Agent Based Multi-Purpose Autonomous Vehicles Simulation

Publication

Simulating Multi-Purpose Autonomous Vehicles: Shared Mobility between People and Goods in Kendall Square, GAMA Days 2022 Presentation Slides: https://www.figma.com/proto/wjzRv3QPleUfdm0NiADYeG/Mobility_Final-Presentation Github Repo: https://github.com/LeeJAJA/GAMA_MPAV_Mobility

Demo: Daxing Airport Region Simulation

Abstract

According to a study by Morgan Stanley, the transport sector is heavily reliant on fossil fuels, accounting for 45% of global oil demand. However, autonomous vehicles(AVs) offer significant environmental benefits in fuel usage, as noted by the Southwest Research Institute study claiming that AVs can lead to as much as a 20% improvement in fuel consumption. Hence, the goal of the GAMA 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. In conclusion, we have developed a simulation tool modeling a traffic system with MPAVs and taken Kendall square as a case study. The findings of our study provide a methodology to investigate different traffic scenarios and to assist the government forecast the size of deployment of new shared mobility services for passengers and packages. Besides, the simulation tool also allows for testing various transportation policy designs, such as strategies for rebalancing fleets and for distributing charging stations. Multi-Purpose Autonomous Vehicle (MPAV) Modeling

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