The Future of Smart Fleet Planning
Planning the right vehicles at the right place and right time is one of the key topics in the mobility industry. As a global premium service provider and innovation leader in the mobility sector, SIXT pursues a consistent digitalization strategy that encompasses both its product portfolio and sales channels as well as its operational business processes. New data-driven approaches and data science based solutions incl. use of AI provide enormous potential for the comprehensive optimization of fleet planning process.
#SustainableFleetPlanning #FleetOptimization #DataDrivenFleet
✅ Completed 🏁 Winner Congratulations to A.S. & Eol Robotics!
🏆 Prize Prize pool of EUR 5,000 + funding and collaboration programs + joint paper
🌎 Scope International - open to participants from all over the world
Submission Template
For the participation within the AI Innovation program, a common submission template is available. This template will help you to structure your ideas and approaches and to find answers to all relevant questions. The submission template is mandatory to submit.
In addition to this submission template, you will find specific requirements and guiding questions for your use case in the "Guiding Questions" section down below. You can also complement your submission with prototypes, pitch decks, image and video materials, higher-level concepts, or specific use case-related instruments – simply submit these documents along with the submission template via our platform.
Guiding Questions
This challenge is calling for the most innovative digital solutions or use cases of existing digital solutions that address the challenge of optimal organization of the car fleet planning
The following guiding questions are for your inspiration, and it is not mandatory to answer all of them.
- What are the most relevant factors for driving unconstrained demand in the vehicle rental industry?
- What are the most suitable approaches to calculate unconstrained demand forecasts taking into consideration uncertainties?
- Which factors influence demand elasticity and to which extent?
- What are suitable elasticity models?
- Which algorithms and AI approaches can be used to plan the fleet optimal considering certain business constraints?
- How does an optimal fleet planning powered by AI-driven and dara science solution look like?
Please state in your submission on which of the Steps 1-3 mentioned in Tab “Brief” you want to focus.