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For Collaboration between People and Machines

2013.01.31

Unit Name:
Human Assistance Research Unit
Unit representative:
Professor Makoto Itoh, Faculty of Engineering, Information and Systems

Unit members:
18 (4 faculty members, 1 postdoctoral fellow, 13 from other organizations)

Key words:
assistance, monitoring, data analysis, assessment of ability, automation

URL:

 

People are scared of losing concentration while driving an automobile due to fatigue or sleepiness more than anything else. One of the methods for increasing safety in such a situation is “automated” driving, or a assistance system installed in an automobile to prevent crashes. However, the automated driving system has complex problems, e.g., to what extent can we rely on it? Therefore, its introduction should be carefully considered from many different aspects. With the aim of developing an appropriate automated driving system, our research unit considers and predicts drivers’ judgments of situations, decision-making, and inattention due to excess trust in the assistance system.

Attentive human assistance facilitated by technologies for monitoring the behaviors of people

To develop a system for automated driving, it is essential to understand the conditions of drivers and their behaviors, and identify what is required to support their actions. We are involved in the development of monitoring technologies to understand the behaviors of humans. As shown in Figure 1, the sensors determine the distribution of pressure applied to the driving seat. They monitor the physical and psychological conditions of the driver, including the sleepiness and consciousness, while detecting the movement of the center of gravity.

Figure 1: Measurement of the pressure applied to the seat to determine the physical and psychological conditions of the driver
Figure 1: Measurement of the pressure applied to the seat to determine the physical and psychological conditions of the driver

 

The image of the face is used to determine what the driver is looking at and whether or not he/she is aware of danger. We develop pattern recognition technologies to assume the physical and psychological conditions of drivers and their intentions based on data collected using a simulator (Figures 2 to 4). We are determined to establish a methodology to develop a system in which both humans and machines are responsible for control, while considering the timing at which the vehicle should intervene for control in the event of an emergency.

Figure 2: Simulation equipment

Figure 2: Simulation equipment

Figure 3: Scene of a simulation-based experiment

Figure 3: Scene of a simulation-based experiment

Figure 4: Measurement in a simulation-based experiment

Figure 4: Measurement in a simulation-based experiment

Support provided by machines to complement the cognition of humans

We develop systems in which differences in the cognition of individual drivers are taken into consideration, from the viewpoint that machines complement the ability of humans, rather than automation to replace humans. Our research unit aims to design control systems that complement the functions of people with visual impairment due to glaucoma and memory and attention problems attributed to higher cerebral dysfunction, and help them drive safely. This theory and technology can also be applied in other fields, such as automated railway systems. As research on machine-controlled systems advances in Western countries, we are promoting collaboration with French and Dutch universities to conduct a wide variety of studies.

Social contributions and achievements
● Establishment of a basis for the unit to conduct research on automobile driving assistance as an international research center
● Development of technologies for assessment of the driving skills and ability of people, including patients with higher cerebral dysfunction
● Application of data analysis methods to actual problems (related to the safety of vehicles and airplanes in particular) to develop advanced preventive and safety-based technologies

(Interviewed on June 14, 2013)


Research Administration/Management Office at U Tsukuba TEL 029-853-4434