In　recent years，mega-casting aluminum alloy structures have gradually been used to replace traditional stamping-welded body-in-white structures. The study on lightweight design of mega-casting aluminum alloy rear floor structure is conduced in this paper. An equivalent analysis scheme is proposed for the analysis of mega-casting vehicle body components. Regarding the processing and performance of the mega-casting structure，the processing constraints for the design are investigated，and the heterogeneity of its material properties is clarified. Based on the topology optimization method，the design domain of the structure is analyzed and the ideal topological design is obtained. Finally，a lightweight design is carried out，achieving a 7% weight reduction while ensuring performance. The study illustrates the design and optimization process of the mega-casting vehicle body components，which has certain reference significance.

The front axle manufactured through forging has large dimension，and the stress on it is complex. It is difficult to lightweight due to the limitation of the I-beam structure. In this paper，the design method of hollow front axle is given，and the hollow rectangular structure with variable cross-section and wall thickness and a combination of leaf spring seats are used to achieve lightweight and improve bending and torsion resistance. The influence of wall thickness at the kingpin hole on the strength of the fist is revealed，and the appropriate wall thickness range of the fist and the height and width coefficient of the plugging hole is given，by the vertical and longitudinal working conditions of the finite element mode. The 1：1 hollow front axle sample with an axle load of 5 t is produced by using seamless steel pipes，which is 10.75% lighter than the forged front axle. The variation law of vertical displacement and axial stress changes on the lower surface of the shaft and the stress distribution at the edge of the sealing hole on the outer end face of the fist are revealed through stiffness tests under vertical and longitudinal working conditions，as well as static strength and fatigue life tests under vertical working condition. The results show that the stiffness and static strength of the variable cross-section hollow rectangular front shaft meet industry standards，and the fatigue life under vertical working condition is much higher than industry standards. It is indicated that the variable cross-section hollow front axle can improve performance and achieve lightweight.

Megacasting during rapid filling and cooling processes inevitably generates defects，which significantly impact the mechanical properties of castings. However，it is difficult for existing mechanical analysis models to accurately predict the properties in defective castings，posing substantial challenges to the design of structurally safe castings. To solve the problem，a constitutive model and a fracture criterion of cast aluminum considering defects are proposed in this paper. Five different shapes of samples are cut from different locations of the megacasting floor，and experimental tests are carried out. The defect information on the fracture sections is statistically analyzed using scanning electron microscopy. Based on the stress-strain curves of the standard tensile samples，a constitutive model considering defects and saturating stresses is proposed to accurately characterize the strain-hardening properties. Based on the existing Modified Mohr-Coulomb （MMC） fracture criterion，an improved MMC model considering defects and stress states is proposed，and the parameters are calibrated by four different shaped samples. To validate the effectiveness of the proposed model，a comparative analysis between experimentation and simulation is conducted. The results show that the proposed constitutive model has a high fitting accuracy compared with the traditional hardening model. The load-displacement curves of the tests and simulation of different samples are in good agreement，which verifies the validity of the proposed fracture model. This study provides a novel approach to accurately predicting the mechanical properties of megacasting aluminum alloys.

In order to develop a hood with better pedestrian protection performance，firstly three types of straw energy absorption modules are designed，specifically circular，triangular and rectangular. Subsequently，the CSEAM sample with PA11 material is prepared and the finite element model is verified. Then，the human body injury protection effectiveness of the three types of Novel Straw-shaped structure Sandwich Hood （NSSH） is evaluated by simulation and the deformation mode is analyzed. The results show that the three NSSHs can significantly reduce pedestrian head injury，and the Triangle Straw-shape structure Sandwich Hood （TSSH） has the best protective effectiveness on human body injury. The deformation is uniformly diffused in a regular shape，and the peak of acceleration and impact force in each stage of the collision waveform is optimized by reducing the overall structural stiffness of the hood. Further analysis shows that the human body injury protection effectiveness of TSSH decreases with the increase of vehicle speed and impact angle，and the injury caused by TSSH is significantly lower than that of the original hood，indicating that raising the hood can reduce the impact angle to better protect pedestrians，while when the Ratio of Pedestrian height to Bonnet leading edge height R_h≤2.1 and R_h≥2.45，the head only impacts the hood and windshield，respectively. It can be used as the criterion of hood lift. The research results can provide support for the design of hood structure with better pedestrian protection effectiveness.

The detection of free space in underground mine tunnels is the key sensing technology for underground mining autonomous driving systems. However，the characteristics of low illumination and complex working environment inside the tunnels bring great challenges to this task. In view of this，in this paper an algorithm for detecting free space in underground mine tunnels is proposed. Firstly，a dual-branch feature extraction backbone network is proposed to solve the problem of difficulty in extracting image features caused by the degradation of tunnel details. Secondly，for the problem of incomplete detection of drivable areas in underground mining tunnels，an adaptive multi-scale atrous spatial pyramid pooling feature enhancement module is proposed. Finally，a dual-branch channel attention mechanism fusion module is developed to solve the problem of inaccurate boundary extraction in the underground mine tunnels. The experiments are conducted on a self-made dataset specifically designed for underground mine tunnels. The results show that the proposed algorithm surpasses other existing methods such as Deeplabv3+，UNet，DDRNet-23，and PIDNet，with an increase of 2.07，2.39，1.87，and 1.92 percentage points in terms of MIoU scores，and 1.78，2.45，1.84，and 1.86 in terms of mAcc scores，respectively. The effectiveness of the proposed algorithm has been validated through its successful application in real mine tunnel scenarios，particularly for underground mining autonomous driving vehicles.

