Qian Wang

The field of modern autonomous driving and unmanned systems places significant importance on planning and semantic navigation tasks for autonomous vehicles. The successful execution of these tasks relies heavily on mapping and localization technologies. We propose a method to address the difficulty of using trajectory maps of autonomous vehicle cameras in complex environments for planning. The proposed method constructs a topological map that is convenient for subsequent planning and semantic navigation. To enhance the integration of trajectory maps with topological maps, we employ the ORB-SLAM2 algorithm to create the camera's trajectory map, and we extract the keyframe information to obtain frames from the data. These extracted keyframes are then fed sequentially into a junction recognition network that utilizes ResNet18 transfer learning. Then we connect the resulting nodes that are recognized as junctions to generate the camera's topological map. The integration of trajectory and topological maps has been found to be advantageous in improving the planning and navigation abilities of ground robots.

Due to the characteristics of multibody (MB) and finite element (FE) digital human body models (HBMs), the reconstruction of running pedestrians (RPs) remains a major challenge in traffic accidents (TAs) and new innovative methods are needed. This study presents a novel approach for reconstructing moving pedestrian TAs based on a humanoid robot method to improve the accuracy of analyzing dynamic vehicle–pedestrian collision accidents. Firstly, we applied the theory of humanoid robots to the corresponding joints and centroids of the TNO HBM and implemented the pedestrian running process. Secondly, we used rigid–flexible coupling HBMs to build pedestrians, which can not only simulate running but also analyze human injuries. Then, we validated the feasibility of the RP reconstruction method by comparing the simulated dynamics with the pedestrian in the accident. Next, we extracted the velocity and posture of the pedestrian at the moment of collision and further validated the modeling method through a comparison of human injuries and forensic autopsy results. Finally, by comparing two other cases, we can conclude that there are relative errors in both the pedestrian injury results and the rest position. This comparative analysis is helpful for understanding the differences in injury characteristics between the running pedestrian and the other two cases in TAs.

The problem of large calculation models in bus–two-wheeled vehicle traffic accidents (TA) leads to the difficulty of balancing the calculation efficiency and accuracy, as well as difficulties in accident reconstruction. Herein, two typical accidents were reconstructed, based on the rigid–flexible coupled human model (HM) and the Facet vehicle model, and the vehicle damage conditions and the human head biomechanical injury were analyzed. The simulation results showed that the physical process of the human–vehicle collision was basically consistent with the accident video, the windshield fracture was consistent with the actual vehicle report, and the human biomechanical injury characteristics were also consistent with the autopsy report, which verified the feasibility of the simulation model, and provides a basis and reference for forensic identification and for traffic police to deal with accident disputes.

In the human–vehicle–road system of collisions, the human is the most important factor, and digital human models (DHMs) are developed with the aim of preventing or at least reducing human injury. Because most of the relevant literature is focused mainly on collisions in traffic accidents (TAs), only some of the literature reviewed in this paper involves research results on other aspects of collisions. In this review, based on the background of DHMs and the application of DHMs regarding human injury biomechanics in collisions field, research results regarding the development of DHMs are described, the methods for verifying such models are introduced, and the application of the research results is discussed based on the aspect of human injury biomechanics. From the research literature, the development and validation of DHMs and their application in human injury biomechanics are summarized, and future research trends are proposed and discussed.

Conservation tillage is an alternative to conventional tillage (CT) for addressing the issue of soil degradation, while how it affects soil quality remains unclear. To characterise the temporary and stable effects of 8 years of conservation tillage on soil quality, topsoil (0–20 cm) properties, 16S rDNA‐based bacterial community properties and their relationships were analysed. Three tillage practices (CT [as the control], subsoiling tillage [ST] and no tillage [NT]) were compared at the sowing and harvest stages of a continuous winter wheat (Triticum aestivum L.) system. The mean weight diameter of the water‐stable aggregate, organic matter, total N/P/K and available K consistently improved with NT at both crop stages, with averages of 26.8, 35.3, 38.5, 29.2, 13.1 and 59.1%, respectively. Similar but lower levels of improvements were observed under ST. Tillage did not significantly affect soil bulk density, penetration resistance and temperature, whereas NT significantly decreased capillary porosity by 7.9% at sowing. At the sowing stage, CT showed higher bacterial α/β‐diversity but lower soil water content and abundances of N‐cycling bacteria. The physicochemical properties showed significant correlation with the abundances of some genera belonging to Proteobacteria, Nitrospirae and Actinobacteria. After 8 years of experimentation, we found that conservation tillage, especially NT, resulted in stable effects on soil aggregation and nutrient storage. Although soil compaction temporarily decreased after CT, the bacterial community, soil water storage and the aforementioned stable effects were more favourable for soil sustainability under conservation tillage.