WP1 – Project coordination (Lead: POLITO)
The overall management plan aims to guarantee the smooth cooperation between Research Units (RUs) and interconnection between WPs and Tasks.

WP2 – State-of-the-art and current technological solutions monitoring (Lead: POLITO, UNIPARTHENOPE) in the mobility domain, both due to constant technological innovations and the possible radicalization of public policies also due to external factors (for example the current pandemic situation linked to Covid-19 spread, the evolving Ukrainian conflict, changes in the political framework, including local ones, etc. ), game changers events are even more possible and probable. Infact, with reference to the pandemic, the actual change (to be considered stable in the future) in the working methods in a form of smart working, leads to drastic decreases in commuter mobility and a densification of local flows in urban areas or peripheral areas, not registering suah flows since few years ago. The Ukrainian conflict is instead leading to a reconsideration of the supply of energy sources on a global scale, in which the energy transition imagined up to now, based on renewables strongly dependent on raw materials generally not available in the European Union, also strongly affects mobility. in which hydrogen could in the next few years be the preferred source, and to a large extent, self-produced by individual States to protect them from future international tensions. To this end, WP2 focuses on a continuous updating of the state of the art and technological solutions that could, given what was mentioned above, radically change even in very short terms.

WP3 – Mobility data transfer, integration and modeling (Lead: UNIPARTHENOPE)
Location tracking technologies are currently primarily used for location-based services (LBS) such as local search or routing and navigation, but increasingly serve other mobility purposes as well. One basic use of location tracking is data collection for statistical purposes, in particular in combination with spatio-temporal analyses. Other uses of location tracking in the focus of the project is giving mobility feedback that can be used to encourage people to make sustainable mobility choices.
To resolve mobility-related issues significantly and in the long term, all of the relevant influences on individual mobility behaviors in an urban environment must be detected. Since gathering data on travel behaviors from the real world is extremely difficult, the primary objective of this WP is to develop GNSS-ready tracking and positioning solutions for user mobility behavior detection.
In recent years, new data sources have become increasingly common through the use of the automatic collection of entry counts, exit counts and link flows. However, collecting such data can be sometimes costly. On the other hand, GNSS-based positioning systems are likely to profoundly influence the mobility survey data. GNSS serve as a consolidated technology for applications where accurate location is needed – including the tracking of moving objects. A major advantage with the usage of GNSS tracking devices for collecting data is that it enables the researcher to collect large amounts of accurate and detailed human mobility data.
We primarily aim to examine the performance of positioning systems to better understand the positional needs of user mobility it meets today and what might be possible in the near future with the advent of GNSS advances in the areas of low-cost multi-frequency carrier phase GNSS receivers and correction services.
Nowadays, satellite-based positioning systems have been much improved both on availability and accuracy with a combination of multiple global navigation satellite systems (GPS, Galileo, GLONASS and BeiDou), namely multi-GNSS. With decimetre accuracy and the update rate up to 30-50 Hz, GNSS have significant potential in the development of ITS and associated services. Europe’s contribution to this global initiative includes the European Geostationary Navigation Overlay Service (EGNOS) and Galileo providing a
great impact on such sectors as mobility and location-based services (LBS).
Nevertheless, a major technical issue is the quality of positioning service — not only in terms of accuracy, continuity, and availability, but also integrity, which expresses the level of trust in the positioning solution. With increasing reliance on GNSS technology, positioning testing is critical and it is important to understand what to expect from such systems. This includes formulating an understanding of the limitations and challenges of PNT technologies and how to test them. Multiple factors influence the performance of a GNSS-enabled system and only accurate testing can characterize the performance of the system to ensure that it
meets the expectations of the end-user. There aren’t any global standards available for GNSS testing except in the case of a few applications and hence most of the GNSS and GNSS-based applications testing are ad hoc in nature.
In this project, advanced multi-GNSS with precise point position real-time kinematic (PPP-RTK) technique is proposed. The advantage of PPP-RTK over conventional navigation is decimeter accuracy without direct connection to any reference base station with low convergence time.
GNSS mobility data can be provided by various sources to distinguish between smartphones and stand-alone low-cost GNSS receivers. With the increasing digital transformation, the mobile phone has developed into a powerful portable computer carried in the pockets of almost the entire population. The integration of GNSS-receivers into these devices allows the gathering of data on human mobility at an unprecedented scale and detail. On the other hand, vehicle location information is of increasing importance for Advanced Driver Assistance Systems (ADAS), connectivity (V2X, in terms of vehicle to vehicle, infrastructure and other entities), and Autonomous Driving (AD) features. This project deals with several important aspects of the collection, processing and application of such data.
Therefore, low-cost embedded GNSS receivers have become ubiquitous in mobile devices to a large extent. However, limited sky visibility and multipath scattering induced in urban areas are responsible for severe errors on the raw GNSS measurements. In this context, it is also of interest to focus on hybrid positioning systems based on low-cost GNSS integrated with other sensors. Advanced integration schemes leveraging fusion of GNSS/Inertial Measurement Unit (IMU) measurements constitute the prevalent solutions to guarantee satisfying performance in harsh environment, where standalone GNSS is typically weak.
Some specific applications can be enabled only if location is broadcasted live, to traffic control centres (V2I) or to other vehicles (V2V or V2I), and if coupled with additional sensors: e.g., for the automatic detection of parking spaces at ground level or for authorising double-parking in special situations. Within the project, a feasibility test will be performed: the test will be focused on the possibility for live transmission of location and imagery data (e.g. the ones acquired by on-board cameras) and on measuring the latency needed for providing value-added information based on the processing of those data (e.g. AI algorithms applied to images acquired by on-board cameras on a known location, in order to broadcast information over available parking places to other vehicles.

