Modeling Driver Responses During Automated Vehicle Failures
Grant
Overview
Overview
abstract
Automated and connected vehicle technologies, like truck platoons, offer tremendous promise for driving safety, efficiency, and productivity. Some projections even go as far to suggest that these technologies will eliminate all traffic fatalities. However, the benefits of these technologies will only be realized if they are designed for the human beings that interact with them. This interaction is particularly significant in cases where automation fails or hits an operational limit, where drivers may unexpectedly be asked to resume control of the vehicle often with little time to re-engage and react before a crash. One method of alleviating these problematic transitions is to integrate models of human behavior directly into the design process. The models can be used to predict human reactions and differentiate between scenarios where the driver can recover safely, and those where a crash is likely to occur. In this project we develop a model of human behavior during automation failures that may be integrated into current and future design processes for automated vehicles. We will use this model to generate a set of design guidelines for future automated vehicle following technologies that will promote safety and reduce automated driving crashes.
