“Human” Problems in Semi-Autonomous Vehicles: Understanding Drivers’ Reactions to Off-Nominal Scenarios

ABSTRACT

Research related to autonomous vehicles and to their implications for human-machine interactions is on the rise. Advanced Driver Assistance Systems have become increasingly popular in vehicles currently deployed on the market, making researchers wonder about potential risks in case of technology failures for drivers that become accustomed to the use of such technology. To further our understanding of such concern, this work looks at the currently available data from autonomous vehicles field testing that has been carried out in California from 2014 to 2017. Our examination includes both qualitative and quantitative analyses, respectively, based on (i) the type of response in terms of control takeover in off-nominal scenarios that led to collisions involving autonomous vehicles; and (ii) the time to takeover after disengagements of the autonomous technology that acts as “brain” of the vehicle, with the request to the human driver to regain control of the vehicle. Our findings include expected values for the response time, discussion of factors that affect dispersion, presentation of how to determine trust and experience effects in the data, as well as a careful comparison with state-of-the-art literature on the topic.

Notes

1. In those cases, while the monitoring is still performed by a human, this human is not the primary driver, and the workload is thus not placed on the main driver.

2. Negative correlation at r(21) = −0.071 for Waymo and positive correlation at r(13) = 0.2983 for Mercedes-Benz, but p-values > 0.2.

Additional information

Funding

Funding for this research was provided by the US Department of Transportation Office of the Assistant Secretary for Research and Technology University Transportation Centers Program (grant 69A3551747127). The grant is managed by the Mineta Transportation Institute (MTI) of San Jose, CA.

Notes on contributors

Francesca M. Favarò

Francesca M. Favarò is an Assistant Professor in the Department of Aviation and Technology of San Jose State University, California. In 2016 she founded the RiSA²S lab, which deals with Risk and Safety Assessment of Autonomous Systems such as Unmanned Aerial Systems and autonomous ground vehicles.

Sky O. Eurich

Sky O. Eurich is a graduate student in the Human Factors and Ergonomics program at San Jose State University. He currently conducts research for the RiSA²S lab at San Jose State and for the Training and Cognition lab within the Human Systems Integration Division at NASA Ames.

Syeda S. Rizvi

Syeda S. Rizvi is a third year undergraduate student studying Electrical Engineering at San Jose State University. At RiSA²S her research has been focusing on a simulation based project that analyzes driver response times to disengagements of the autonomous vehicle technology.