Redefining Engineering Ethics in the Context of Society and Technology

Norihisa Miki (Keio University, Department of Mechanical Engineering)

As the impact of technology on society grows exponentially, engineering ethics must be redefined within the context of its relationship with society. This redefinition should not merely follow the transformations of society but rather anticipate them, actively designing a desirable future. In this lecture, I will discuss engineering ethics and society, drawing on specific examples and, to a significant extent, my personal perspectives.

Characterizing micro-ethics in autonomous vehicles using scenarios

Masao Ito (NIL)

To ensure the safety of autonomous vehicles, we must consider the relationships with the numerous agents that operate autonomously, including autonomous vehicles. We use the concept of microethics as one way to clarify these relationships. However, it is generally difficult to demonstrate its characteristics, and in this paper, we attempt to explain this using test scenarios shown in ISO 34502 and other standards.

Assessment of risky driving levels from traffic accident statistics data analysis on high-velocity runaway accidents on public roads
-Estimating the aggressiveness of high- velocity vehicles in causing human injuries through traffic accident statistics data analysis-

Yasufumi Sekine (Fukuyama University)

In collision accidents, the velocity at which the accident occurs is an important factor that determines the severity of human injuries, such as the fatal or serious injuries rate of vehicle occupants or pedestrians. In this study, the author attempted to derive an approximate equation for the relationship between vehicle velocity and the fatal or serious injury rate by traffic accident statistics data analysis, and to clarify the dangers of accidents that occur at velocity significantly exceeding the velocity limit.

Derivation of Support Concepts Based on the Driver's Cognitive Abilities

Nanae Michida･Masanori Honda･Kuninori Suzuki･Yoh Yamazaki･Kenta Okada･Hiromune Obayashi (Mazda)

Over 900 participants took part in measurements using two tasks displayed on a screen (a spatial recognition task using right-turn scenes of automobiles and the Stroop task). Based on the performance in each task, participants were classified into four groups. For each group, causal analysis was conducted on the results of a questionnaire regarding difficult driving scenes and the reasons for these difficulties. This was done to examine support concepts tailored to different ability types.