A variable following characteristic traffic vehicle modeling method for intelligent driving system testing is proposed in this paper. Firstly，by clustering and analyzing natural driving data，a highly realistic interactive personalized car following model is established，and the model output coupling is used to assign multiple weights to construct a traffic vehicle model with variable car following characteristics that can be used for intelligent driving system testing. Then，by establishing the traffic vehicle trajectory evaluation method，the rationality，diversity and authenticity of the model's output trajectory are verified. Finally，a joint simulation platform is built to test the application of the constructed traffic vehicle model to the Automatic Emergency Braking （AEB） algorithm. The results show that the traffic vehicle model constructed in this paper can output reasonable，diverse，and realistic trajectories under different car following characteristics. When the number of trajectories reaches 60 000，the average root mean square error matched with the real natural driving speed trajectory is 0.427 m/s. Moreover，the behavioral response of the tested system varies under different traffic vehicle trajectory characteristics. By changing the weight coefficients，the evolution law of the tested system response can be revealed，and targeted testing of the tested system performance can be achieved.

Considering the limitation of global fixed bandwidth of load extrapolation for kernel density estimation，a load extrapolation method based on K-Average Nearest Neighbor Density-Based Spatial Clustering of Applications with Noise （KANN-DBSCAN） kernel density estimation （KDE） is proposed. The load data is grouped and clustered using the KANN-DBSCAN clustering algorithm，and the Rule-of-thumb （ROT） method is used to obtain the optimal bandwidth between different clusters. Then the kernel density estimation is conducted，and finally extrapolation is carried out using Monte Carlo simulation. The extrapolation rationality is verified using the measured load data of a certain electric vehicle on user road as the application object. The extrapolation effect is assessed by the three indicators of statistical parameter quantity，goodness of fit，and pseudo-damage. The results show that compared with the traditional fixed bandwidth kernel density estimation extrapolation method，the extrapolation load obtained by the DBSCSN kernel density estimation extrapolation method is closer to the actual load in statistical parameters，and the error of the mean，standard deviation，and maximum value is only 1.9%，4.3%，and 1.9%，respectively. The magnitude cumulative frequency curve fits R ² are all greater than 0.99，and the pseudo-damage is close to 1. The results show the effectiveness of the clustering method in kernel density estimation load extrapolation，which is helpful for compiling the load spectrum of electric vehicles on customer service road，and can provide reference for the load extrapolation of mechanical parts with similar load distribution characteristics.

The design of the floating valve plate effectively addresses the problem of cylinder block tilting at high speed in axial piston pumps/motors，aligning with the trend towards high-speed development of axial piston pumps/motors and gaining attention in recent years. However，there is still a lack of systematic dynamic modeling and dynamic characteristic research for the piston pump/motor system designed with floating valve plate，which limits the design of floating valve plate piston pump/motor products. A comprehensive parameterized dynamic model of the system that considers its detailed structural features is established for the piston pump motor system designed with floating valve plate. The study focuses on the laws of dynamic changes of the pressure in the high-pressure oil circuit and the auxiliary hydraulic chambers，and the model's correctness is verified through bench tests. The results show that the high-pressure oil circuit exhibits a "sharp drop and slow rise" characteristic of "sawtooth" pressure pulsations，which are intense. At a pump speed of 1 000 revolutions per minute （r/min），the average pressure in the high-pressure oil circuit at 20 and 40 MPa pressure levels results in pulsation amplitudes as high as ±1.5 and ±3 MPa，respectively. The fluid pressure in the auxiliary hydraulic chamber exhibits a dynamic change pattern of "rapid follow-up and slow decline，" meaning that once the auxiliary hydraulic chamber is connected with the high-speed rotating piston chamber，its fluid pressure almost immediately follows the piston chamber pressure changes without attenuation or lag. After disconnection from the piston chamber，it can still maintain the chamber pressure effectively.

The interaction ability between Highly Automated Vehicles （HAV） with human-driven vehicles is critical to the operational safety and efficiency of hybrid traffic in future. In order to test the interactivity of HAV，the background vehicle in the testing scenario needs to have naturalistic interaction characteristics and reflect the heterogeneous interaction strategy of human drivers. Based on the game theory，the Game-theoretical Strategic Interaction Model （GSIM） is developed in this paper. In the individual utility function，the interactive social characterization parameters with distinguishable values are introduced to directionally regulate the interaction strategy of the background vehicle. The test results of unprotected left-turning scenarios at intersections show that GSIM preserves the interpretability of natural driving stepwise planning and mutual interactions to ensure simulation accuracy of interactive behaviors. GSIM is also able to effectively reflect the interactive strategy of human driving in high-risk scenarios，helping to provide challenging and valuable testing scenarios. Compared to traditional Intelligent Driver Models，GSIM improves average simulation accuracy by 42.8% in unprotected left turn scenarios and serious conflicts recurrence rate by 25.8%.

Predictive cruise control （PCC） performs long-term speed planning at the planning layer with the objective of predicting energy savings and short-term tracking control for the vehicle speed at the execution layer. Integrating these layers into a single optimal control problem poses significant challenges in system design due to the different time scale step requirements between the planning layer and the execution layer. To address this challenge，a hierarchical control approach is adopted in this paper. At the planning layer，an improved twin delayed deep deterministic policy gradient （TD3） algorithm is utilized to determine the long-term planning speed over the prediction horizon. Meanwhile，at the execution layer，based on model predictive control （MPC），taking the planned vehicle speed as the reference speed and considering engine fuel consumption characteristics and transmission shift laws，further economic optimization and tracking control of the planned speed are carried out in the short term. The hardware-in-the-loop （HIL） validation results show that combining the improved TD3 algorithm with MPC effectively resolves the time scale inconsistency between planning and execution in PCC，which can significantly reduce both fuel consumption and shift frequency during the cruising of heavy-duty commercial vehicles.