Abstract
Tractor-trailer freight hauling has increased markedly within the United States over the past several years, resulting in higher truck volumes. commercial heavy vehicle drivers are required under federal Hours Of Services rules to rest and take breaks to mitigate driving while fatigued. Although there are many rest area facilities available to truck drivers, there is a lack of persistent timely information on truck parking availability. An automated real-time sensing system to directly detect and disseminate parking space occupancy from truck parking facilities is described in detail. The methodology and system architecture are presented in which robust, persistent, parking occupancy detection is achieved by extending Structure from Motion (SfM) techniques using a multiplicity of commercial, off-the-shelf cameras. The system architecture allows the approach to be scaled to a region-wide comprehensive truck parking information system for commercial heavy vehicle drivers and operators. Per parking space detection accuracy of 99% is achieved over continuous operation. Classification accuracy under diverse scene and parking behavior scenarios is discussed.
Original language | English (US) |
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Title of host publication | Proceedings - IEEE International Conference on Robotics and Automation |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3989-3994 |
Number of pages | 6 |
ISBN (Electronic) | 9781479936854, 9781479936854 |
DOIs | |
State | Published - Sep 22 2014 |
Event | 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China Duration: May 31 2014 → Jun 7 2014 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
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ISSN (Print) | 1050-4729 |
Other
Other | 2014 IEEE International Conference on Robotics and Automation, ICRA 2014 |
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Country/Territory | China |
City | Hong Kong |
Period | 5/31/14 → 6/7/14 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.