Small Projects Year 3 (2014-2015)
Fault Tree Analysis for Accident Prevention in Transportation Infrastructure Projects
PI: Hyun Woo Lee (OSU), hw.chris.lee@oregonstate.edu
Co-Investigators: Ingrid Arocho (OSU)
Dates: 01/16/2015 – 06/15/2016
Status: Completed
UTC Project Sheet
Final Technical Report
The study will combine literature review and content analysis to develop a list of risk factors that lead to contribute to major accident types in transportation infrastructure projects. OSHA’s Fatality and Catastrophe Investigation Summaries will be the main source of data for the content analysis. OSHA requires construction companies to report any type of work-related accidents resulting in the hospitalization of three or more workers. Thus, this summary database contains valuable information regarding safety-related performance, which can be used as a basis for identification of accident types and risk factors. Read More
3D Virtual Sight Distance Analysis Using Mobile LIDAR Data
PI: Michael Olsen (OSU), michael.olsen@oregonstate.edu
Co-Investigators: David Hurwitz (OSU), Alireza Kashani (OSU)
Dates: 01/16/2015 – 06/15/2016
Status: Completed
UTC Project Sheet
Final Technical Report
This research explores the feasibility, benefits and challenges of a safety analysis for sight distances based on DOT Mobile Laser Scanning (MLS) data. This research will also develop a systematic MLS data analysis framework to evaluate sight distances in different practical scenarios. The use of high density MLS data for sight distance analysis provides a data driven solution to aid decision making for safe transportation, directly aligning with the PacTrans FY2014-2015 theme. Further, it fits directly within Topic Area #3 Technological Impacts on Safety. Read More
Development of Low-Cost Wireless Sensors for Real-Time Lifeline Condition Assessment
PI: Daniel Borello (OSU), daniel.borello@oregonstate.edu
Dates: 01/16/2015 – 06/15/2016
Status: Completed
UTC Project Sheet
Final Technical Report
This research proposes to develop a low-cost wireless sensor to assess the condition of the lifeline bridges following a natural hazard. The primary goal of the sensor will be to minimize cost and increase the ease of installation. Off-the-shelf hardware will be adopted to meet the design criteria, emphasizing multiple year autonomous operation. The sensors will be configured to measure individual member demands, calculated locally at the node, eliminating the challenge of time-synchronization. Structural models will be developed to predict the loss of the structure based on these measurements. The sensors will be paired with a wide-area network, allowing real-time analysis of the entire transportation system following an event. Therefore, this project will deliver a low-cost sensor that can be widely deployed throughout the Pacific Northwest transportation network to provide first responders with an overview of the current state, and route appropriately. Read More
