane line offset is
To meet the requirements for efficient evacuation during tunnel navigation, the pontoon of the tunnel bank wall evacuation channel in a large-scale navigation building is taken as the research object. The water body and water wave are simulated using the coupled Euler-Lagrangian method and the push-plate wave method, respectively. The water boundary is processed using the viscoelastic artificial boundary method, and a simulation analysis model of the pontoon under the combined action of water waves and load is established. The results show that the average relative vertical displacement of the pontoon is basically the same under the condition of water wave and no water waves, but the fluctuation range of the pontoon is larger under the condition of water waves. When there are water waves and different loads, the maximum Mises stress distribution of the pontoon is essentially the same, and both are less than 80 MPa, meeting the strength requirements and demonstrating the rationality of
Aiming at the problem of insufficient modeling of spatio-temporal heterogeneity in road traffic accident prediction, a dual task machine learning framework integrating geographical environment, location attributes and time periodicity is proposed. The dataset used in this study was derived from traffic accident records of Nanchang during 2019–2023. Firstly, geographical identifiers are generated by rounding and aggregating latitude and longitude coordinates. At the same time, the location type is processed by a one-hot encoding, so as to carry out spatial clustering analysis of accident hotspots. Compared with the North-South pattern, the contribution of geographical features shows a strong East-West trend. The kernel density heatmap identified Zone A and zone B as dual core high-risk areas. Secondly, the sinusoidal/cosine function is used to encode the time feature circularly, which effectively captures the daily change of the accident. The quantitative analysis of random forest
With the rapid development of China’s logistics and transportation industry, how to reasonably and efficiently use drones to carry out logistics and distribution business under the background of UAM has become a focus of attention for social enterprises. It is urgent to propose a feasible logistics drone take-off and landing sites layout planning method based on reality. The article first explains the principles and connotations of the layout of logistics unmanned aerial vehicle take-off and landing sites, dividing logistics distribution scenarios into three sub scenarios: urban end of pipe distribution, medical material distribution, and short distance logistics transportation. Then, based on strong constraint conditions, preliminary site selection is carried out for each sub scenario. The HRW-Kmedoids algorithm is used to optimize the site selection points for each sub scenario, and the final site selection and alternative points are obtained. The Huangpu District of Guangzhou is
The gearbox is a key component of the mechanical transmission system, and its fault diagnosis is essential to the reliability of the equipment. However, obtaining fault samples under actual working conditions for gearbox fault diagnosis is challenging. In this paper, the rigid-flexible coupling dynamic simulation model of the gearbox is established, and the co-simulation of gear normal, crack, and breakage is carried out in the ADAMS and MATLAB environments. The comparison between the simulated and measured signals shows that the simulation method can accurately reflect the key characteristics, such as rotation frequency and meshing frequency, and verify its reliability and accuracy. The research results can provide effective data support for gearbox fault diagnosis and improve the operational safety of mechanical systems.