OPTIMUM project
The project consortium consists of 14 partners from 8 countries across Europe (Belgium, UK, Austria, Portugal, Greece, Slovenia, Serbia and Hungary).
OPTIMUM is working to unveil state-of-the-art information technology solutions to improve transit, freight transportation and traffic connectivity throughout Europe in the area of big transportation data. Through tailor-made applications, OPTIMUM is striving to bring proactive and problem-free mobility to modern transport systems by introducing and promoting interoperability, adaptability and dynamicity.
The main objectives of OPTIMUM are:
- To capitalise on the benefits and potential of big data fusion and proactive behaviour in the context of diverse and multimodal transportation by designing a distributed and scalable architecture;
- To enable comprehensive observations of the transport ecosystem by designing and developing a smart sensing system able to cope with huge amounts of heterogeneous data in real time;
- To enable semantic understanding of acquired data and predict the status of transport networks for short- and medium-term horizons by designing and developing an efficient management framework for dynamic (proactive) and context-aware forecasting and the detection of situations of interest on the basis of complex and predictive data analysis algorithms and event detection;
- To realise sustainable transportation behaviours through system-aware optimisation mechanisms that integrate adaptive charging and crediting models and real-time multimodal routing and navigation algorithms;
- To support proactive decisions and sustainable transportation behaviours through proactive information provisioning and personalisation;
- To deploy proposed solutions in real-life pilots to place challenging use cases in the domain of the proactive improvement of transport system quality and efficiency — such as proactive charging for freight transport and Car2X communication integration; and
- To enable the provision of suitable business models for the commercialization of results beyond selected end-user pilots to ensure the impact of the OPTIMUM approach.
Figure 1: OPTIMUM’s conceptual architecture. OPTIMUM follows a cognitive approach based on the Observe, Orient, Decide, Act loop of the big data supply chain for continuous situational awareness. OPTIMUM's goals are achieved by incorporating and advancing state of the art in transport and traffic modelling, travel behaviour analysis, sentiment analysis, big data processing, predictive analysis and real-time event-based processing, persuasive technologies and proactive recommenders. The proposed solution is deployed in real-life pilots in order to realise challenging use cases in the domains of proactive improvement of transport systems quality and efficiency, proactive charging for freight transport and Car2X communication integration.
OPTIMUM Impact for ICCS / NTUA
For ICCS/NTUA (and the Information Management Unit (IMU) that participates in the project), OPTIMUM has provided and supported:
- The opportunity to conduct research to a new, rapidly developing area of smart, green and integrated transport. More specifically, IMU:
- Designs the OPTIMUM information personalization and recommendation algorithms and implements them in services that filter and select appropriate information to be displayed to the user pre-, on- and post-trip, addressing the requirements of each phase.
- Investigates how to extract context from the OPTIMUM system by leveraging information from various sources and sensors and how to aggregate and utilize the context information in personalization and recommendation processes.
- Designs and implements personalized persuasive strategies with the aim to nudge users towards selecting environmentally friendly transportation options.
- The research of two experienced, postdoctoral researchers (E. Bothos, B. Magoutas)
- The doctoral research of PhD student (E. Anagnostopoulou)
- The publication of original conference and journal papers.
- New partnerships with some of the leading organizations worldwide who develop intelligent transportation technology including Kapsch A.G. and Intrasoft International.
Publications (indicative)
1. Anagnostopoulou, E., Bothos, E., Magoutas, B., Schrammel, J., & Mentzas, G. (2016). Persuasive Technologies for Sustainable Urban Mobility. Presented at the 11th International Conference on Persuasive Technology Workshop "Where are we bound for? Persuasion in Transport Applications".
2. Anagnostopoulou, E. (2016). Personalized persuasion for sustainable mobility. Doctoral Consortium of the 11th International Conference on Persuasive Technology.