Events
DMS Statistics and Data Science Seminar |
| Time: Oct 08, 2020 (02:00 PM) |
| Location: ZOOM |
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Details: Speaker: Alex Vinel (Industrial and Systems Engineering, Auburn University) Title: Explaining and predicting unsafe driving events among commercial truck drivers: Lessons learned from observing 20 million driving miles using IoT sensors
Abstract: Highway transportation safety is one of the most pressing global public health issues. With the emergence of a multitude of sources of relevant information (such as real-time weather, traffic and vehicle kinematic data) there is a potential for employing advanced data analytics techniques to help address this problem. In this talk we will discuss a set of studies that was based on a large data set concerning commercial trucking operations in the US. We will review approaches to characterizing the relationship between the risk factors and incident risk, first with the goal of statistically explaining this relationship and then for the purpose of forecasting. In the former, we model the underlying time series as a Bayesian hierarchical non-homogeneous Poisson process, showing that intensity of incidents (significantly) increases with more driving and (significantly) reduces after rest breaks. In the latter, we employ machine learning methods to evaluate the extent to which it is possible to predict probability of traffic incidents (and hence evaluate the risk associated with a particular route).
Seminar website (which also contains the links for the recordings of the seminars): http://webhome.auburn.edu/~ezc0066/stat-datasci-seminar.html
Join from PC, Mac, Linux, iOS or Android: https://auburn.zoom.us/j/93758346031
If you're a new participant, we have a quick start guide here: https://aub.ie/zoomquickstart
Join from PC, Mac, Linux, iOS or Android: https://auburn.zoom.us/j/93758346031 Connect using Computer/Device audio if possible.
Or Telephone: Meeting ID: 937 5834 6031 Dial: +1 646 876 9923 (US Toll) or +1 301 715 8592 (US Toll)
Or an H.323/SIP room system: H.323: 162.255.37.11 (US West) or 162.255.36.11 (US East) Meeting ID: 937 5834 6031
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