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Browsing by Author "Wu, Lingtao"

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    Connected Vehicle Data Safety Applications
    Martin, Michael; Wu, Lingtao; Ramezani, Mahin; Li, Xiao; Turner, Shawn; Stutes, Sophia; Hasan, Faiza; Potter, Michael (2023-09)
    The large-scale assessment of how driving behavior affects traffic safety and ongoing surveillance is hindered by data collection difficulties, small sample sizes, and high costs. Connected vehicles (CV) now offer massive volumes of observed driving behavior data from newer vehicles with myriad electronics and sensors that monitor the state of the vehicle, environmental conditions, and the driver’s actions. This project evaluated the viability of CV data in roadway safety applications with the objective of improving existing predictive crash methods, measuring traffic speed and its relationship to crashes, and determining whether CV data could be used to evaluate pavement marking products. The research team developed safety performance functions (SPFs) for rural two-lane segments and urban intersections in Texas. The results showed that the SPFs improved with the addition of hard braking and hard acceleration counts in a majority of areas. Further, a variety of CV speed measures were generated from the CV data and were shown to have conflicting correlations with crash risk and counts. Lastly, the research team developed the data processing methods for evaluating pavement marking products but was unable to perform an evaluation due to the lack of detailed construction project records.
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    Using Health Behavior Theory and Relative Risk Information to Increase and Inform Use of Alternative Transportation
    Glenn, Laurel; Sinha, Nishita; Dopp, Lia; Shipp, Eva; Jiles, Kristina; Edwards, Samantha; Hosig, Kathy; Wu, Lingtao; Villani, Domenique; Quint, Nicholas; Ogieriakhi, Macson; Perez, Marcelina; Woodson, Caitlin; Martin, Michael; Ramezani, Mahin (2024-01)
    One of the main goals of the Virginia Tech (VT) Alternative Transportation Department is encouraging the VT community (including students, faculty, and staff) to walk, use the bus, carpool, or ride bicycles for alternative transportation to decrease dependency on vehicle use and traffic around campus and increase overall safety. This project develops an intervention and education program to encourage alternative transportation to, from, and around campus to reduce campus traffic. In addition, since there is currently no standardized approach for computing the injury rates for non-vehicle roadway users, this project also refines and assesses a methodology for estimating injury rates for pedestrians and pedalcyclists, which was used to inform the developed educational alternative transportation safety course.