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Ontario’s Reduced Load Period (RLP) Onset and Removal Prediction Model


In the spring, the frost formed in the pavement subsurface structure starts thawing and pavement becomes weaker. Heavy loads on the weakened roads can cause substantial damage and lead to pavement life reduction or road failure. To ensure the integrity of roadway structures during spring-thaw season, the Ontario Ministry of Transportation (MTO) and municipalities in Ontario enforces reduced load restriction on certain provincial highways and municipal roads in according with the Highway Traffic Act.

Currently, most municipalities implemented a fixed-date approach for the reduced load period (RLP). However, concerns have been raised by municipalities and the trucking industry that this fixed RLP does not accurately reflect the actual spring-thaw condition. In an effort to reduce economic red tape and hardship for the trucking industry and to support the municipalities in protecting their road infrastructure, the MTO propose a calibrated predictive approach for determining the start and end dates of the RLP. This predictive approach utilizes representative weather data and the response of pavement structure.

Based on assessment of the RLP protocols from MTO and neighboring agencies, the MTO suggests dividing the province into four RLP zones and employing the Cumulative Thawing Index (CTI) method to forecast the start and removal dates of the RLP. This paper outlines the rationale behind the proposed methodology, which involves utilizing field measurement such as subsurface temperature, moisture content, borehole data, and pavement deflection to establish CTI thresholds for each specific zone’s start and removal dates. This paper also highlights the calibration, verification, recommendations, and the subsequent steps necessary for implementing the proposed RLP management solution, which seeks to strike a balance between the requirements of trucking industry and the objectives of road agencies.

Conference Paper Details

Session title:
Innovations in Pavement Management, Engineering and Technologies
Leung, Yuen-Ting Fiona
Liu, Youjia
Chan, Susanne
Lee, Stephen
Asset management