Agent-based Framework for Self-Organization of Collective and Autonomous Shuttle Fleets

TL;DR

This paper introduces an agent-based simulation framework to explore how autonomous vehicle fleets can self-organize within multi-modal urban transit systems, aiding city planning for sustainable mobility.

Contribution

It presents a novel agent-based framework for simulating autonomous vehicle fleet self-organization in urban mobility scenarios, validated with real city data.

Findings

Framework enables scenario testing of AV fleet integration

Supports decentralized control for autonomous fleet coordination

Validated with data from the city of Trento

Abstract

The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This paper proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.