Hybrid Approach for Clustering Vehicle Classification Data to Support Regional Implementation of the Mechanistic–Empirical Pavement Design Guide

Abstract

This paper develops a hybrid approach for analyzing vehicle classification data and applies the approach to a fused data set from multiple jurisdictions in the Canadian prairie region. Application of the approach results in a set of regional default truck traffic classification groups for use in the Mechanistic–Empirical Pavement Design Guide. The hybrid approach is a conglomeration of three components: statistical clustering procedures, expert judgment, and industry intelligence. By applying the hybrid approach, analysts receive the joint benefits of analytical rigor and industry-oriented pragmatism. Application of this approach results in eight truck traffic classification groups for the Canadian prairie region that exhibit distinct differences from the default distributions developed for national use in the United States. The benefits of applying the hybrid approach on fused data sets include (a) the statistical strength gained from use of additional classification data, (b) the development of truck traffic classification groups that better reflect the diversity of patterns in a region, and (c) the potential for improved ability to capture future shifts in truck traffic characteristics because of experience gained in other jurisdictions. The paper also identifies limitations to the hybrid approach that should be considered. These limitations include varying data quality between jurisdictions, the sensitivity of low-volume sites to changes in industry patterns and the ability to track these changes, and potential shortages of continuous classification sites. When its benefits and limitations are well understood, the hybrid approach can be applied to truck traffic data analyses in any jurisdiction.

Issues and Options for Oversize/Overweight Permitting of Petroleum-Related Trucks in a Performance-Based Regulatory Context: The Manitoba Experience

“…Figure 4 illustrates the capability of these data by showing the vehicle class distributions (VCDs) obtained from four 48-hour classification sites near the Pierson oilfield, adjacent to the Saskatchewan and North Dakota borders. The distributions shown are unique to oilfield activity in Manitoba, Saskatchewan, and Alberta, as evident by the high percent of class 10 trucks (Reimer and Regehr 2014).…”

Framework for Characterizing Truck Traffic Related to Petroleum Well Development and Production in Unconventional Shale Plays

“…From a freight demand modeling perspective, inclusion of these data sources is not novel as they provide the fundamental inputs for the components of the modeling process. However, from a truck traffic monitoring perspective, explicit integration of these nontraditional data sets has not been emphasized, despite general recognition that better information about industry-related patterns and trends supports more robust monitoring practices and better data interpretation (18). Therefore, the framework offers a structured way of relating the two processes, which ultimately have a common objective.…”

“…The bottom graph shows the VCD of a provincial highway in Manitoba that is a primary corridor in the petroleum-producing region. There is no continuous classification equipment along this route; however, the VCD reflects typical oil-related truck traffic classification distribu-tions in which Class 10 vehicles make up the bulk of the fleet mix (18). The truck traffic along this corridor would also be influenced by other local industries, particularly agriculture.…”

Clustering Approach to Generate Pedestrian Traffic Pattern Groups

“…31 (2) Typically, cluster analysis has been used as a method to characterize temporal traffic patterns. For example, cluster analysis has different applications: to characterize truck flows [10]- [13] or traffic patterns [14], to classify roads according to their use [15], or to identify unusual patterns or nonrecurrent events [16], [17]. Additionally, [18] characterized the stations of a public bicycle system according to entrance and exit.…”