Tradeable Mobility Credits: Addressing Ethical Concerns with Algorithm Transparency

Tradable Mobility Credits (TMC) have the potential to reduce carbon emissions from the transport sector by aligning transport choices with environmental objectives. Nevertheless, the implementation of TMC systems raises concerns about tracking individuals’ mobility and the processing of personal data by using AI to adjust and personalize prices. Users might be unaware of their potential impact on pricing, which poses ethical concerns regarding their decision autonomy, (data) security, and fairness of outcomes. The project builds on recent advances in choice architecture research, innovation economics, and traffic engineering to contribute new insights into the ethical aspects of TMC systems and investigate its ethical aspects and mediate the role of trust as a result of algorithm transparency. The researchers will conduct incentivized choice experiments to investigate whether disclosing tracking requirements and algorithmic transparency affect users’ acceptance and usage of TMC. The project will further clarify whether algorithm disclosure affects transport mode choices. Moreover, signpost experiments will be used to study users’ reactions to the disclosure of heterogeneity in initial TMC budgets, pricing, and underlying AI algorithms.

News & Updates

Principal Investigators

Prof. Dr. Klaus Bogenberger, TUM School of Engineering and Design, Chair for Traffic Engineering and Control

Dr. Allister Loder, TUM School of Engineering and Design, Chair for Traffic Engineering and Control

Prof. Dr. Hanna Hottenrott, TUM School of Management, Professorship for Economics of Innovation

Prof. Dr. Christoph Ungemach, TUM School of Management, Chair for Marketing