Assessing the Environmental Performances of Urban Roundabouts Using the VSP Methodology and AIMSUN

Acuto, Francesco; Coelho, Margarida C.; Fernandes, Paulo; Giuffrè, Tullio; Macioszek, Elżbieta; Granà, Anna · 2022 · OpenAlex-citations

DOI: 10.3390/en15041371

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study addresses the need for accurate, microscale environmental assessments of urban road infrastructure, specifically focusing on roundabouts. As urban mobility shifts toward sustainability, there is a growing requirement to evaluate the environmental impact of specific road designs and operational changes. Traditional emission models often rely on average speeds or macroscopic data, which fail to capture the second-by-second variations in vehicle behavior—such as acceleration, deceleration, and idling—that significantly influence pollutant emissions. The authors aim to bridge this gap by developing an empirically based methodology that integrates the Vehicle-Specific Power (VSP) model with microscopic traffic simulation software (AIMSUN). The primary research question investigates whether fine-tuning simulation parameters using real-world trajectory data can improve the accuracy of emission estimates at urban roundabouts. The methodology involved a pilot study of six roundabouts in Palermo, Italy. Field data were collected using a "crowdsensing" approach, where a sentinel vehicle equipped with a smartphone recorded second-by-second GPS trajectories, including speed and acceleration profiles. This real-world data served as the baseline for calibrating the AIMSUN microsimulation model. The researchers adjusted vehicle attributes and driver behavior parameters in the simulation to ensure that the generated speed-time profiles closely matched the field-observed trajectories. Once calibrated, the simulated trajectories were used to calculate VSP modes, which were then applied to estimate second-by-second emissions. To validate the reproducibility of the procedure, the study also simulated the conversion of one existing roundabout into a turbo-roundabout design, comparing the environmental performance of the two configurations. The results demonstrated that the integrated approach effectively captures the complex driving dynamics at roundabouts, providing more accurate emission estimates than traditional average-speed models. The calibration process revealed that adjusting simulation parameters based on field data significantly enhanced the model's ability to replicate realistic traffic behavior, particularly regarding acceleration and deceleration events. The analysis highlighted that emission rates are heavily influenced by the specific geometric design of the roundabout and the resulting driver behavior, such as the frequency of stops and speed changes. The comparison between the conventional and turbo-roundabout designs provided insights into how geometric modifications affect environmental performance, confirming the methodology's utility for evaluating alternative infrastructure designs. The significance of this work lies in its contribution to sustainable urban mobility planning. By combining crowdsourced data collection with microsimulation, the study offers a cost-effective and scalable tool for assessing the environmental impact of road infrastructure at a granular level. This approach allows planners to evaluate the trade-offs between safety, capacity, and emissions for specific road units, supporting the development of greener road networks. Furthermore, the study underscores the potential of digital technologies and mobile sensing in creating "smart" infrastructure systems that can monitor and optimize traffic emissions in real-time. The findings support the integration of such methodologies into broader traffic management strategies, enabling more precise environmental assessments for future urban transport projects.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• exposure measurement