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Toyota Launches Five Studies into Human Acceptance of Automated Driving Systems

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2018 Toyota RAV4 exterior

Toyota’s Collaborative Safety Research Center (CSRC) has announced five new research projects, undertaken in collaboration with five research institutions across the United States, are launching to better understand “how drivers use and respond to advanced vehicle technologies, including automated driver assistance systems.”

The studies are part of CSRC Next, a five-year program aimed at facilitating the transition to “future mobility”—specifically, autonomous vehicles and artificial intelligence. They will launch in partnership with the University of Washington, University of Michigan Transportation Research Institute, George Mason University, San Francisco State University, and Rockville Institute.

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While Toyota engineers are hard at work developing automated driver assistance systems on a technical level, the automaker is also concerned with how people will interact with them on an emotional level. Of the five studies, four will focus on societal acceptance of connected and automated vehicle technologies.

“The development of advanced vehicle technologies may be progressing faster than the ability of some people to fully understand their capabilities, and it’s important to identify how drivers actually understand and use these emerging systems,” said Chuck Gulash, director of CSRC.

Gulash believes that by conducting the studies and then sharing their insights not just with the industry but also with the government and technology communities, they can help society more readily accept the new technologies.

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Project Title Description Institution
A Neuroergonomic Evaluation of Mental Model Development
of Future Automated Driving Technologies
This project is aimed at objectively determining (through neuroergonomic methods) how different factors impact mental model development and evolution of advanced safety technologies. George Mason University
A Naturalistic Driving Evaluation of Mental Model Development of Future Automated Driving Technologies This project will develop a taxonomy of mental model development of automotive safety technologies by determining in a naturalistic driving setting how users develop and maintain mental models as AV safety technologies are integrated into the vehicle. Rockville Institute
Effectiveness of Short and Long Term Education Methods to Enhance Risk Mitigation and Associated Safety-Related Driving Skills The aim of the project is to develop analytical models that can capture and identify changes in driver performance that are indicative of risk mitigation behavior and to assess the effectiveness of candidate behavioral countermeasures aimed at curbing future risk. University of Washington
Guidelines for Development of Evidenced-Based Countermeasures for Risky Driving The overall project objective is to create a set of guidelines that can be used to inform the development of risky driving countermeasures that are evidence-based, guided by theory, and lead to sustained behavioral change.  This will be done by identifying the underlying constructs of current, and future, risky driving behaviors, identifying driver attributes that contribute to the performance of these risky behaviors, and finally, ascertaining the behavior change theories that are mostly likely to create lasting change. University of Michigan Transportation Research Institute
Effective Stimuli and Behavior for Driving Safety in Automated Driving This project provides a proof of concept that appropriate behaviors toward perceived risks can be generated automatically and effortlessly after a short form of training that links stimuli to adaptive behavioral dispositions. San Francisco State University