Significant concern has been expressed about what will happen when autonomous vehicles fail while driving. This issue has been the source of many opinions and some suitable strategies have been proposed. However, little is known about proper ways for managing failure using methods that do not alienate potential purchasers of such systems. Inappropriate driver-vehicle interaction will lead to decreased safety and poor road user experiences. While the latter may not seem important, it will directly impact market adoption, public perceptions of autonomy quality, and other factors that could delay or derail otherwise successful market penetration of safety-enhancing technologies. Most of the research on vehicle autonomy failure centers on vehicle-to-driver handoffs. This is an important problem and significant resources are being devoted to this challenge. However, little attention is being spent on bystander interactions. How will pedestrians, bicyclists, and drivers of other vehicles react and interpret autonomous actions designed to keep the vehicle safe? For example, a likely failure mode when a successful handoff does not, or cannot, occur is for the vehicle to autonomously pull to the side of the road. Safety can be improved dramatically if the car is able to express the failure is occurring and a safety-oriented motion is underway. Drivers currently use hazard lights, extended turn signals, and other methods to inform nearby road users. Is it appropriate to use the same signals? Are new signals needed? How does wireless technology help or hinder such communication? This project will extend knowledge and findings from an existing, related project on appropriate human-robot interaction during autonomous robot failure. The project is focusing on new methods for autonomous robots to express failures so that operators and bystanders take appropriate action. Methodologies and lessons from this project will be applied to the proposed effort, thereby accelerating project activities.
Bystander Interactions with Failing Vehicle Autonomy
2018
9 pages
Report
No indication
English
Transportation & Traffic Planning , Data & Information Systems , Advanced Vehicle Control Systems , Cyclists , Driver vehicle interfaces , Drivers , Human factors , Human machine systems , Intelligent vehicles , Mechanical failure , Pedestrian safety , Traffic safety , Data and Information Technology , Highways , Pedestrians , Bicyclists , Safety and human factors , Society , Vehicles and equipment , Carnegie Mellon University
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