Abstract

Commercial heavy vehicle-borne freight will continue to be the dominant cross-region shipping mode for materials and goods for the foreseeable future. Federal hours of service (HOS) regulations mandate scheduled minimum times for of-duty and in-transit rest periods to minimize operator fatigue. Without timely, accurate information disseminated to drivers and carriers on where to park, complying to HOS regulations can often become a very challenging task for drivers. This paper describes a region-wide deployment of a unique non-intrusive, multi-camera, truck parking space detection and availability information dissemination architecture. The architecture leverages multi-view Structure and Motion methods to reconstruct a Three-dimensional representation of the environment for estimating unoccupied spatial extents to deduce truck parking availability. Unlike 2D camera sensor-based methodologies, the advantage is its immediate adaptability to a variety of parking facilities and scenarios without the need for any subsequent re-training. The approach also mitigates errors arising from occlusions, and many other environmental conditions that confound many 2D camera-based approaches. The region-wide deployment, operated by a state transportation agency, has been online since early 2019, and has thus far substantiated the technical and day-to-day operational viability of the approach. The performance throughout this period indicates an overall accuracy at or above 90%. This paper provides a general overview of the deployed system architecture and performance characteristics across varied parking facility designs, parking behaviors, and other environmental conditions.

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