Developing a Cost-Effective Mobile-Based System for Collecting On-Demand Road Condition Images for Snowplow Operations Management
Mobile devices (e.g., tablets and smartphones) have become increasingly popular for collecting and processing transportation data for various purposes without the need for complicated systems that require operator training. In recent years, several state departments of transportation (state DOTs) have equipped snowplow fleets with different systems to communicate road condition images to assist winter operations supervisors in making operational decisions during winter storms. The existing systems usually consist of several pieces of equipment and automatically transmit the road condition images at only predetermined intervals. They are expensive because they require multiple pieces of equipment installed in the snowplows. Furthermore, existing systems do not enable supervisors in the office to request images if the received images are insufficient to determine the conditions of the roads. This study proposes a cost-effective and easy-to-use mobile-based system for operators to collect on-demand road condition images from fields or offices using the capabilities of mobile devices. The proposed data collection system was implemented in the TxDOT Wichita Falls District for the 2021–2022 winter season. The collected images were visualized in an ArcGIS map-based interface and assisted winter operations supervisors in asset management and operational decisions during winter storms. The results revealed that even operators with little experience operating technological devices could still operate the system using mobile devices. Moreover, these devices could be easily removed from the fixed mounts in snowplows to capture images that were not directly in front of the snowplows. The developed system also facilitated requesting road condition images by supervisors in offices using a web-based add-on when the received images are insufficient to determine the state of the roads. The proposed system simplifies the on-demand data collection process for operators and eliminates the need to conduct extensive training for operators.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484883
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Supplemental Notes:
- © 2023 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Darghiasi, Pooya
- Baral, Anil
- Shahandashti, Mohsen
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Conference:
- International Conference on Transportation and Development 2023
- Location: Austin Texas, United States
- Date: 2023-6-14 to 2023-6-17
- Publication Date: 2023
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 127-137
- Monograph Title: International Conference on Transportation and Development 2023: Transportation Planning, Operations, and Transit
Subject/Index Terms
- TRT Terms: Highway maintenance; Image transmission; Maintenance personnel; Mobile applications; Snowplows; Winter maintenance
- Identifier Terms: Texas Department of Transportation
- Geographic Terms: Wichita Falls (Texas)
- Subject Areas: Data and Information Technology; Environment; Highways; Maintenance and Preservation; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01886901
- Record Type: Publication
- ISBN: 9780784484883
- Files: TRIS, ASCE
- Created Date: Jun 30 2023 11:28AM