Forecast for traffic characteristics
The modelling of cause-and-effect relations in passenger and commercial transport is of vital significance for transport planning, administration and politics.
On satellite images, in regions with high levels of shipping, you can find long, low-lying clouds, which are clearly not natural in origin. Known as 'ship tracks', these are the result of emissions from ships.
DLR (CC-BY 3.0).
Travel assistance with modern information and communication technologies
With the increasing provision of traffic information through modern information and communication technologies such as PDAs, smartphones, mobile phones and the Internet, individual transport users will in future be able to travel more flexibly, more rapidly and more comfortably in their chosen mode of transport.
The objective is to analytically fill the existing lack of a complete modelling and process chain from traffic demand and traffic flow to the effects of transport and make them predictable. Beyond the actual scientific contribution, decision-makers are supported in evaluating traffic development and the effectiveness and efficiency of possible measures. In this context, DLR researchers working in this programme topic focus on the following five main tasks:
Analysis: Causes of Transport Demand
The primary objective within this task is to expand empirical and analytical comprehension of the causes of demand in passenger and commercial transport. The investigation will also highlight changes and investigate options for influencing demand. Along with the traditional observation of actor-external factors, DLR’s approach increasingly centres on individual attitudes, preferences and lifestyles. Results and data from the analysis of transport-related human behaviour are included in the models of passenger travel and commercial transport demand. These models will allow the assessment of demand-related fiscal and regulatory measures and also technological and organisational innovations.
Modelling: Transport Development
In addition to simulating cause-effect relationships in passenger and commercial transport, this research topic combines new and existing data to analyse and evaluate the transport system at a regional, national and global level. For this purpose, DLR's researchers will expand their microscopic travel demand model and combine it with macroscopic models, enabling unique, large-scale transport demand modelling to be performed. DLR's existing freight transport demand model will be extended with modules for service-related transport. Worldwide freight flows will be recorded and integrated into these models, especially in the air cargo sector. Based on global supply, demand, and framework data, the extent and structure of traffic and its spatial and time distribution will be identified, as well as the transport modes used.
Environmental Effects: Noise and Emissions
The objectives of this research topic include predicting traffic noise and evaluating its effect on human beings, developing geographically distributed emissions registers and scenarios and evaluating traffic emissions with regard to their climate relevance. A comprehensive understanding of the atmospheric processes in proximity to sources will be developed and measurement systems for a simplified description of the environmental impact of traffic will be devised. Contrary to the previous, primarily sectoral analyses, DLR researchers are pursuing an integrated approach on the prognosis for traffic noise and its cumulative effect. This approach will include a description of source, sound propagation in the inhomogeneous atmosphere over structured topography, as well as population and traffic density. With the help of descriptors, noise effects will be quantified and conclusions drawn to determine noise-reducing measures. The emission of important trace substances and precursor substances for local, regional and global emission distributions will be modelled. DLR's investigators will simulate changes in the atmosphere resulting from traffic emissions and the subsequent climate effects with a climate-chemistry aerosol model. A large part of the necessary atmospheric data will be collected by DLR with its own aircraft and satellites. The derivation of measured values for comparing various courses of action and their effects completes the work.
Scenarios: Measures and Technologies
DLR's researchers will identify innovative measures to implement a sustainable transport system. The specific focus will be on the parameters of passenger vehicle purchasing choices, the determining factors of the travel and transport behaviour of private and commercial actors, and possibilities for increasing intermodality. In addition, new vehicle concepts will be evaluated. By means of vehicle technology scenarios, investigators will be assessing the potential effects associated with the use of competing vehicle technologies and fuel alternatives in terms of energy, environmental and climate objectives. Finally, the questions of how efficient multi-mode traffic behaviour can be supported by suitable information and how traffic control potentials can be evaluated through traffic information will be addressed. Based on an analysis of the effects of conventional and innovative types of traffic information, the research team will make recommendations for their use in traffic management. These will include a differentiated examination of medium and long-term behavioural changes. Intermodal information and its effects on dynamic choices of transport mode will be one focus of the investigations.
Integration and Knowledge Transfer: Integrated Transport-Environment Model
At the end of the current research program in 2013, the necessary components for an overall model of the transport system will have been developed and integrated into a holistic transport-environment model. It will then be possible to evaluate the effect of transport-related measures by means of parameters and to process the modelling results into a user-friendly format. Combining various transport and environmental models will allow the drawing of local, regional and global conclusions. Based on specific parameters, changes in actors' transport decisions brought about by external effects will be described.
Last modified:15/06/2011 10:46:59