Through the literature review of PID control, robust control, sliding mode control and model predictive control, the characteristics of each method’s application in autonomous driving are analyzed. PID control is simple to implement but limited in complex environments. Robust control can deal with uncertainty and interference, but the design tends to be conservative. Sliding mode control offers rapid response and strong resistance to disturbances, yet it may cause chattering issues. Model predictive control provides precise trajectory optimization which requires high computational resources. The study shows that PID control is suitable for simple environments, robust control is suitable for situations requiring high stability, sliding mode control is applied to tasks that require for rapid adjustments, and model predictive control is suitable for scenarios that demand high precision. Future research will focus on integratiing multi-strategy to improve performance, adapt to various working conditions, and ensure stability and accuracy. Moreover, it is also necessary to develop efficient real-time algorithms, combine machine learning to enhance adaptability, improve control efficiency and reliability, and achieve accurate path tracking.

To systematically summarize the research status of multi-source fusion environmental perception technology for intelligent vehicles, this paper compares and analyzes the principles and characteristics of various sensors including cameras, Light Detection and Ranging (LiDAR), and millimeter-wave radar. The environmental perception technologies based on single-sensor approaches (such as camera-based object detection and LiDAR point cloud processing) and multi-sensor fusion strategies (data-level, feature-level, and decision-level) are reviewed with their technical bottlenecks and challenges. Typical algorithm cases are also discussed to explore their application effectiveness. The research findings indicate that: single sensors exhibit inherent limitations, such as cameras’ dependency on illumination conditions and LiDAR’s high cost with insufficient semantic information acquisition capability, as well as multi-sensor fusion technology significantly enhances environmental perception robustness through complementary advantages, yet challenges like data heterogeneity and insufficient real-time performance still remain unresolved. To meet the perception demands of complex scenarios, future development will focus on intelligent multi-modal fusion algorithms, cost-effective sensor integration, and V2X collaborative perception technologies.

In order to enhance the vehicle’s maneuverability and steering flexibility, a literature review is conducted to analyze the structures, technical applications, and controlling schemes of four-wheel steering systems, and summarize the main research methods and application outcomes of automotive four-wheel steering technology. Currently, the developement of automotive four-wheel steering systems is characterized by electrification, intelligence and integration. The four-wheel steering system is transitioning from the classic mechanical passive structure to a more mature electric active four-wheel steering structure. The control schemes for four-wheel steering systems have evolved from single-performance four-wheel steering control technology towards more complex multi-system integration and active fault-tolerant control technology. In the future, electrification, modularity, precision, speed,and safety-reliability are trends for advanced four-wheel steering systems, which are also effective ways to enhance the vehicle maneuverability and steering flexibility.

A redundant braking system composed of an Integrated Electronic Control Brake System (IBC) and a Redundant Brake Unit (RBU) has been proposed. Firstly, the working principle and modes of the IBC+RBU system are analyzed. Then, the pressure control of the RBU is implemented based on the Hardware Abstraction Layer (HAL) module. Next, a control strategy for the IBC+RBU to take over Level 3 autonomous driving is developed, and the Anti-Lock Braking System (ABS) is controlled based on the RBU. Finally, a Hardware-In-the-Loop (HIL) test bench is set up for HIL testing and verification. The research results indicate that the current system has the basic capability of redundant brake control which can ensure the reliability of redundant takeover and the stability of redundant brake control, and can meet the fundamental functional and performance requirements of Level 3 autonomous driving.

To enhance data security management in the automotive industry and establish a robust industry-wide data security management system, this paper analyzes policies, standards, current state of data security and the compliance of enterprise data security. The following issues are identified: multiple layers of data regulation lacking effective coordination, inconsistent standards and specifications, a weak supply chain protection system, and a shortage of specialized talent. In response to these challenges, the following development suggestions are proposed: Establish a comprehensive regulatory mechanism for data security in the automotive industry. Clearly define the boundaries of responsibility for different processing entities. Accelerate the classification and grading of data, as well as the management of critical data. Enhance data security management and risk prevention awareness and capabilities throughout the entire industry chain. Strengthen the training and development of professionals specializing in comprehensive industry data security.

In order to explore SOA architecture development methods and processes,through method research, process analysis and development practice, a software component development method under the framework of service-oriented architecture is proposed, and the software component development process conforming to AUTOSAR specification is analyzed.Based on the proposed method and process, the development practice from requirement analysis, service design, architecture design, application development, software integration and testing is given.The application proves that this development method is helpful for Oems to realize the integration and reuse of software modules more efficiently, with good iteration and expansibility.

In order to optimize the structural design of laminated forked contact, the stress of laminated forked contact is studied, and the coupling relationship between the structural parameters and the stress of the contact is analyzed as well. The mechanical field simulation analysis is conducted using COMSOL to simulate the stress field distribution, insertion force variation during the insertion process, and contact pressure between the contacts. Theoretical analysis reveals that the contact pressure and insertion force are directly proportional to the elastic modulus, cross-sectional moment of inertia, and material interference. The stress concentration area of the laminated fork-shaped contact component is located at the inner side of the root of the fork spring. In the future, targeted optimization of the above structural parameters can improve the contact performance between contacts.

In China’s road freight market, there exists the issue of decentralized transportation capacity, requiring online freight platforms to allocate logistics tasks according to travel preferences of freight operators and optimize the matching of vehicles and goods. Thus, a data-model collaborative-driven classification method for truck logistics patterns is proposed. Firstly, based on the truck trajectory data, 5 characteristic parameters including turning radius, activity entropy, average daily travel locations, average daily travel time, and average daily travel distance are constructed. After dimensionality reduction by Principal Component Analysis (PCA) and clustering by K-Means Cluster, trucks are categorized into 3 types of logistics patterns: long-distance round-trip, short-distance fixed-point, and short-distance multi-point. Secondly, the network motif identification technology from graph theory is introduced, generating a directed logistics network from truck OD data, using the DotMotif Algorithm for motifs recoginition and selecting p-value to test the significance of motifs. Finally, by deeply analyzing the connection between network motifs and the typical topological structures of truck travel chains, the differences in significant motifs within the logistics networks of different logistics modes of trucks are explained, verifying the accuracy of the the truck logistics pattern classification results.

Safety reliability, and driving range are critical considerations that impact consumer decisions in the electric vehicle market. Battery capacity and safety serve as principal metrics for evaluating the dependability of electirc vehicles. In order to enhance the battery capacity and safety reliability of electric vehicles and consolidate China’s leading advantage in new energy vehicles, this paper conducts a comparative analysis of the features of liquid and solid-state batteries of electirc vehicles, delineates the benefits and technical pathways of solid-state batteries, and identifies the challenges and strategic solutions in the advancement of solid-state battery technology. The paper concludes with an analysis of the capacity planning for the commercial deployment of solid-state batteries, offering insights for further research in the field.

In order to meet the requirements of vehicle quality and safety, and reduce the complexity and Research and Development(R&D) cost of implementing quality and safety process system, this paper discusses the method of integrated implementation of Automotive Software Process Improvement and Capability Determination(ASPICE), Functional safety, Safety of the intended functionality, Security and other R&D systems based on the whole process of automotive software development. A fully integrated research and development system method based on the quality and safety requirements of intelligent networked vehicles is proposed. It reduces the difficulty and cost of quality and safety development of intelligent networked vehicles.