Initial work focused on current state of the art analysis, elicitation of user requirements and formalisation of use cases to describe the functionality of the platform leading to the development of the OPTIMUM conceptual model and technical architecture which based on the outcomes of the first pilot trials was refined to facilitate requirements for faster information exchange among components.
The developed architecture guided the modelling and implementation of all R&D activities structured into 4 layers. For Observe layer, a working data infrastructure constituting a single point of access for all data was built. The initial data architecture was enhanced and fine-tuned to integrate all necessary data operators for automated retrieval of the ITS-sensor and multimodal information from distributed data sources allowing for the harmonisation and enrichment of the data sources.
Travel demand and forecasting models were developed and fine-tuned in terms of predictive accuracy and execution efficiency as part of the Orient layer while a complex event processing engine was designed, developed, integrated in the information flow, validated and fine-tuned.
For Decide layer, a dynamic charging model was developed and fine-tuned calculating the discount for any given road section containing a specific toll. The multimodal routing algorithm was also enhanced and fine-tuned to integrate the feedback received, increase accuracy and integrate additional querying parameters.
The (Pro-)Act layer involved development of the OPTIMUM user model and a range of information personalisation and persuasive recommendation services. These services were also enhanced and fine-tuned to integrate the feedback received, increase accuracy and deliver more personalised recommendations.
All components were integrated together as part of OPTIMUM applications used as part of the two rounds of the pilots during the project lifecycle.
The overall dissemination strategy was applied and the targets were reached engaging the specified audience. OPTIMUM engaged key stakeholders such as decision makers, technology experts, researchers, policy makers and potential users and will further liaise with already existing clusters on the field even after the project end.
The exploitation methodology was successfully defined and the consortium identified the business models that could be employed for the commercialisation of OPTIMUM.
