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 work 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 autonomous vehicles using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento.
For a complete understanding we suggest to consult the file containing all the implemented algorithms, available at: https://github.com/Martins83/AutonomousVehicles/blob/master/CompleteAlgorithms.pdf
The IDE used for the development was GAMA 1.7. You can find a guide for the installation here.
The project is made by the two following directories:
- includes: original GIS data and GIS data after parsing.
- models: scripts to create a map that can be used in the system from raw GIS data, scripts for the decentralised simulation.
This study has been designed, developed, and reported by the following investigators:
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Antonio Bucchiarone - Fondazione Bruno Kessler (FBK, Trento - Italy)
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Martina De Sanctis - Gran Sasso Science Institute - GSSI, L'Aquila, Italy
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Annalisa Congiu - Univerità degli Studi di Trento - Trento, Italy
For any information, interested researchers can contact us by writing an email to [email protected].