RIDE2RAIL
Travel Companion enhancements and RIDE-sharing services synchronised to RAIL and Public Transport
Facilitating the efficient combination of ride-sharing and scheduled transport services such as bus and rail.
Vision.
To utilise intelligent mobility technologies to make ride sharing an effective feeder for high-capacity transport services (such as rail) in areas with limited population and rural locations. The results will be to shift existing demand from individual to collective mobility and eventually attract new demand, so improving transport accessibility and limiting "disutilities" for users.
The challenge.
According to several studies, the average car occupancy rate for commuting trips in EU countries is roughly 1.1 people per vehicle. At the same time, whether there are one or four persons in one car, the implications on traffic congestion, energy consumption, and environmental impacts are the same.
Ride sharing, on the other hand, has the ability to reduce the number of single occupancy vehicles. Even with current smartphone technologies enabling this mode of transportation, ride sharing has undergone limited acceptance thus far. This is caused by a number of challenges, including a lack of awareness of available services, a lack of trust and willingness to ride with strangers, the need for scheduling flexibility to allow for and cope with changes in plans, and uncertainty in reaching agreements on cost sharing.
Energy Consumption
Environmental Impacts
Ride Sharing Limitations
Approach & solutions.
To address this challenge, RIDE2RAIL created a framework for intelligent mobility that integrates and harmonises real-time and diverse information about rail, public transportation, ride-sharing, and crowdsourcing in a social ecosystem, allowing users to compare and choose between multiple options/services classified by a set of criteria - including environmental impact, travel time, comfort, and cost - based on their preferences; this makes the travel experience more positive for both individuals and businesses.
Specifically, the project aimed at:
- encouraging carpooling (and ride sharing acceptance) as complementary for public transport.
- enhancing the performance of the overall mobility system, reducing road congestion and environmental impact, reinforcing the mobility offer in rural and low-demand areas.
- combining travel offer classifications and software components, integrating them into existing collective and on-demand transport services.
- introducing high-capacity services with simple multimodal and integrated travel planning, booking, ticketing, and payment features.
The project combines diverse (public/private/social) data sets and existing transportation platforms in order to promote effective ride sharing among citizens that can serve as a complementary transport mode that extends public transportation networks.
Ride2Rail leverages Blockchain technology to address existing issues with trust between drivers and passengers.
Because traditional rating systems frequently do not depict the truth, the project introduced the use of Distributed Ledger Technology (DLT), specifically
Blockchain technology,
to create a safe and 'honest' service with bilateral 'contracts/agreements' being formed between the driver and the passengers.
Pilots
Real commuters and users will use the solutions provided by RIDE2RAIL at these demo sites.
RIDE2RAIL has designed, created, and tested a set of software components for the IP4 ecosystem, including an enhanced Travel Companion and a crowd-sourced Transport Service Provider, in four real-world demos in both urban and rural settings.
The project has delivered a set of validated proof of concept and business cases imagining future mobility scenarios in four (4) diverse European cities: Padua, Athens, Brno, and Helsinki, where advanced transport solutions were seamlessly integrated into existing collective transport services (rail and others).
Our role.
Inlecom Innovation drives the activities that relate to the design and the development of the Ride-Sharing Agreements Ledger Module.
This project has received funding from the Shift2Rail Joint Undertaking under the European Union's Horizon Europe research and innovation programme under GA 881825. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the granting authority can be held responsible for them.
