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With the development of autonomous driving technology, it is of great practical and educational significance to consider the ethics in the process of its technology realization. On the one hand, compared with foreign countries, engineering ethics education still needs to be actively promoted and innovated in China. On the other hand, carrying out case study of engineering ethics meets the practical needs of training engineering talents. Based on this, this paper adopts a case study strategy centered on the autonomous driving ethics, and transforms the traditional teacher-centered teaching mode into a student-centered teaching mode in the form of role-playing and collaborative discussion. In addition, a curriculum design framework is proposed, which highlights initiative, participation and self-study guidance. Then, a simulation case of autonomous driving with increasingly complex scenarios is designed, guiding students to consider ethical issues in a deeper and more comprehensive way. As a result, the described teaching plan deepens the ethical awareness of engineering students in the project, and improves their ability to analyze and solve multi-dimensional engineering ethical problems.

With the continuous development and maturity of artificial intelligence, its application in many industries has gradually deepened, which has caused many ethical problems. This paper analyses the engineering ethical dilemma in the development of artificial intelligence from the aspects of intelligent robots, self-driving technology, killer robots and public information security, and further explores the causes of related problems. Finally, the corresponding countermeasures are put forward, including strengthening the supervision of artificial intelligence technology and products, enhancing the moral responsibility of scientists and engineers, strengthening international cooperation and building a human-machine fate community. The analysis of ethical problems and Countermeasures in artificial intelligence technology will help to solve the dilemma faced by AI technology in the development process to a certain extent.

Under the comprehensive background of the development of engineering education in the world today and the promotion of quality education in China, strengthening engineering ethics education of engineering masters meets the needs of engineering technology development, and is also an indispensable part of shaping high-quality engineers. However, engineering ethics awareness cannot be generated spontaneously. It needs to be cultivated and improved through engineering ethics education. Therefore, this paper designs a closed questionnaire from three aspects: school curriculum education, engineering ethics cognition and the application of ethical dilemma of driverless cars. The statistical data of the questionnaire shows that engineering masters do not pay enough attention to the engineering ethics curriculum and it is difficult to use the knowledge of engineering ethics to analyze and solve the actual ethical dilemmas. In addition, it is further found that there is a gap between professional masters and academic masters in the ethical awareness, and the reasons are related to the distribution of engineering ethics education courses offered by the school. This paper proposes three specific recommendations in response to the above problems.

In this paper, a mapping model for product surface morphology design based on ergonomics is proposed. The method advances the traditional approaches based on anthropometric measurements to a new one based on digitised product surfaces; thus, it simplifies the complexity of non-uniform rational B-spline surface representation during product design. The method was constructed by converting the experimental data to the surface shapes based on the pressure distribution map. An adjustment algorithm is presented to eliminate the errors in mapping non-planar base shapes. The experimental mapping data are pretreated, so that the mapping process reflects the statistical characteristics of the tested groups as far as possible. Based on the mapping model, a prototype implementation system for ergonomic product design is developed. As an example, a car seat design is presented to show the performance and availability of the method.

Considering the needs for getting more precise parameters and at the same time to get faster cutting speed and better surface roughness in Wire Electrical Discharge Machining (WEDM), the authors established a model of WEDM, which has higher forecast precision and generalization ability and could help us in getting better understanding of the basic principles of WEDM. The model combined modeling function of fuzzy inference with the learning ability of artificial neural network; and a set of rules has been generated directly from the experimental data. Integrated with the genetic optimization procedure, the fuzzy inference systems are used to optimize the wire electrical discharge model of WEDM and the optimum results of the model have proved the feasibility and practicability of the system in WEDM.