WP4 – Implementation of the data structure and setting up of the analysis environment (Lead: POLITO)
Within this project, we also look at how geospatial technologies and mapping approaches are able to support sustainable personal mobility, with a particular focus on mapping techniques as key enablers for users need to know where they are in relation to roadway and all other physical features on the ground.
The quality and integrity of the data behind these maps is paramount to meeting the requirements of mobility applications. On top of these challenges, international technical procedures ensuring digital maps reliability are currently lacking. The need for minimum performance parameters to ensure the integrity, accuracy and reliability of the datasets (both GNSS data and digital maps), as well as the creation of governance processes regarding the aggregation, storage and redistribution of these datasets were two of the key aspects of this project (Scrocca M., Cornerio M., Carenini A., Celino I., 2020).
In urban and metropolitan context, the above mentioned Central Positioning Aggregator Engine can store and aggregate data coming from different sources: a challenge in mobility management is to transfer different data into a unified data management system that preserves access to legacy data, allowing further processings and analysis. The general aim is to build-up a geodatabase in a federated DMBS platforms, rather than replacing existing systems, allowing and extensive usage of integrated data for policy and strategic mobility decisions. A data modelling activity taking reference from a review of transport standards, should then result in geodatabase general schema that could be generalized, disseminated and integrated in other apps. Concerning topics related to road spatial visualisation and thematic representation, different standards will be taken into consideration; the INSPIRE Road Network Model (INSPIRE,2013), the FGDC Model (Federal Geographic Data Committee,2008) and the CityGML are considered to be the most complete, allowing a detailed geometrical representation and the high number of possible feature attributes enables a variety of thematic representations (road hierarchy, speed limits, lanes, …). On the other hand, Traffic Message Channel (TMC) standards defines only at logical level (points and relation between points), lacking of a precise road geometrical representation and a hierarchical classification taking into consideration road naming only. TRANSMODEL (TRANSMODEL, 2015) and GTFS, also allow a precise geometrical representation of the public transport routes (even if in GTFS the geometrical definition of a linear element is optional).
In connection to this modeling activities, the research project will ingest all possible source of digital mapping data taking into consideration both authoritative and Open Source (OS) dataset, trying to define all the characteristics enabling mobility applications: scale, precision, accuracy (both in term of positional and thematic contents), updating, associated attributes and impedances, topology, hierarchy, etc. CPAE will, as result, integrate all reference mobility map features such as points elements (road graph nodes, bus and train stops, etc), linear (road graphs, road lanes, limited traffic areas borders, public transportation lines, cycling
paths, etc.) and polygon ones (road and crossing sections, sidewalks, platforms, ecc.).
From the thematic dataset point of view, the geodatabase will incorporate and model also other data source such as:

• vehicle flows measured for road arc (both actual and historical data) as measured by traffic centres endorsing the research project (following figure), enabling traffic distribution and analysis.