Rare Failures, Public Perceptions, and Automated Driving

Rare Failures, Public Perceptions, and Automated Driving

Overview

Daniel V McGehee, Professor of Industrial and Systems Engineering at the University of Iowa, joins us for the CCAT Distinguished Lecture.

This lecture explores the “vaccine paradox” of automated driving: why rare, highly publicized failures of self-driving vehicles provoke intense emotional and political reactions while the far more common harms of human driving remain normalized. Drawing on risk psychology, public-health history, and human-factors research, Prof. McGehee examines how visibility imbalance, trust, and perceptions of control shape public acceptance of emerging vehicle automation. Using real-world examples from automated-vehicle deployments alongside lessons from vaccine adoption and safety communication, the talk argues that societal expectations for perfection in automation may obscure meaningful population-level safety gains. The presentation concludes by discussing how transparency, responsible system design, and careful language around driver-assistance technologies can help align public perception with evidence as automated driving evolves toward broader deployment.

Daniel V McGehee, Professor of Industrial and Systems Engineering at the University of Iowa, joins us for the CCAT Distinguished Lecture.

This lecture explores the “vaccine paradox” of automated driving: why rare, highly publicized failures of self-driving vehicles provoke intense emotional and political reactions while the far more common harms of human driving remain normalized. Drawing on risk psychology, public-health history, and human-factors research, Prof. McGehee examines how visibility imbalance, trust, and perceptions of control shape public acceptance of emerging vehicle automation. Using real-world examples from automated-vehicle deployments alongside lessons from vaccine adoption and safety communication, the talk argues that societal expectations for perfection in automation may obscure meaningful population-level safety gains. The presentation concludes by discussing how transparency, responsible system design, and careful language around driver-assistance technologies can help align public perception with evidence as automated driving evolves toward broader deployment.

Lineup

Headliner

Daniel V. McGehee

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Highlights

  • 1 hour
  • In person

Location

University of Michigan Transportation Research Institute

2901 Baxter Road

Ann Arbor, MI 48109

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Agenda

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Lecture Starts

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Webinar Introduction

Prof. Henry Liu

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Presentation

Prof. Daniel V. McGehee

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Center for Connected and Automated Transportation
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