Onboard perspective on context-aware travel support for disturbances in public transport

Onboard perspective on context-aware travel support for disturbances in public transport

In most public transport systems today, travel planner applications play an important role in providing travellers with vital information about available travel times and routes. However, during a journey, the initial conditions might change, either for personal reasons or non-personal reasons (e.g. due to public transport disturbances), forcing the traveller to change the original plan. The new plan should take the new conditions, the current location of the traveller (e.g. on-board a vehicle or at a station), and any special needs or preferences of the traveller, into account. The purpose of this project has been to explore how future travel planners can make use of new types of information related to traveller needs/preferences and context, to improve this replanning process for travellers. Such information may be generated by IoT-based systems, or derive from travellers interacting with their travel planners. The particular focus of this project has concerned the situation when a traveller with specific needs/preferences is travelling with a public transport vehicle and has to replan the continued journey (e.g. due to disturbances). Public transport networks are often considered as complex and difficult to navigate by these traveller groups. Moreover, many people lack a sense of personal control, especially in case of disturbances. A context-aware and personalized travel planner may reduce these drawbacks and enhance the accessibility of the transport network. Furthermore, by making the travel planner aware of the traveller context, a more proactive travel plan can be obtained. For instance, many of the travel planners used today enable the user to search for travel routes originating from their current position. The system determines the traveller’s current position by using GPS. However, with information about, for instance, which particular vehicle the traveller is currently riding on, the travel planner would be able to list all route alternatives originating from the vehicle stops ahead, to the traveller’s final destination, and recommend the user the best option(s). This might be very valuable in case of disturbances.

The results from the project show how information about the traveller’s context can be used to enhance the support provided by travel planners. In particular, a specification of what types of context information are relevant and which travel planner tasks they support, is included. Furthermore, the results also show that several concrete scenarios can be identified, where context-aware travel planners would provide useful travel support during unplanned disturbances, for instance, by suggesting alternative travel routes that are not displayed by the travel planners available on the market today. The potentials, requirements, and risks associated with the travel support suggested in these scenarios were also identified; including, risks connected to traveller privacy and uncertainties of the PTS. Finally, the results show that there are several technologies proposed in literature that may be used for retrieving information about the two traveller context information subtypes: knowing the relative distance to a particular public transport stop (e.g., being at or close to a station) and knowing on which public transport vehicle the traveller currently is.

In summary, the project provides support for the analysis and development of context-aware travel planners by addressing the information and tasks that need to be performed during unplanned disturbances. In relation to previous research, the project contributes with knowledge of how travel planners and micro navigators can be enhanced using information about the traveller’s context. Thereby, the travel support provided can be more personalized, and can include individually adapted suggestions for alternative routes, taking the real-time effects of public transport disturbances into account. These results might be used to increase the attractiveness of public transportation.

Malmö Universitet
350 000 kr

Publikationer kopplade till projektet

Potentials of Context-Aware Travel Support during Unplanned Public Transport Disturbances

Åse Jevinger, Jan Persson, Sustainability 2019, 11(6)