Research

Due to increasing population in metropolitan areas, intelligent planning and control of urban mobility and freight transportation is becoming more important. Traditionally, research in the area of city logistics has investigated the trade-off between efficiency and reliability of urban deliveries. Extending well-known city logistics approaches, the Management Science Group focuses on the preparation and aggregation of large databases for dynamic and stochastic methods of transportation planning and control, e.g., optimal path-finding and vehicle routing. We follow a wholistic approach stretching from data collection via data aggregation with data mining to extended approaches of applied operations research. We are also interested in better planning and control of mobility and transportation services such as car and bike sharing services.

Considering Complex Customer Preferences in Multimodal Travel Itineraries

Easier access for travelers to a variety of individual mobility services via mobility applications and the integration of innovative means of transport have led to an increase in multimodal travel behavior in recent years. In this context, the combination of different transportation services within a certain period of time (mostly one week), or in particular within one trip, is referred to as multimodal mobility. In this research project, optimization approaches are developed which take complex individual customer preferences into account when orchestrating travel itineraries. In particular, the identification of a diversified and adequate amount of different travel itineraries under consideration of individual customer preferences will be discussed.

Potentials of Automated Transport Systems

Joint project with Jarmo Haferkamp and Rico Kötschau

The technical progress on self-driving and connected vehicles is expected to lead to a significant change in the realization and organization of passenger and freight transportation. Aims of the project are: (1) to derive requirements for self-driving vehicles, (2) to estimate and evaluate their impact on transportation systems as well as environment and safety, (3) and to develop visions of future behavioral and organizational forms caused by self-driving vehicles.

A key aspect in achieving these aims is the development and investigation of solution approaches for the strategic and operational planning problems of self-driving and connected car based services.