The primary objective of this project is to create a flexible architecture to enable wide-scale deployment, monitoring, and maintenance of a non-intrusive computer vision truck parking availability system across diverse parking scenarios. Such scenarios involve facilities that allow either undisciplined parking, or designated stall arrangements. Undisciplined parking facilities are actually relatively common place in many states in North America. The need for truck parking availability over contiguous regions is supported by the fact that driver perceptions of parking availability while traveling their routes, are often incorrect (FHWA, 2002). Our recent pilot study with Kansas adapted the multi-camera Structure and Motion (SfM) approach for undisciplined parking scenarios has indicated over this year an overall detection accuracy at, or above, 90%, demonstrating feasibility of the approach to handle undisciplined parking. As a result, the state of Kansas instrumented 22 sites along two major interstate corridors, that encompass both types of facilities, all of which will disseminate real-time parking availability through either roadside dynamic signs, or through an Internet portal to 3rd party stakeholders and application developers. Eighteen of them went "live" at the beginning of 2019, with the remainder to go live before the end of 2019. Accordingly, monitoring tools must be tightly integrated with the vision processing and parking notification pipeline to query the "health" of different system components: 1) real-time notification, and data retrieval 2) computer vision processing, and 3) camera sensor management. Furthermore, other tools to enable remote re-calibrations, and real-time data visualization of the computer vision processing pipeline, will also be developed. A technology transfer component that consists of System Engineering documents for the software supporting the aforementioned components will be completed in the early phases of the work, with specific training to Kansas DOT and other stakeholders. The architecture will then be evaluated by the Kansas DOT and the University of Minnesota members to assess long term system wide performance.
- Project number: 2019067
- Start date: 01/2019
- Project status: Active
- Research area: Transportation Safety and Traffic Flow