MACROSCOPIC MODELING AND CONTROL OF EMISSION IN URBAN ROAD TRAFFIC NETWORKS

Csikós, Alfréd; Tettamanti, Tamás; Varga, István · 2015 · Crossref

DOI: 10.3846/16484142.2015.1046137

archive: archived pipeline: cataloged verified

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Summary

This paper addresses the challenge of modeling and controlling vehicular emissions in urban road traffic networks, specifically within "Protected Networks" (PNs) designed to prevent congestion. While traditional traffic control methods focus on optimizing traffic flow metrics like Total Travel Distance (TTD), this work introduces a multi-criteria approach that simultaneously maximizes TTD and minimizes pollution. The study is motivated by the need to integrate environmental considerations into traffic management without requiring additional sensor infrastructure, relying instead on aggregated macroscopic variables derived from existing traffic data. The authors develop a macroscopic modeling framework based on the Network Fundamental Diagram (NFD) concept, which relates the total number of vehicles in a network to the average speed and total travel distance. The model formalizes traffic emissions as a function of two aggregated variables: Total Travel Distance (TTD) and network average speed. This approach extends previous microscopic emission models by treating emissions as a distributed parameter system dependent on macroscopic traffic states. The framework incorporates conservation laws, queue dynamics at perimeter gates, and actuator dynamics for traffic lights. To validate the model, the authors conducted simulations using the microscopic Versit+Micro simulator as a reference. The test network was modeled after a district in Budapest, featuring homogeneous traffic conditions and controlled entry/exit gates. The NFD and emission parameters were identified using simulation data representing various demand levels, including rush hours. The results demonstrate that the macroscopic emission model accurately predicts pollution levels when compared to microscopic simulations. The study identifies the Network Fundamental Diagram using a fourth-order polynomial fit and determines key parameters, such as the network exit rate and gate inflow ratios, through linear regression on simulation data. The analysis confirms that emissions can be effectively calculated using aggregated network parameters (TTD and average speed) rather than link-specific data. Furthermore, the paper formalizes a control objective for pollution reduction, showing that perimeter control strategies can be designed to optimize both traffic performance and environmental impact. The model assumes full information availability regarding traffic variables within the network. The significance of this work lies in providing a computationally efficient, macroscopic framework for emission-aware traffic control. By linking emissions directly to macroscopic traffic variables, the approach enables real-time control strategies that balance mobility and environmental goals. This is particularly relevant for urban centers where congestion leads to increased pollution. The study contributes to the field by extending the NFD concept to include environmental metrics, offering a practical tool for traffic engineers to design controllers that reduce emissions without compromising traffic flow efficiency. The findings support the use of perimeter control as an effective mechanism for managing both congestion and pollution in protected urban networks.

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• mental model of traffic