Exploring Commercial Vehicle Detouring Patterns through the Application of Probe Trajectory Data

TL;DR

This study demonstrates that high-resolution probe trajectory data can effectively capture commercial vehicle detouring behaviors, validated through correlation with count stations, and applied to analyze detours related to enforcement, congestion, and incidents.

Contribution

The paper introduces a methodology using probe trajectory data to analyze commercial vehicle detouring patterns, validated with real-world data, and applied to multiple case scenarios.

Findings

Strong correlation (>0.75) between probe data and vehicle counts at VWS stations.

Probe data reliably captures CMV detouring behavior.

Application of method reveals detour patterns during enforcement and incidents.

Abstract

Understanding motorist detouring behavior is critical for both traffic operations and planning applications. However, measuring real-world detouring behavior is challenging due to the need to track the movement of individual vehicles. Recent developments in high-resolution vehicle trajectory data have enabled transportation professionals to observe real-world detouring behaviors without the need to install and maintain hardware such as license plate reading cameras. This paper investigates the feasibility of vehicle probe trajectory data to capture commercial motor vehicle (CMV) detouring behavior under three unique case studies. Before doing so, a validation analysis was conducted to investigate the ability of CMV probe trajectory data to represent overall CMV volumes at well-calibrated count stations near virtual weigh stations (VWS) in Maryland. The validation analysis showed strong positive correlations (above 0.75) at all VWS stations. Upon validating the data, a methodology was applied to assess CMV detour behaviors associated with CMV enforcement activities, congestion avoidance, and incident induced temporary road closures.