TP4.2: Eco-Sensitive Traffic Management

Subproject manager
Prof. Dr. Fritz Busch
Subproject manager
Dr. Antonios Tsakarestos
Nihan Celikkaya

Air pollutants, greenhouse gases and noise are three road transportation related emissions that must be reduced due to their direct effects on health and their regional/global impacts on the environment. While air pollutants cause several health problems (e.g. irritations, respiratory or cardiovascular problems and cancer), greenhouse gases cause regional and global problems (e.g. extreme weather conditions, water or food shortages and climate change) [1]. In addition, high noise emissions, which are often ignored, cause health problems such as high blood pressure, sleeping disorders and cardiovascular disease [2].

There are several methods and measures to reduce road transportation related emissions covering different policy fields including planning, regulations, vehicle technologies and traffic operation. One of the policy instruments that focuses on reducing air pollutant emissions is eco-sensitive traffic management (ETM). In Europe, NOx and PM10 are the two major air pollutants to which road transport majorly contribute [3]. Although the average air pollutant emission levels have been decreasing in the last decades, due to new standards and regulations in Europe, the limits defined by European Air Quality Standards and World Health Organization are often exceeded in central urban areas with high traffic volumes and/or congestion (i.e. hotspots) (Figure 1). ETM is a dynamic traffic management application where specific measures are activated due to current and/or projected high air pollution levels for a specific area and for a defined time period [4].

Connected Mobility Ecosystem Explorer
Figure 1: Motivation [5]

Intensive discussions about environmental management of urban traffic began after the second world war with the increase in population as well as car ownership and initially started as planning of access restrictions for certain areas [6]. In time with increasing traffic volumes, shifted importance from safety to environmental issues, increasing awareness and stricter emission regulations static measures became increasingly important and together with the development of intelligent transport systems, it became possible to apply complementary dynamic measures. The state of the art analysis that focused on studies and applications conducted in the last decades in Germany showed that emission generation is mostly influenced by traffic volumes and compositions, although there are several external effects (wind, weather, radiation, building structure,…etc.) that can affect measured emission levels. It also showed that the quality and effectiveness of ETM systems are remarkably affected by the availability of data, aggregation levels and user acceptance [7].

The main objective of the sub-project 4.2 is to develop innovative traffic management scenarios and technologies which are adapted dynamically according to the emission levels in order to reduce road transport related emissions in urban areas. Within this scope, it is important to contribute to the state of the art in eco-sensitive traffic management. Corresponding sub-goals are listed below:
• Enhancement of data availability, to improve the accuracy of emission level assessment and projection,
• Integration of electric vehicles (EVs), which generate zero local exhaust emissions and less noise at low speeds (e.g. in urban areas) into ETM systems and related traffic management measures,
• Consideration of the reduction potential of noise and greenhouse gas emissions in ETM Systems,
• Assessment of the impacts of the increasing share of EVs in traffic composition on emission reduction, as well as evaluation of the possible effects of EV related ETM measures on promotion of electric mobility.
Connected Mobility Ecosystem Explorer
Figure 2: New components to be integrated in ETM

The main working steps of the project are in line with the generic approach of the eco-sensitive traffic management. However, in accordance with the listed objectives, two new major components will be integrated in ETM systems (Figure 2). New emission detection technologies will be used for data collection, model development and calibration. On the other hand, electric vehicles will be taken into account in traffic and emission estimations as well as measure development. Landshuter Allee and its surrounding area is selected for the use case due to high emission levels and existence of already installed measurement stations.

The subproject is currently in the data collection and model building process. If you would like to get more information about this subproject, please contact Nihan Celikkaya (

[1] IPCC (2014). Climate Change 2014: Synthesis Report: Contribution of Working Groups I,II and III to Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Geneva.
[2] WHO (2011). Burden of Disease from Environmental Noise – Quantification of Healthy Life Years Lost in Europe. Copenhagen: World Health Organization.
[3] Dora, C., Jamie, H., Pierpaolo, M., & Elaine, F. (2011). Urban Transport and Health: Revised October 2009. Sustainable Transport: A sourcebook for policymakers in developing cities. Eschborn: GIZ
[4] FGSV (2014). Wirkung von Maßnahmen zur Umweltbelastung Teil 3: Umweltsensitives Verkehrsmanagement (UVM), Zwischenstand. FGSV Forschungsgesellschaft für Straßen und Verkehrswesen.
[5] Own Figure adapted from Lutz, M. stated in Air Quality Plan of City of Munich, 2004
[6] McKee, W.A. & Mattingly, M.J. Transportation (1977) 6:365. Environmental Traffic Management — The End of the Road?
[7] Celikkaya, N., Papapanagiotou, E., Busch, F., Use Case: Eco-Sensitive Traffic Management (2016) In State of the Art Report, TUM Living Lab Connected Mobility (pp.172-186).