Project Description

Driving2Driverless addresses the system management challenges of a future mobility with shared electric automated vehicles. The project will pursue the creation of methods that allow managing the mobility system at an urban and inter-urban scale using automated vehicles which are shared and are powered by electricity. Driving2Driverless assumes this scenario and envisions the algorithms needed for: reaching a system optimum distribution of traffic flows at a macro level (urban and regional level); power the system with electricity for all trips extension (local or regional); locating parking capacity; and compare a network of direct door to door connections with a hierarchical network (hub and spoke) with need for transfers. These are challenges that the transport system will be facing in a medium to long term as full automated cars and shared mobility penetrate the market. However the project’s objectives are still valid for non-automated vehicles since sharing is already happening with normal vehicles or with taxis, some of them electric, thus the project should produce meaningful results for the shorter term as well.

The project intends to unify the research that is being done independently on methods for locating electric charging stations, the routing of automated vehicles, transport network modeling and parking capacity planning. These sub-components of the mobility system are traditionally modeled taking the other sub-components as static ones. Optimization and simulation methods are used to analyze these sub-systems taking key aspects as given (eg. routing without looking at power needs, shared automated vehicles without looking at where they will park). Each subsystem operator is searching to optimize its network but afterward these solutions must be tested in a realistic setup which will be done through an agent-based simulation model. Performance is observed from different stakeholders perspectives: generalized cost of traveling for the population; the financial performances of the operators; and society (pollution and equity factors). A negotiation between the conflicting objectives of the different stakeholders must take place considering the overarching performance of the system. The methodology will be applied and tested in the centro region of Portugal focused on the mobility system of its two major cities: Coimbra and Aveiro.

Driving2driverless methodological approach, integrating optimization, simulation and cost-benefit analysis, will allow studying the mobility management of shared electric automated vehicles by providing an estimation of the positive and negative impacts that this system entails when compared to the current multi-modal mobility where private cars and public transport play a major role. The results of the project should be useful not just for the long-term but for a near future as well where shared vehicles are representing a more significant share of mobility.

Research Team

CITTA

• Gonçalo Homem de Almeida Rodriguez Correia (coordinator)
• António Pais Antunes (co-coordinator)
• Anabela Ribeiro

CMTA

• Margarida Coelho
• 1 Researcher with a PhD to hire
• 1 Grant-holder with a MSc

Financial Support

• POCI-01-0145-FEDER-31923

Stage of Progress

• Concluded