Search

Although road surface friction is considered the most effective performance measure for maintenance operations, it is not commonly used due to the high cost of collection. As a result, most jurisdictions use subjective visual indicators that qualitatively describe the state of the road surface, even though they create measurement inconsistencies and offer less detailed maintenance tracking. For maintenance personnel to transition into using friction, the collection cost must be reduced. This paper attempts to do so by proposing a low-cost, machine learning-based method for predicting road surface friction using dash camera imagery and demonstrates its feasibility through a case study. The dataset used for this project was collected in the City of Edmonton, AB, Canada during its 2021/2022 winter season. Three models were developed using tree-based algorithms, where all three displayed high performance with an average root mean squared error of 0.0796 or 79.3% accuracy based on RMSPE. [ABSTRACT FROM AUTHOR]

Speed limits are a common traffic regulation for balancing traffic mobility and safety on roadways. Speed transition zones bear complicated driver behaviours. However, driver behaviours are even more complex when speed transition zones are dynamically created and shifted by variable speed limits (VSLs). Much existing research has estimated long-term driver compliance, evaluated effectiveness of speed enforcement, and attempted to involve compliance into VSL control algorithms. Whereas, limited research provides convincing solutions for representing speed limit effect and estimating real-time driver compliance at speed transition zones. To fill this research gap, this paper analyses field data from two speed transition zones along southbound of 97th Street, Edmonton, Canada. Temporal and spatial variations of speed and driver compliance are investigated in detail using statistical tests. A linear regression is then established to rank the contributions of the selected factors. Finally, some suggestions and guidelines for VSL algorithm design and implementation are proposed. [ABSTRACT FROM AUTHOR]