Insufficient availability of safe and accessible truck parking forces professional truck drivers to choose between adherence to federal hours-of-service regulations and parking in unsafe or unauthorized locations, including highway shoulders, ramps, and local streets. Challenges to developing an effective Truck Parking Information and Management System (TPIMS) for tracking commercial truck parking availability and informing drivers include non-stationary parking demand patterns, sparsity of data, and imperfect conditions for sensor reliability. The goal of this research is to develop a robust, adaptive, and deployable truck parking prediction framework, together with a practical Prediction Improvement Toolkit, that can maintain reliable TPIMS performance over time despite the challenges commonly observed in real-world deployments. Building on operational experience from WSDOT\u2019s TPIMS,\u00a0this research is focusing on advancing prediction methodologies and translating them into reusable tools, guidelines, and evaluation resources that will support long-term TPIMS stability, trust, and scalability throughout the system\u2019s lifecycle.<\/p>\n\n\n\n
Principle Investigator: Yinhai Wang<\/a>, Civil and Environmental Engineering, UW Insufficient availability of safe and accessible truck parking forces professional truck drivers to choose between adherence to federal hours-of-service regulations and parking in unsafe or unauthorized locations, including highway shoulders, ramps, and local streets. Challenges to developing an effective Truck Parking Information and Management System (TPIMS) for tracking commercial truck parking availability and informing drivers … Continue reading WSDOT Truck Parking 2026-2027 Continual Learning for Predicting Truck Parking Availability<\/span>
Sponsor: WSDOT
WSDOT Technical Monitor: Matt Neeley<\/a>
WSDOT Project Coordinator: David Strich<\/a>
Scheduled completion: July 2027<\/p>\n","protected":false},"excerpt":{"rendered":"