MODELLING HETEROGENEOUS TRAFFIC FLOW ON UPGRADES OF INTERCITY ROADS

Arasan, Venkatachalam Thamizh; Arkatkar, Shriniwas Shrikant · 2010 · Crossref

DOI: 10.3846/transport.2010.16

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Summary

This study addresses the challenge of modeling heterogeneous traffic flow on intercity road upgrades in developing countries, specifically India. Unlike homogeneous traffic in developed nations, Indian traffic comprises a mix of vehicles with vastly different physical dimensions, weights, and dynamic characteristics, such as buses, trucks, cars, and two-wheelers. The authors note that existing traffic flow models are largely based on homogeneous conditions or focus solely on heavy trucks, failing to capture the complex interactions and varying speed reductions experienced by different vehicle types on grades. The research aims to quantify how upgrade magnitude and length affect traffic flow characteristics and to develop speed–distance profiles for various vehicle categories under these heterogeneous conditions. To achieve this, the researchers utilized HETEROSIM, a micro-simulation model designed for heterogeneous traffic. The study involved field data collection from three stretches of National Highway No. 4 near Pune, India, featuring uniform gradients of 3%, 3.78%, and 5%. The model was calibrated and validated using observed data, including free speeds, vehicle dimensions, and lateral clearances. Acceleration rates for different vehicle categories were estimated using a force balance equation that accounts for rolling resistance, air resistance, grade resistance, and inertial forces, incorporating parameters like power-to-weight ratios and aerodynamic drag coefficients. The validation process compared simulated speeds against observed speeds at fixed intervals along a 5% upgrade, using statistical paired t-tests to confirm the model's accuracy. The results demonstrated that the HETEROSIM model accurately replicates field observations, with no significant statistical difference between simulated and observed mean speeds. The analysis revealed that acceleration rates vary significantly by vehicle type and speed range; for instance, heavy vehicles like buses and trucks exhibited negative acceleration rates (deceleration) at speeds above 40 km/h on a 5% grade, whereas lighter vehicles like cars and motorized three-wheelers maintained positive acceleration. The study further applied the validated model to simulate traffic flow on upgrades ranging from 2% to 6% using a representative traffic composition. This allowed for the development of speed–volume relationships and speed–distance profiles, illustrating how vehicle performance degrades as grade magnitude increases. The significance of this work lies in providing a robust tool for analyzing heterogeneous traffic on grades, a scenario previously lacking comprehensive modeling resources. By accounting for the specific dynamic characteristics of mixed vehicle fleets, the study offers more accurate predictions of traffic flow and vehicle performance on upgrades than traditional homogeneous models. These findings are critical for the planning, design, and operation of roadway systems in developing countries, enabling engineers to better understand the impact of road geometry on diverse traffic compositions and to design infrastructure that accommodates the varying capabilities of different vehicle types.

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• traffic density