Increasing mobility demands raise the pressure on existing transport networks. As the most used mode of transport, private cars have a particularly strong environmental impact and produce congestion. Ridesharing or carpooling, where a driver and several riders form a carpool, can help to address these issues by increasing the number of persons per car. Therefore, recent years have seen a strong interest in carpooling. However, there exists no effective method of integrating carpooling into transport trip planners as of now, mainly due to the fuzzy and flexible nature e.g., no fixed stops, possibility of making detours of carpooling. This hinders the acceptance of carpooling by the general public. This paper proposes a new method to merge public transport and carpooling networks for multimodal route planning, considering the fuzziness and flexibility brought by carpooling. It is based on the concept of drive-time areas and points of action. The evaluation with real-world data sets shows that, compared with the state-of-the-art method, the proposed method merges static i.e., public transport and dynamic/fuzzy i.e., carpooling networks better, while retaining the desired flexibility offered by the latter, and thus creates a higher interconnectivity between the networks. Meanwhile, the merged network enables multimodal route planning, which can provide users with trips from an origin to a destination using different combinations of modes.

The present urban transportation system, mostly tailored for cars, has long shown its limitations. In many urban areas, public transportation and soft mobility would be able to effectively satisfy many travel needs. However, they tend to be neglected, due to a deep-rooted car dependency. How can we encourage people to make sustainable mobility choices, reducing car use and the related CO ${}_2$ emissions and energy consumption? Taking advantage of the wide availability of smartphone devices, we designed GoEco!, a smartphone application exploiting automatic mobility tracking, eco-feedback, social comparison and gamification elements to persuade individual modal change. We tested the effectiveness of GoEco! in two regions of Switzerland (Cantons Ticino and Zurich), in a large-scale, one year long randomized controlled trial. Notwithstanding a large drop-out rate experienced throughout the experiment, GoEco! was observed to produce a statistically significant impact (a decrease in CO ${}_2$ emissions and energy consumption per kilometer) for systematic routes in highly car-dependent urban areas, such as the Canton Ticino. In Zurich, instead, where high quality public transport is already available, no statistically significant effects were found. In this paper we present the GoEco! experiment and discuss its results and the lessons learnt, highlighting practical difficulties in performing randomized controlled trials in the field of mobility and providing recommendations for future research.

How can we encourage people to make sustainable mobility choices, reducing car dependency and the related CO ${}_2$ emissions and energy consumption? Taking advantage of the wide availability of smartphone devices, we designed GoEco!, an application (app) exploiting automatic mobility tracking, eco-feedback, social comparison and gamification elements to persuade individuals to change their mode of transport. The app features and contents are grounded in the transtheoretical model for behaviour change and were designed to avoid over-reliance on “one-size-fits-all”, simplistic point-based systems. The GoEco! app was designed in a user centred approach and was field-tested in Switzerland in a three-month experiment involving around 150 voluntary users. In this paper, we present the app’s features and comment on their evaluation from the perspective of the field-testers. The insights we collected through an online questionnaire and individual interviews allowed us to develop recommendations for similar persuasive apps and to identify open challenges for the future. In particular, we recommend to endow such apps with multi-modal travel planning components and features evoking the feeling of belonging to a community, that provide support and helping relationships.