Why Waiting for Perfect Autonomous Vehicles May Cost Lives
Nov 7, 2017
This report describes a simple model of how factors shaping the diffusion and performance of highly automated vehicles may interact and result in different safety outcomes over time. Insights from the model can help users consider how policies will shape the future of road safety.
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Highly automated vehicle (HAV) safety is a principal concern for the transportation industry, policymakers, and the public. Much of the concern is focused on the question of how safe HAVs should be before they are allowed on the road for consumer use. However, the safety performance and impact of HAVs will change over time and may have much greater effects in the long term than in the short term. Thus, to address this concern properly, stakeholders must also ask how safe HAVs will become over time and how policy choices made today could shape the future of road safety.
To help answer these questions, this report describes a simple model of how factors shaping HAV diffusion and performance may interact and result in different safety outcomes over time. It can be used to measure safety in terms of injuries, crashes, or other metrics. Importantly, the model does not predict the pace of future HAV diffusion, the rate of change in safety performance, or other factors. Instead, given a user's hypotheses, it estimates how many lives would be lost each year in a future with and without HAVs. The model helps users explore how different assumptions lead to different outcomes and which factors may lead to greater or lesser safety. Such insights can help users consider how policies might shape HAV diffusion and performance to improve safety now and over time.
Problem-Framing and Definitions
Modeling Safety in a Future Without Highly Automated Vehicles
Modeling Safety in a Future with Highly Automated Vehicles
Model Exploration and Illustration
Model Summary and Conclusions
Modeling Diffusion with a Logistic Function
Modeling Learning with an Exponential Decay Function
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