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Abstract:
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The Naturalistic Driving Study (NDS), characterized by continuous data collection via multiple video cameras and sensors during regular daily driving, provides unprecedented high resolution information on driver behavior, traffic condition, and vehicle condition. The large amount of data collected via NDS and a wide spectrum of research questions can potentially be answered by NDS bring challenges in data processing, modeling, and inference. This paper will discuss the opportunities and challenges for statistical analysis of NDS data, including time-variance risk factors, recurrent event models, and issues associated with crash surrogate. The statistical challenges will be demonstrated with examples and results from the Strategic Highway Research 2 NDS, the 100-Car NDS, and the Naturalistic Teenage Driver Study.
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