Macroscopic modeling and control of emission in urban road traffic networks

AbstractThis work suggests a framework for modeling the traffic emissions in urban road traffic networks that are described by the Network Fundamental Diagram (NFD) concept. Traffic emission is formalized in finite spatiotemporal windows as a function of aggregated traffic variables, i.e. Total Travel Distances (TTDs) in the network and network average speed. The framework is extended for the size of an urban network during a signal cycle – the size of a window in which the network aggregated parameters are modeled in the NFD concept. Simulations have been carried out for model accuracy analysis, using the microscopic Versit + Micro model as reference. By applying the macroscopic emission model function and the traffic modeling relationships, the control objective for pollution reduction has also been formalized. Basically, multi-criteria control design has been introduced for two criteria: maximization of the TTD and minimization of traffic emissions within the network.

[1]  R. Smokers,et al.  A new modelling approach for road traffic emissions : VERSIT+ , 2007 .

[2]  Carlos F. Daganzo,et al.  Urban Gridlock: Macroscopic Modeling and Mitigation Approaches , 2007 .

[3]  Serge P. Hoogendoorn,et al.  The effect of signal settings on the macroscopic fundamental diagram and its applicability in traffic signal driven perimeter control strategies , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[4]  Livia Mannini,et al.  Within-Day Dynamic Estimation of Pollutant Emissions: A Procedure for Wide Urban Network , 2012 .

[5]  István Varga,et al.  A simple dynamic model for the dispersion of motorway traffic emission , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[6]  W R Blunden,et al.  On the theory of traffic flow , 1962 .

[7]  Shigeru Shimamoto,et al.  An Open Traffic Light Control Model for Reducing Vehicles' $\hbox{CO}_{2}$ Emissions Based on ETC Vehicles , 2012, IEEE Transactions on Vehicular Technology.

[8]  D. Sun,et al.  Comparison and optimization of cordon and area pricings for managing travel demand , 2014 .

[9]  István Varga,et al.  Development of road traffic control by using integrated VISSIM-MATLAB simulation environment , 2012 .

[10]  Bart De Schutter,et al.  Integrated urban traffic control for the reduction of travel delays and emissions , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[11]  Gábor Szendrő.  Congestion charging in Budapest - A comparison with existing systems , 2011 .

[12]  Stefan Hausberger,et al.  Road vehicle emission factors development: A review , 2013 .

[13]  Cameron Kergaye,et al.  Environmental Benefits of Adaptive Traffic Control System: Assessment of Fuel Consumption and Vehicular Emissions , 2012 .

[14]  Csaba Csiszár,et al.  Information system for road infrastructure booking , 2011 .

[15]  Zoltán Bokor.  Calculation model for transport costing , 2011 .

[16]  Zhongyi Zuo,et al.  Analysis of Traffic Conflict Characteristic at Temporary Reversible Lane , 2014 .

[17]  Peter Wagner,et al.  Analysis of Traffic Flow Characteristics on Signalized Arterials , 2004 .

[18]  István Varga,et al.  Real-time Modeling and Control Objective Analysis of Motorway Emissions , 2012 .

[19]  Markos Papageorgiou,et al.  Urban congestion gating control based on reduced operational network fundamental diagrams , 2013 .

[20]  Markos Papageorgiou,et al.  Perimeter Traffic Control via Remote Feedback Gating , 2014 .