Browsing by Author "Medina-Flintsch, Alejandra"
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- Developing a Web-Based Return-on-Investment Calculator for Truck Safety TechnologiesCamden, Matthew C.; Medina-Flintsch, Alejandra; Hickman, Jeffrey S.; Feng, Xueting; Hanowski, Richard J. (National Surface Transportation Safety Center for Excellence, 2020-10-08)Although large truck advanced safety technologies such as automatic emergency braking, lane departure warning, and video-based onboard monitoring are becoming more prevalent, adoption rates and use are lagging due to concerns about return on investment (ROI). To address this, researchers at the Virginia Tech Transportation Institute (VTTI) developed an Excel-based ROI calculator and accompanying user manual. This report describes an extension of that original project: a web-based version of that calculator available at https://www.vtti.vt.edu/roicalculator/. The report describes the rationale behind the calculator and an provides an overview of the resources available on the website.
- Large Truck Safety at Highway Railroad Grade Crossings: Developing a Naturalistic Commercial Motor Vehicle Database of Railroad Grade CrossingsCamden, Matthew C.; Manke, Aditi; Soccolich, Susan A.; Islam, Mouyid; Medina-Flintsch, Alejandra; Feierabend, Neal; Alemayehu, Desta (National Surface Transportation Safety Center for Excellence, 2022-10-12)In 2021, there were 2,131 collisions, 237 fatalities, and 653 injuries at highway-railroad grade crossings (RGCs). However, these data do not include the full scope of incidents at RGCs, as they do not account for vehicle-to-vehicle collisions (e.g., a rear-end collision when a lead vehicle stopped prior to traversing the RGC). This is especially true for the classes of commercial motor vehicles (CMVs) required to stop at all RGCs prior to crossing the tracks. The Virginia Tech Transportation Institute houses valuable data that may be used to better understand CMV driver behavior (and the behavior of other drivers near the CMV) at RGCs. One naturalistic driving study, the On-Board Monitoring System Field Operational Test (OBMS FOT), includes classes of CMVs required to stop at all RGCs: tanker trucks carrying oil/gas and motorcoaches. The objective of this project was to combine the OBMS FOT datasets with the Roadway Information Database and the Federal Railroad Administration’s Highway-Rail Crossing Inventory. Specifically, the purpose of this study was to identify all RGCs traversed by CMVs in the OBMS FOT (Hammond et al., 2021) datasets; identify which of those CMVs traversing an RGC were required to stop (i.e., a placarded CMV or motorcoach); identify the number of trips included in the OBMS that involved crossing an RGC; and create a database of RGCs that can be used in a future study to examine driver behavior of CMV and passenger vehicle drivers at RGCs. The final database included 1,733 RGCs traversed by a CMV that were in the OBMS FOT study. These vehicles made 52,358 trips across the 1,733 RGCs. This includes 17,990 trips of a tanker truck and 10,087 trips of a motorcoach traversing an RGC. This newly created database can be used in future research efforts to investigate CMV driver behavior at RGCs and to develop new countermeasures to reduce RGC crashes and their resulting injuries and fatalities.
- Large Truck Technology Return-on-Investment Calculator: User Guide and Instruction ManualCamden, Matthew C.; Medina-Flintsch, Alejandra; Hickman, Jeffrey S.; Hanowski, Richard J. (National Surface Transportation Safety Center for Excellence, 2020-04-21)In 2015, large trucks were involved in 415,000 crashes in the United States that resulted in approximately 116,000 injuries and 4,067 fatalities. One way to reduce these crashes and their resulting injuries and fatalities is through the adoption of advanced safety technologies (ASTs) such as automatic emergency braking, lane departure warning, and video-based onboard safety monitoring. Despite studies showing that ASTs effectively prevent or mitigate crashes, commercial motor vehicle (CMV) carriers often lack data on their associated return-on-investment (ROI). This project offers CMV carriers a research-based ROI calculator in the form of an Excel spreadsheet with an accompanying user guide.