Effects of heavy vehicles on dynamic traffic features.

Ahn, Soyoung; Noyce, David A.; Chen, Danjue; Bang, Soohyuk · 2016 · ROSA P / National Center for Freight and Infrastructure Research and Education (U.S.)

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Summary

This study investigates the impact of heavy vehicles (HVs) on dynamic traffic patterns, specifically focusing on bottleneck capacity drop and stop-and-go oscillations. Motivated by growing highway congestion in freight hubs, the research aims to characterize HV car-following (CF) and lane-changing (LC) behaviors at the individual vehicle level to improve traffic control strategies and freight reliability. The researchers utilized high-resolution trajectory data from the Next Generation Simulation (NGSIM) dataset collected on Interstate 80. They calibrated three established CF models—Newell’s, Gipps’, and the Intelligent Driver Model (IDM)—using a genetic algorithm to assess their effectiveness in describing HV behavior. The study analyzed three CF combinations: HV-following-passenger car (HV-PC), passenger car-following-HV (PC-HV), and passenger car-following-passenger car (PC-PC). Additionally, empirical analyses of LC behavior around HVs were conducted, and simulations were performed to evaluate HV impacts in rubbernecking and uphill bottleneck scenarios. The calibration results indicated that Newell’s model was superior for HV analysis because its parameters were insensitive to time resolution and possessed clear physical meanings, whereas IDM and Gipps’ models showed high sensitivity and performance deterioration with increased time resolution. Empirical analysis revealed distinct behavioral differences: PC-HV pairs exhibited the largest time gaps, while HV-PC pairs demonstrated a significant dampening effect on stop-and-go disturbances due to HVs’ convex or non-increasing reaction patterns. HVs also discouraged other vehicles from lane-changing behind them, which favored traffic stability but reduced roadway utilization. Simulations showed that in rubbernecking bottlenecks, HVs reduced the formation of traffic oscillations and increased normalized bottleneck discharge flow. Conversely, in uphill segments, restrained acceleration caused significant discharge flow reductions, with effects being more profound for HVs than passenger cars. The findings suggest that HVs play a complex role in traffic dynamics, simultaneously stabilizing flow by dampening oscillations and discouraging lane changes, while potentially reducing throughput due to larger spatial gaps and mechanical limitations on grades. The study concludes that understanding these individual-level behaviors is critical for developing effective traffic controls and integrating emerging technologies like connected vehicles to improve highway operations and freight efficiency.

Key finding

Heavy vehicle-following-passenger car pairs dampened stop-and-go oscillations, which increased bottleneck discharge flow in rubbernecking scenarios but was less effective in mitigating flow reductions on uphill grades.

Methodology

dataset

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• traffic density
• following distance