How can AMOD serve Winnipeg's aging population?
Agent-Based Modelling of Older Adult Needs for Autonomous Mobility-on-Demand: A Case Study in Winnipeg, Canada
October 16, 2024
https://arxiv.org/pdf/2410.11416This paper explores how agent-based modeling (ABM) can be used to design a demand-responsive transportation service for elderly populations using autonomous vehicles (AMoD). Researchers built a detailed simulation of Winnipeg, Canada, modeling individual citizens as "agents" with unique characteristics and travel needs, especially focusing on the elderly.
Key points for LLM-based multi-agent systems:
- Individualized Agent Behavior: The ABM simulates individual agents with diverse needs and adapts their behavior to the transportation environment, showcasing the potential of LLMs to drive individual agent decisions in a complex system.
- Scalability and Real-World Data: The model uses real-world data (census, open street maps, etc.) to simulate a large-scale urban environment, demonstrating the feasibility of applying LLM-based multi-agent systems to complex real-world problems.
- Emergent Phenomena: The simulation reveals emergent phenomena like induced demand, where the introduction of AMoD changes overall travel patterns. LLMs could be instrumental in understanding and predicting such complex system-level outcomes.
- Service Optimization: The research highlights the impact of fleet size and service design on AMoD effectiveness, suggesting that LLMs could play a crucial role in optimizing multi-agent systems in real-time based on evolving demand and user behavior.