CAPE
  • Posted at Dec 4, 2025
  • Graduation Thesis
  • Enschede
  • Internship

Improve logistic efficiency and fleet management using a real-time AI support system, utilizing vehicle data, predict and mitigate delays in truck deliveries

This research aims to develop a real-time decision support system for transportation that predicts potential delays in truck deliveries. By analyzing (vehicle) data, a predictive model (based, for example, on machine learning techniques) can identify if a truck will miss its estimated time of arrival (ETA) due to mandatory breaks, unexpected breakdowns or other events. The system will generate solutions, such as rerouting or dispatching assistance, to enhance logistics efficiency and improve fleet management.\

Interested in this assignment? Feel free to contact us at jessie.ensing@cape.nl and include your resume. You can also contact us if you want more information regarding the assignment.
Graduating at CAPE means receiving one-on-one guidance from one of our experienced consultants. Many graduates have gone before you! Additionally, a compensation of €550 per month is provided.

Proficiency in Dutch is required.