Multi-Purpose Autonomous Vehicles Simulation
Agent Based Multi-Purpose Autonomous Vehicles Simulation
Shared Mobility between People and Goods in Kendall Square, GAMA Days 2022
Demo: Daxing Airport Region Simulation
Abstract
The goal of this multi-agent simulation is to predict a low-carbon and efficient transportation system to shift the usage and reliance on high fossil fuel consuming vehicles to multi-purpose vehicles, to shape what an optimal transportation system in the future will look like. To accomplish this, we will introduce a Multi-Purpose Autonomous Vehicle (MPAV).
Based on a modular design strategy, the MPAV is able to do tasks such as cleaning waste and delivering commercial goods. For the simulation, we simplified it to carrying people and goods(parcels and food) with two capacities. stakeholders.
We choose Kendall Square as a representative site for the future entrepreneurship innovative city, for it gathered a large number of high-tech enterprises that generate huge demand for parcel and food delivery from companies and commuters. Through simulation, we hope to find a balance between existing transportation options, MPAVs, and potentially other future modes of transportation to meet the transportation demands of the people of Kendall Square.
Multi-Purpose Autonomous Vehicle (MPAV) Modeling
Agent-based Traffic Modeling
Experiments
Conclusions
- All MPAV based solutions save ~1000 kgCO2-eq even if theaverage travel time for vehicles increases by 1 min (5 min -> 6 min)
- All solutions involving MPAVs (except 1 MPAV) drastically reduce delivery times by ~1 hour
- Optimal solution based on the above and fleet cost is 5 miniMPAVs ($10k x 5 $50k)due to the small area of Kendall Square
Credits
Team: Chance Jiajie Li, Jin Gao, Ziyi Tang, Trent Tepool, Hiromu Ryan Rose Advisor: Naroa Coretti Sánchez, Maitane Iruretagoyena, Luis Alonso, Kent Larson