Level: Master Thesis
Emerging Technologies for Data-Driven Network Effects within Digitalized Urban Infrastructures and towards Autonomous Driving Applications
Mobility is changing. Technological innovations introduced to the market, the digitalization of infrastructures and services, or social challenges such as the COVID-19 pandemic are influencing the way we understand and experience mobility. By providing novel services like MaaS and carpooling, autonomous vehicles are set to take the centre stage for new mobility. Given this development, even more disruptive technologies and use cases will emerge. V2X connectivity and smart infrastructure leverage services in the area of multimodal transport, traffic, maps & navigation, parking, safety and payment. Those innovations create room for novel HMI solutions, new mobility solution providers and many other potential actors.
The DAI-Lab is researching and developing solutions that could meet the requirements of an cooperative, connected and automated mobility landscape (CCAM). An essential focus is to understand the role and effects that appear from data collected in digitalized infrastructures and autonomous vehicles. These are linked to mobility services offered in these environments.
Given the concept of Platform Economy (PE), it is very interesting to investigate data-driven network effects (DDNE). DDNE occurs when a product improves significantly by shared data generated by its users, and is often enhanced by AI technologies. This thesis’ target is to conduct research on such effects in the context of PE in CCAM use cases.
Main Research Focus
- Conduct literature research and create an overview on possible interplay of cooperative and connected autonomous mobility framework (CCAM) and platform economy (PE) approaches.
- Choose several related use cases, identify their relevant stakeholders and visualise the interconnectivity between all instances.
- Analyse the impact of chosen use cases in terms of data-driven network effects (DDNE) and develop a framework/tool that provides answers to the following questions:
- What are DDNE in the context of digitalized urban infrastructures and autonomous driving?
- How can digitised urban infrastructure enrich the data landscape qualitatively?
- What properties do the different actors and entities show (autonomous vehicle, pedestrians, cyclists, Road-Side-Units, etc.)?
- Given the use cases, what data is needed, what data is helpful? How can different data be gathered and prioritized for the given use cases?
- What challenges occur in the context of gathering the data? How can they be solved?
- What role does data security regulation and customer’s demand in Germany/EU play? How could developments in this domain inhibit or amplify DDNE?
- Conclude with a discussion on benefits and disadvantages of possible future scenarios.
- General knowledge on state-of-the-art autonomous mobility solutions and the platform economy concept.
- Preferably successfully completed university courses in the area of platform economy.
- High motivation of discovering novel use cases within the autonomous mobility framework and DDNE.
- Good grades in relevant fields are beneficial.
- Diginet-PS Project
- Quantifying the direct network effect for online platforms supporting industrial symbiosis: an agent-based simulation study
- Banned from the sharing economy: an agent-based model of a peer-to-peer marketplace for consumer goods and services
- Evaluating the systemic effects of automated mobility-on-demand services via large-scale agent-based simulation of auto-dependent prototype cities
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We are looking forward to receiving your application. Please include your current transcript of records and Curriculum vitae in tabular form; all documents in PDF format.