Short description: Routing applications for public transit and cars consider road users as “machines”. Sometimes this approach is transferred to routing applications for bicyclists and pedestrians. In doing so, the personal abilities and preferences (which usually play a role for motorized road users) are largely neglected. Common routing applications optimize routes for average bicyclists and pedestrians. However, this average user doesn’t exist and the range of preferences is huge (compare a bike courier with a child on a bicycle for instance). In this master thesis research models and routing environments should be developed that account for individual preferences of users and have the ability to adapt to specific situations (e.g. heavy rain). The identification of a suitable approach (multi-criteria routing, model-based impedance manipulation, consideration of user feedback etc.) is subject to research.
References, suggested reading:
- PRIEDHORSKY, R., PITCHFORD, D., SEN, S. & TERVEEN, L. 2012. Recommending routes in the context of bicycling: algorithms, evaluation, and the value of personalization. ACM 2012 conference on Computer Supported Cooperative Work. Seattle, Washington, USA: ACM.
Prerequisites/qualifications: Skills in data management and analysis (especially network analysis) as well as in scripting/programming are required.