Abstract
This paper investigates the effectiveness of traffic management tools, including traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project.
Highlights
This paper assesses the impacts of traffic signal control and re-routing via Variable Message Signs on traffic congestion and CO2/Black Carbon (BC) emissions in a variety of realistic scenarios.CO2 is the primary greenhouse gas contributing to the recent climate change (United States Environmental Protection Agency USEPA 2013)
The results show that the impact of the Intelligent Transport Systems (ITS) actions varies depending on the spatial reference of the indicators: at network and corridor levels the combined ITS action Traffic Signal Control (TSC)-VMS10 seems to bring the highest benefits in terms of delay across all spatial Key Performance Indicators (KPIs) except at the junction
This paper presents the microsimulation results from the CARBOTRAF project, which aims to provide adaptive traffic management to reduce CO2 and black carbon emissions
Summary
This paper assesses the impacts of traffic signal control and re-routing via Variable Message Signs on traffic congestion and CO2/Black Carbon (BC) emissions in a variety of realistic scenarios. Significant research efforts have been dedicated to the assessment of the impact of traffic signal controls on emissions These studies tend to focus on different spatial references, namely isolated junctions, corridors and/or networks. Research on the junction level has been carried out to investigate the effect of cycle length on emissions (Li et al 2004), to identify the relationship between delay, number of stops and emissions (Li et al 2011) and to explore the impact of the optimization of phase ordering (Barnes and Paruchuri 2012) It has been shown in certain case studies that increasing green time to the subject approach reduces CO, HC and NOx emissions by up to 7.21, 4.54 and 2.63 %, respectively (Chen and Yu 2007). & Traffic perspective: travel time, vehicle speed, and delay;1 & Environmental perspective: black carbon, CO2, and NOx emissions These KPIs have been distinguished by different spatial references including junction, corridor, and network levels. The remainder of this section describes in detail the three core modules of the methodology of this study
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