SYNCHROMODE

Context

Transport plays a vital role in the EU society and the economy: ten million people are employed in mobility-related positions, accounting for 5% of the GDP, and effective transport systems are essential for European companies to increase their competitiveness in the global economy and impose a strong impact on people’s quality of life. 

The technological advances (including automation and electrification) and the new modes and schemes of transport and mobility (e.g., CAVs and micro-mobility) are generating a revolution in mobility, transport network, and traffic management. Peoples’ mobility and the transport of goods are expected to continuously increase dramatically, which may cause a substantial pressure on the existing traffic infrastructure, further increasing air pollution and traffic jams. Traffic congestion costs in Europe are already over EUR 100 billion, 1% of GDP each year. In 2018, 28% of total EU-28 greenhouse gas emissions came from the transport sector. 

Even though transport network management has also benefited from the latest technological advances, current traffic and transport management solutions pertain to local, or limited to small areas, and traffic management strategies are based on aggregated variables (e.g., total flows, average speeds). This allows to deploy solutions that seek a compromise in terms of efficiency but cannot address the heterogeneity and variety of the mobility needs.

The project SYNCHROMODE

SYNCHROMODE aims to develop a data driven ICT toolbox for improving the management of transport operations from a multimodal perspective, in order to manage the transport network as a whole. SYNCHROMODE will provide transport managers with new predictive and network optimization capabilities for balancing the transport supply and demand, enabling the efficient reaction to different types of events. The project will demonstrate via well-chosen case studies the effectiveness of integrated multimodal and multi-actor traffic and transport management solutions and the SYNCHROMODE toolbox, able to balance the demand load of both people and goods and at the same time reduce individual journey times.

Goals

The main goal of the SYNCHROMODE project is to develop solutions for a more collaborative, multimodal and efficient transport system. For that, the specific project objectives are: 

• To develop advanced multi-actor cooperation models for multimodal mobility service operation, network and traffic management. 
• To develop a set of new interoperable solutions for data gathering, harmonisation, fusion and analysis.
• To perform simulations for assessing the impacts of the provision of multimodal traffic management strategies utilising connected vehicles technologies and services, capable of reacting to various events disrupting the transport network; (iv) to develop new artificial intelligence methods and tools, for network-wide multimodal transport, able to optimise the coordination of passengers and freight transport, network load balancing with the use of new traffic management capabilities, the synchronisation of shared/on-demand and public transport, and optimised response plans for bottlenecks and events management.
• To integrate models, algorithms and tools in the SYNCHROMODE toolbox, for an efficient multimodal traffic management framework applied to various environments and addressing mobility users & stakeholders’ needs.
• To test and validate the SYNCHROMODE toolbox, and evaluate the impact of multimodal traffic management strategies to passenger and freight mobility patterns and to provide insights to system-related benefits.
• To develop a framework guiding through replication capabilities for innovative multimodal traffic management in Europe, relying on interoperability and scalability capabilities of the developed services and the SYNCHROMODE toolbox.

Nommon’s role

Nommon leads most of SYNCHROMODE work directly related with data analysis and fusion, especially regarding the analysis and reconstruction of mobility patterns with data fusion and machine learning (ML) techniques and the identification of bottlenecks and disruptions in multimodal networks with sensor, FCD and other data. 

In addition, Nommon is the leader of the SYNCHROMODE Madrid case study, which focuses on the development of simulated multimodal strategic and operational solutions for the coordination of fixed public transport and demand-responsive transport (DRT) both for passenger transport and parcel delivery demand provision. These solutions focus on providing more efficient, sustainable and flexible public transportation options, especially in rural and peri-urban areas, by adding DRT and combining passenger trips with logistic deliveries. To address the use cases of Madrid, Nommon will: 

• Analyse parcel delivery agent mobility patterns and fuse them with other data sources in order to characterise the total parcel delivery demand  in the Madrid region.
• Develop ML models to predict DRT and public transport passenger demand in urban and peri-urban areas.
• Work alongside other partners to find the areas best-suited to be served by new DRT services (strategic view) and to find the optimal DRT routes for some predicted passenger and parcel request demand combination in each case (operational view).