Benefits of Using Microscopic Models for Simulating Air Quality Management Measures

The raising of awareness about air pollution has brought about legislative regulations that force local administrations to keep the concentrations of certain pollutants under the formulated thresholds. A large variety of measures have been implemented to reduce road traffic’s emissions on the local level, but the observed results are not always satisfactory. For determining the effects of such measures a priori, a simulation system could be used. Because of the high variability of traffic management measures, such a system must be capable of replicating changes in traffic flow, the vehicle fleet, as well as user behavior, including modal shifts, as well as the interactions between these parts. Often, the effects of a measure can be found in a bigger region than the directly influenced one. Thus, the system must be able to simulate traffic in large, city-wide areas. This report emphasizes why the usage of microscopic models for this purpose makes sense nowadays. It introduces an exemplary system and presents some initial results.

[1]  Daniel Krajzewicz,et al.  Driving patterns reducing pollutant emission at traffic lights , 2015 .

[2]  S. Hausberger Emission Factors from the Model PHEM for the HBEFA Version 3 , 2009 .

[3]  Mark Bradley,et al.  Activity-Based Travel Demand Models: A Primer , 2014 .

[4]  Michael G. McNally,et al.  The Four Step Model , 2007 .

[5]  Daniel Krajzewicz,et al.  iTETRIS Deliverable 3.1 – Traffic Modelling: Environmental Factors , 2009 .

[6]  A. Schadschneider,et al.  Statistical physics of vehicular traffic and some related systems , 2000, cond-mat/0007053.

[7]  Christian Gawron,et al.  Simulation-Based Traffic Assignment. Computing user equilibria in large street networks , 1998 .

[8]  Eric J. Miller,et al.  Simulating the impacts of household travel on greenhouse gas emissions, urban air quality, and population exposure , 2011 .

[9]  Sascha Bauer,et al.  AIM – Application Platform Intelligent Mobility , 2009 .

[10]  Sergio Chiquetto The environmental impacts from the implementation of a pedestrianization scheme , 1997 .

[11]  Rita Cyganski,et al.  Demographic Effects on Passenger Transport Demand , 2011 .

[12]  Rita Cyganski,et al.  Decision-making by microscopic demand modeling: a case study , 2008 .

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

[14]  Kirk R. Smith,et al.  Global review of national ambient air quality standards for PM10 and SO2 (24 h) , 2011, Air Quality, Atmosphere & Health.

[15]  Tomer Toledo,et al.  Driving Behaviour: Models and Challenges , 2007 .

[16]  Daniel Krajzewicz,et al.  Comparing Performance and Quality of Traffic Assignments for Microscopic Simulation , 2010 .

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

[18]  Chang-i Hua,et al.  A Critical Review of the Development of the Gravity Model , 1979 .

[19]  Martin Treiber,et al.  Automatic and efficient driving strategies while approaching a traffic light , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[20]  J K Affum,et al.  Integrating air pollution modelling with scenario testing in road transport planning: the TRAEMS approach. , 2003, The Science of the total environment.

[21]  K. Nagel,et al.  Towards High-Resolution First-Best Air Pollution Tolls , 2016 .

[22]  Mario Krumnow,et al.  Second Generation of Pollutant Emission Models for SUMO , 2015 .

[23]  J. Fenger,et al.  Urban air quality , 1999 .

[24]  Daniel Krajzewicz,et al.  Großflächige Simulation von Verkehrsmanagementansätzen zur Reduktion von Schadstoffemissionen , 2014 .

[25]  Gemmer Marco,et al.  Air Quality Legislation and Standards in the European Union: Background, Status and Public Participation , 2013 .

[26]  R. Blokpoel,et al.  Micro-routing using accurate traffic predictions , 2012 .

[27]  Daniel Krajzewicz,et al.  Recent Development and Applications of SUMO - Simulation of Urban MObility , 2012 .

[28]  S. Stouffer Intervening opportunities: a theory relating mobility and distance , 1940 .

[29]  Antje von Schmidt,et al.  Applying Geovisualisation to Validate and Communicate Simulation Results of an Activity-based Travel Demand Model , 2015 .

[30]  Hong Zheng,et al.  A Primer for Agent-Based Simulation and Modeling in Transportation Applications , 2013 .

[31]  John P. Allen Urban Air Pollution in Megacities of the World , 1993 .

[32]  L. A. Pipes An Operational Analysis of Traffic Dynamics , 1953 .