The pilot study will introduce new user services for individual travellers, including the following:
- Personalised trip and routing information, based on individual preferences and current physical and emotional states derived by observation services. The latter will be realised via the integration of social networking tools, natural language processing and sentiment analysis algorithms. For example, a Facebook post stating “Traveller X is now feeling tired” will affect the proposed trip option.
- Proactive services for personalised trips and re-routing based on personal plans, traffic information and historical data. In addition, users will be proactively informed about incidents in the transportation network and provided with alternative route suggestions.
- Trip optimisation for all travellers, taking into account the interaction between travellers within transportation systems with limited capacities.
- “C-tags” for cars, which can simultaneously generate savings and reduce CO2 emissions.
- Alternative services that may compensate for or minimise the need to travel. For example, a medium-distance business trip might be deferred or shortened if teleconference facilities are available nearby.
- Incentives for travellers that favour collective and sustainable means of transport. Such incentives may be of monetary, credit, or privileged service provision nature, and will be determined based on socioeconometric models to be developed as part of the project. For example, everyday private car users might be offered a guaranteed parking space if they opt to use a bus for “x” number of trips.
- Persuasive and proactive recommendations for collective trips. Certain trip types offer flexibility in terms of destination, and the OPTIMUM platform will evaluate this dynamic with the aim or relieving congested areas. For example, if a group of friends starting from different locations decide to go shopping in an area that is already heavily congested, the OPTIMUM platform will proactively suggest alternatives.
The OPTIMUM platform will collect information for public authorities and other transport operators that can improve policies and everyday decision making. For example, a transport operator can inform a bus driver to wait for a metro that is slightly behind schedule; or a shared bicycle can be reserved for a user who is about to miss the tram to her destination. Effects on overall transport systems will also be considered. For instance, a bus delay can severely disrupt subsequent connections: this might be addressed by providing proactive decision support, thereby enabling fully coordinated action to maximise route efficiency and minimise vehicle emissions. In short, city authorities will be able to plan and respond to predicted traffic flows in order to improve mobility and ease urban congestion.