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TU Berlin

Inhalt des Dokuments

Master thesis: Evaluate MATSim results using TomTom-LiveTraffic data as ground truth (Compensated 20h/week)


Mega Cities and growing urban areas face a growing risk of daily traffic collapse. To ensure individual mobility and improve the life quality in urban areas, an advanced prescriptive traffic management is needed. The latter has to accurately predict the impact of traffic policies and optimize the traffic flow in cities. Here we focus on the first crucial step, the accurate prediction of traffic, which has a huge potential to improve routing and builds the foundation of any prescriptive traffic management.

We envision to combine the expertise in the domain of traffic models - provided by Prof. Kai Nagel and his group - with the capability to measure traffic with a high precision - provided by TomTom with its award-winning LiveTraffic service. The traffic model is based on the very successful open-source framework MATSim which allows to model traffic on macroscopic scales using an agent-based (microscopic) approach. The main goal of the master thesis is to evaluate MATSim speed predictions using TomTom-LiveTraffic data as ground truth. Furthermore, it will be investigated how TomTom data can be fed into MATSim simulations to improve the prediction.

Figure 1
a) TomTom Live feed Berlin; providing a detailed view on the current traffic situation.
b) MatSim simulation output Berlin.

Ansprechpartner: Gunnar Berghäuser

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