The capability to accurately and reliably estimate the traffic conditions during the snow events is of critical importance in improving the efficiency and effectiveness of the winter maintenance strategies at the Minnesota Department of Transportation. While the traffic flow data from the field detectors have been widely used for traffic operations, the research effort of applying traffic data to measure the performance levels of winter snow operations is still in its infancy. The literature search conducted in Phase 1 of this research has found out that the ‘Time to bare pavement’ is the most commonly used measure by the state DOTs for quantifying winter snow operations (1-5). However, it has been also noticed that no state DOT is directly applying traffic flow data to determine ‘the time to bare pavement’. To be sure, most state DOTs, at this point, are relying on the visual inspection of the field crew in determining the bare pavement recovery times, whose estimates can have the inherent limitations because of the subjectivity and the inconsistency of human-based measurements. Phase 1 of this research has studied the feasibility of applying traffic flow data by analyzing the variation process of the traffic speed and developing a prototype process to determine the speed-recovery times for given snow events was developed. The current research, Phase 2, expands this effort and develops a traffic-data based alternative measure that can be automatically estimated with the traffic flow data from the existing detectors on a freeway network. The main objectives of the current research include: • Analysis of the traffic flow patterns during snow events under normal and snow conditions, • Development of traffic data-based alternative measures and estimation process for snow maintenance operations. Example application of the estimation process to the entire corridors in the metro freeway network for the selected snow events. Chapter 2 collects the comprehensive data sets for two selected snow routes in the metro freeway network for both normal and snow conditions in 2012-14 winter seasons. The results from the comparative analysis of the collected data, focusing on the traffic flow patterns in the speed-density plane under different weather conditions, are also included in Chapter 2. Chapter 3 develops the traffic-data based alternative measures for snow operations. Further, the process to estimate those measures on the entire corridors in the metro freeway network is also developed and applied to the selected snow events in Chapter 3. Finally Chapter 4 presents the conclusions. (Author/publisher)
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