This paper presents ten key challenge areas that need to be at the center of automated vehicle discussions across all sectors and stakeholders, along with a glossary of key terms. It is intended to serve as a discussion guide and orientation piece for people entering the conversation from a wide variety of perspectives, including advocacy, public policy, research, injury prevention, and technology developers.

Key findings

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As some of the current detection systems rely on cues from the built environment (such as the striping of bike lanes to predict that a bicyclist may be near) (Levin, 2016), there is a need to consider policy and roadway design enhancements that can provide additional contextual warnings, improve detection of pedestrians and bicyclists, and provide a larger safety margin.

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All people have a right to travel on public streets safely, so ultimately Automatic Driving Systems and connected systems must find a way to detect and respond to all road users, not just those carrying devices. Consideration must be given to people who may not be carrying a device by choice or because they do not have the means to own a device.

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Communication issues are likely to be made more challenging by mixed fleets with many different Human Machine Interfaces and styles of operation. Data and “blueprint” sharing may be necessary (though not likely to occur voluntarily) to ensure that communication systems are consistently integrated and tested across all makes and models of vehicles, and understood by vehicle users and pedestrians and bicyclists alike.

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