Authors: G. Hiermann, M. Schiffer

Published on: April 30, 2024

Impact Score: 7.6

Arxiv code: Arxiv:2405.00230

Summary

• What is new: An algorithmic framework designed to handle large-scale pickup and delivery problems for autonomous mobility-on-demand services, capable of processing over 20 thousand requests.
• Why this is important: Overloaded transportation systems in cities, with existing solutions limiting in scope or overlooking key problem characteristics.
• What the research proposes: A comprehensive framework that integrates request pooling with vehicle-to-request dispatching for efficient operations of autonomous mobility-on-demand services.
• Results: Showcases significant improvements in fleet sizing and customer delay acceptance, validated by computational studies and benchmarks.

Technical Details

Technological frameworks used: Algorithmic framework for large-scale pickup and delivery routing problems

Models used: Integrated request pooling and vehicle-to-request dispatch models

Data used: Benchmark instances from literature and new large-scale instance data

Potential Impact

Transportation and delivery services, automotive manufacturers developing autonomous vehicles, urban mobility planning organizations

Want to implement this idea in a business?

We have generated a startup concept here: FleetOptiMo.