Assessment of the impact of speed limit reduction and traffic signal coordination on vehicle emissions using an integrated approach

Madireddy, Madhava Rao; De Coensel, Bert; Can, Arnaud; Degraeuwe, Bart; Beusen, Bart; De Vlieger, I; Botteldooren, Dick · 2011 · OpenAlex-citations

DOI: 10.1016/j.trd.2011.06.001

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Summary

This study evaluates the environmental impact of two traffic management strategies—speed limit reduction and traffic signal coordination—on vehicle emissions of carbon dioxide (CO2) and nitrogen oxides (NOx). Motivated by the need to mitigate urban air pollution and greenhouse gas emissions caused by congestion and stop-and-go traffic, the research addresses the challenge of assessing these measures without relying on infeasible trial-and-error methods. The authors aim to quantify emission changes in a specific urban context to provide guidance for city planners. The methodology employs an integrated modeling approach combining the microscopic traffic simulation software Paramics with the VERSIT+ instantaneous emission model. The case study focuses on the Zurenborg district in Antwerp, Belgium, a residential area bounded by major arterials and a railway. The traffic network was constructed using GIS data and calibrated with morning rush-hour traffic counts and actual signal timings. The VERSIT+ model, validated against on-road measurements from four diesel vehicles, calculates emissions based on vehicle speed and acceleration profiles. The integrated model’s accuracy was further verified by comparing simulated emission distributions with measured data from instrumented vehicle trips along the N184 arterial road. The results demonstrate significant emission reductions for both interventions. Reducing speed limits from 50 km/h to 30 km/h in the residential zone led to smoother traffic flow, characterized by narrower speed distributions and fewer acceleration events. This measure resulted in total CO2 and NOx emission reductions of approximately 26.8% and 26.7%, respectively, driven by both traffic rerouting and improved driving dynamics. On the N184 arterial, the same speed reduction yielded emission decreases of roughly 10%. Regarding signal coordination, implementing a "green wave" scheme along the N184 reduced CO2 and NOx emissions by approximately 9.5% and 8.7% compared to a desynchronized scenario, confirming that coordinated signals promote smoother traffic flow and lower emissions. The study concludes that microscopic simulation coupled with instantaneous emission modeling is an effective tool for assessing the environmental benefits of traffic management. It reaffirms that lowering speed limits in residential areas offers substantial emission reductions alongside safety benefits. While signal coordination also reduces emissions, the authors note that the associated decrease in travel times may induce additional traffic in the long term, potentially offsetting environmental gains. These findings support the use of integrated modeling for urban planning decisions aimed at reducing vehicular pollution.

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• speed management