Effects of traffic signal coordination on noise and air pollutant emissions

  • Authors:
  • B. De Coensel;A. Can;B. Degraeuwe;I. De Vlieger;D. Botteldooren

  • Affiliations:
  • Ghent University, Department of Information Technology, Acoustics Research Group, St.-Pietersnieuwstraat 41, B-9000 Ghent, Belgium;Ghent University, Department of Information Technology, Acoustics Research Group, St.-Pietersnieuwstraat 41, B-9000 Ghent, Belgium;Flemish Institute for Technological Research (VITO), Boeretang, B-2400 Mol, Belgium;Flemish Institute for Technological Research (VITO), Boeretang, B-2400 Mol, Belgium;Ghent University, Department of Information Technology, Acoustics Research Group, St.-Pietersnieuwstraat 41, B-9000 Ghent, Belgium

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Traffic management solutions are increasingly called for to address problems of transport and mobility. In particular, coordinated traffic lights that create green waves along major arterials are an increasingly used strategy to reduce travel times. Although it is usually assumed that an improved traffic flow will result in lower vehicle emissions, little scientific research has been spent on the effects of synchronized traffic lights on emissions. Moreover, because changes in traffic flow do not necessarily influence travel times, noise and air quality in the same way, there is a clear need for a combined approach. This paper reports on a computational study in which a microscopic traffic simulation model (Paramics) is combined with submodels for the emission of noise (Imagine) and air pollutants (VERSIT+). Through the simulation of a range of scenarios, the model is used to investigate the influence of traffic intensity, signal coordination schemes and signal parameters on the noise, carbon dioxide, nitrogen oxides and particulate matter emissions along an arterial road equiped with a series of traffic lights. It was found that the introduction of a green wave could potentially lower the emissions of the considered air pollutants by 10%-40% in the most favorable conditions, depending on traffic flow and signal timing settings. Sound pressure levels were found to decrease by up to 1 dB(A) near the traffic signals, but to increase by up to 1.5 dB(A) in between intersections. Traffic intensity and green split were found to have the largest influence on emissions, while the cycle time did not have a significant influence on emissions.