Solutions | amigos-project.eu

Blend of Digital and Non-Digital Solutions

Explore AMIGOS’s dynamic approach to urban mobility, blending non-digital and digital strategies. Dive into our co-creation activities, surveys, and the Fotefar app, all designed to promote sustainable travel behaviors and reshape city transit experiences.

NON DIGITAL SOLUTIONS

Co-creation activities

AMIGOS will develop a co-creation methodology for designing sustainable urban mobility solutions. The co-creation activities will use art- and game-based methods, allowing the participation of stakeholders from various backgrounds and geographical locations to express and model their lived and wished mobilities. The digital twins of city models will help them to better visualize and evaluate the urban mobilities toolboxes which pilot cities are willing to implement.

Stated-preference survey

A stated-preference survey will be developed and integrated in Fotefar application, aiming to gain a better understanding of users’ travel behaviour and the factors effecting it. The survey will evaluate users’ expected response to different mobility solutions (such as separated bike lanes and streetlights) aimed at encouraging users to adopt more sustainable and active travel alternatives (including public transport, walking and biking). Users’ response to different incentives will also be evaluated through the stated-preference survey towards the promotion of more sustainable and active mobility in cities.

DIGITAL SOLUTIONS

Fotefar mobile application

The Fotefar application, along with the integrated stated-preference survey, will gather mobility data in all AMIGOS living labs and SIAs to support city authorities in understanding travellers’ behaviour and expected response to various mobility solutions in their city. The app will be leveraged for understanding the factors that influence users’ mode choice and for identifying optimal ways to encourage travellers to use more sustainable and active modes.

Mobility observation box

The Mobility Observation Box (MOB) makes it possible to measure the safety of transport infrastructures according to objective criteria and thus make them comparable. Once data collection is done, machine learning algorithms automatically recognize different groups of road users (pedestrians, cyclists, cars, trucks, e-scooters, etc.), detects them, evaluates their traffic behavior using surrogate safety measures and provides a basis for targeted mitigation measures. The battery-operated system allows a quick and uncomplicated installation and deinstallation of the box, not requiring a supplemental power source. Due to its small size, data collection of all traffic participants can be realized without distraction or influence.

Big data platform

The Big data platform will be used for AMIGOS data storage and processing. Most of the data will be mainly provided by the cities (car traffic, bikes traffic, pedestrians, noise and air pollution data, Mobility Observation Box data from each city…) in different points in time. This data will feed the solutions to be developed (for example, air and noise pollution improvements or optimizing the existing transport network). This data will be crucial to the development and utilization of the three digital urban twins. It will present interesting data for city authorities, local transport authorities and researchers.The data is a combination of accumulated data: Big Data and the real-time (RT) streaming data. The real time data is the data representing current values provided by relevant providers e.g. IoT. This data, after being analysed, defines events to be handled by the city as soon as possible e.g. air quality related events.
The Big Data platform will provide predictions and pattern recognition to be used together with the Real-Time Data to define events that will help to come up with recommendations to address the specific per city challenges.

Digital twins

ITAINNOVA is going to develop Digital Twin, virtual copy of a real-world item or procedure. It is a dynamic model , created with historical data and updated in real-time to represent the physical object or process. Digital twins track, examine, and forecast how physical things or processes will behave. They can boost performance, reduce downtime, and increase efficiency.

Digital twins have the potential to revolutionize the mobility and transport industries. They can be used to improve efficiency, reduce congestion, and make transportation more sustainable. Traffic management: Digital twins can predict traffic conditions with behavioral hypothesis. This information can be used to optimize traffic lights, reroute traffic around accidents, and provide drivers with updates on traffic conditions. The trafic scenarios can be updated with information about the status of the infrastructure, such as roads, bridges, and tunnels. This information can be used to identify potential problems before they cause significant disruptions and to plan for maintenance and repairs.

Public transportation: Digital twins can be used to improve the efficiency of dynamic public transportation systems. They can be used to optimize routes, schedules, and fares.