Many modern vehicles continuously track location and performance data such as speed and acceleration. Collecting large amounts of this data to use in machine learning models has many potential applications, including aggregating and evaluating road pavement conditions. This project investigated the feasibility of using large amounts of onboard data from electric vehicles to monitor and assess pavement conditions comprehensively and cost-effectively across a large network.
Continue reading Using Onboard Vehicle Data to Assess Pavement QualityTag Archives: pavement conditions
Optimizing Pavement Network Maintenance
Maintaining Minnesota’s 14,000 miles of pavement is challenging, especially with the growth in traffic volume resulting in system needs that exceed available funding. New ways to characterize pavement conditions and methodologies to determine the optimal maintenance schedule for individual road segments will allow planners to optimize resources while providing the highest possible ride quality across the pavement network.
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Investigating Pavement Segments With Long-Term Poor Ratings
Researchers investigated pavement segments within MnDOT’s pavement management system that had received a poor ride quality level rating for more than five years. Their investigations showed that for most segments, the true pavement conditions differed from listed ratings due to the pavement segments’ unique characteristics.
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Crossroads 