PacTrans News
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April 25, 2024
PacTrans Regional Transportation Seminar with Petros Ioannou
On Tuesday, May 14, join us for our Spring Regional Transportation Seminar titled “Control of Vehicles and Traffic for Safety, Mobility, and Efficiency” with guest Professor Petros Ioannou.
Watch the Livestream Here.
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April 25, 2024
Computer Vision for Pedestrian Traffic Monitoring
The University of Idaho is working with the City of Moscow, Idaho, to test computer vision sensors provided by Numina, a new start-up company based in New York City. The sensors use sophisticated algorithms to interpret visual data to recognize pedestrian behaviors, such as crossing the street, waiting at crosswalks, or sudden movements. Compared to traditional methods like manual observation or radar-based systems, computer vision sensors offer higher precision and scalability, making them a more effective solution for enhancing pedestrian safety in urban environments. The data is saved in a cloud-based system that is easy to query and download for further analysis. Read More -
April 1, 2024
Applications now open for Washington Transportation Camp 2024!
Do you know a high school student itching for a STEM-packed summer adventure? Look no further!
Applications are now open for the summer 2024 Washington Transportation Camp.
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March 25, 2024
City of Kenmore Internship
The City of Kenmore is hiring a Part-Time Traffic Engineering Intern and more!
- Type: Part Time
- Salary/Pay Rate: $21.90 – $32.40
- Posted Date: 03/20/2024
- Deadline to Apply: 04/05/2024
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March 20, 2024
Automating Data Processing of 3D Point Cloud Data with Vo-Norvana
Lidar and Structure-from-Motion (SfM) technology have been widely used for collecting 3D point cloud data at high resolution and accuracy for various transportation applications, including infrastructure modeling and lane marking quality assessments.
Professors Erzhuo Che and Michael Olsen from Oregon State University (OSU) developed and implemented a framework named Vo-Norvana as part of a National Science Foundation-funded research project. This framework automates a significant portion of data processing by organizing the point cloud into individual segments/surfaces (Figure 1). Despite the extensive use of point cloud data in transportation applications, its complexity and volume present challenges in effective utilization.
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Figure 1. Example of Vo-Norvana point cloud segmentation: (a) raw mobile lidar point cloud data; (b) segmentation result where each color represents a segment.
Through the PacTrans Success Story Tech Transfer funding, the team worked to make the technology more accessible. They produced an intuitive graphical user interface (GUI) for Vo-Norvana, featuring functions such as point cloud file management, downsampling, and segmentation parameter adjustments. Additionally, the software was made compatible with both Windows and Linux environments.
Vo-Norvana has been presented and demonstrated to industry partners and transportation agencies, including the Oregon Department of Transportation. In 2020, the software was licensed to an OSU spinout company, EZDataMD LLC, for sustainable development and expanded use such as asset management, pavement crack mapping, road marking extraction and evaluation, and rockfall hazard analysis.
