Shikakeology is a methodology for inducing people to change their behavior by using "shikake" (gimmicks) that prompt people to unconsciously want to engage in a behavior. Various problems exist in our society, ranging from familiar day-to-day issues like littering and traffic congestion, to global scale issues like air pollution and global warming. Shikakeology doesn't try to solve these problems by giving people a sense of duty or fear, or by imparting as sense of mission through education. Rather it tries to solve them by promoting actions via shikake that evokes a sense of curiosity or expectation, i.e., "I want to try it" or "that looks interesting." This paper presents examples that can be interpreted as shikakeology for traffic-related problem solving. The focus is on three areas: (1) alleviating congestion, (2) promoting tourism and excursions, and (3) curbing speeding while driving.

Metropolitan Expressway traffic management policies have involved pricing and other measures to ensure the smooth transportation of those connected with the 2020 Tokyo Olympic and Paralympic games as well as efforts to improve the environment in residential areas along the Kanagawa Route No.1 Yokohane Line. The latter included cutting emissions of suspended particulate matter (SPM) , nitrogen dioxide (NO₂), etc. by introducing an environmental road pricing discount for ETC equipped vehicles on the alternative Bayshore Route to encourage heavy vehicles to switch over from using the Yokohane Line. The present paper explains the impact of the traffic measures implemented for the Tokyo 2020 games and the environmental road pricing discount scheme that has been offered for 22 years since its trial introduction in 2001.

This paper presents a number of cases where traffic behavior is improved by things seen during driving, due to their influence on the driver's unconscious or conscious mind. Drivers must travel at an appropriate speed, but many drivers habitually travel at speeds higher than the speed limit. Conversely, there are also cases where, for topographical reasons, drivers slow down without noticing and cause a traffic jam. Also, drivers frequently don't temporarily stop when they should at cross-walks where pedestrians are trying to cross. As an approach for improving these driving behaviors, this paper presents examples where figures are drawn on the road surface or other locations, examples where movement of light is shown with illumination, and examples using "trick art." These examples can be understood as cases of "nudge" as advocated by behavioral economics.

Wrong-way driving is dangerous driving that leads directly to a serious accident due to a head-on collision. Therefore, various countermeasures have been taken against wrong-way driving on the expressway, but the number of incidents has not decreased. We implemented a step-by-step study of countermeasures for wrong-way driving, and hypothesized that the cause is the pre-dementia group of drivers. Analysis of driving data collected from people medically diagnosed with dementia suggested the appearance of a peculiar driving behavior, not seen in the elderly in general, caused by a disorder similar to that diagnosed, thereby providing the possibility of understanding the behavior that leads to wrong way driving.

Unlike railroads and airline flights—transportation modes that allow planned operations—it is difficult to control individual cars, and this is one factor causing traffic congestion. In recent years, gamification, a technique that incorporates game elements into non-game contexts, has been attracting attention, and it is being used as a system to encourage people to change their behavior. This paper introduces a gamification system, Tomei Quest, that aims to change driving behavior on an actual expressway, and reports on a social experiment conducted on that expressway.

The rate of traffic accidents caused by elderly drivers has been increasing and become a social problem in Japan, while the total number of traffic accidents is declining. To reduce the rate of traffic accidents caused by elderly drivers, we are proposing and conducting R&D on a Driver Agent which encourages drivers to improve their driving behavior with the goal of extending their driving life years through self-help. In this paper, we introduce the concept of our agent system and several verification and demonstration experiments previously conducted for realizing the agent.

As automated driving systems become increasingly advanced, we are seeing a mixture of self-driving vehicles at multiple levels. Factors such as vehicle behavior and driver role vary depending on the automated driving level. In this sort of society, there is a need to use not only structural approaches such as systems, laws and regulations, but also educational strategies such as cultivation of drivers and traffic users to have safe attitude and behaviors in order to realize safe, secure, and smooth traffic. This paper proposes the development of systems and mechanisms for safety education from the perspective of educational technology. In particular, the contents to be learned, teaching materials, and teaching methods will be described, and the direction that should be taken in the future will be discussed based on empirical verification of the methods that have been effective.