Prof. Dr. Max Klimm
Humboldt Universität Berlin
Traffic and logistic networks are among the most vital infrastructures of modern civilization providing access to economic activities, work, health care, and social and cultural life. However, the huge benefits of private and commercial traffic are accompanied by severe burdens in terms of congestion, exhaust gas pollution and land consumption. In the past years, we witnessed the emergence of several new car-related technologies that have the potential to fundamentally change the way traffic networks are managed and used: navigation devices with real-time information allow each traffic participant to make an informed decision concerning the route choice; electrical and hybrid vehicles allow mobility with reduced carbon-dioxide footprint; car-to-car and car-to-infrastructure communications pave the way to a more coordinated traffic, ultimately culminating in the use of autonomous vehicles. The ubiquity of navigation devices and car communication today produces a wealth of data concerning the traffic demand, its elasticity, and the travel times, making these pieces of information available to the system designer. However, the mathematical theory of traffic equilibria typically assumes a fixed travel demand that is then distributed in the network according to the equilibrium concept in question. The restriction to a single demand matrix may be useful when modeling a particular traffic scenario (e.g. a rush hour situation). However, when designing the overall network or when installing road-pricing schemes that are active for a long time period it is much more sensible to analyze the overall performance of the system, i.e., to study the average travel with respect to the empirical distribution of travel demands over a given time span. This is the main question addressed in this project.