Strategies
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Improve the interaction of the driver with an autonomous vehicle system to avert or minimize the impact of crashes. |
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Develop standard simulation/verification models to effectively understand human behavior and pre-crash safety over a wide range of autonomous vehicle properties and behaviors. |
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Use human behavior data across such variables as age, physical size, or alcohol intake, to inform the actions of the driver in pre-crash scenarios. |
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Include policy and regulation considerations early in the R&D process to accelerate the transition of promising research outcomes into widespread practice. |
Projects
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Pre-crash Multi-vehicle Experimental Analysis Using a Networked Multiple Driving Simulator Facility |
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Driver Models for Both Human and Autonomous Vehicles with Different Sensing Technologies and Near-crash Activity |
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Cognitive Attention Models for Driver Engagement in Intelligent and Semi-autonomous Vehicles |
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Bioinjury Implications of Pre-crash Safety Modeling and Intervention |
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Pre-Crash Interactions Between Pedestrians and Cyclists and Intelligent Vehicles |
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Safety Policy Implications and Information Dissemination |
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Technology and Enhancements to Improve Pre-Crash Safety |