@incollection{M{\"u}nstDamerMeieretal.2024,
  author    = {M{\"u}nst, Philipp and Damer, Lara and Meier, Selina and Graef, Marcel and Voßwinkel, Rick},
  title     = {Pipeline for Modeling Urban Traffic Density as the Data Basis for Micrologistics and Autonomous Delivery Robots: Project MoVMi},
  booktitle = {Emerging Cutting-Edge Applied Research and Development in Intelligent Traffic and Transportation Systems : Proceedings of the 8th International Conference on Intelligent Traffic and Transportation (ICITT), Incorporating the 8th International Conference on Communication and Network Technology (ICCNT), Florence, Italy, 16-18 September 2024},
  editor    = {Shafik, Mahmoud},
  publisher = {IOS Press},
  address   = {Amsterdam},
  isbn      = {9781643685601},
  issn      = {2352-751X},
  doi       = {10.3233/ATDE241210},
  institution = {Kraftfahrzeugtechnik},
  series    = {Advances in Transdisciplinary Engineering},
  number    = {63},
  pages     = {360 -- 369},
  year      = {2024},
  abstract  = {This paper presents a framework for modeling urban traffic density to support micrologistics using automated guided vehicles (AGV), more specifically autonomous delivery robots (ADR). The project MoVMi integrates survey data, pedestrian simulations using SUMO, and AGV interaction modeling in CARLA to optimize last-mile delivery in urban environments. Our approach addresses challenges such as congestion and access restrictions, and balances routing efficiency with delivery time windows. The framework's adaptability allows application in various cities globally, enhancing urban freight transportation and sustainability. Future work will refine models with real-time data and extend applicability to diverse urban settings.},
  language  = {en}
}