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Data Sources and Models for Integrated Mobility and Transport Solutions.

Pierfrancesco Bellini¹, Stefano Bilotta¹, Enrico Collini¹

¹DISIT Lab, University of Florence, 50139 Florence, Italy.

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|January 23, 2024

Summary

This summary is machine-generated.

This paper reviews mobility data models and standards, highlighting their complexity and potential for integration. It explores using these models for city transport management and planning, leveraging the Snap4City platform.

Keywords:

big data data models data space mobility and transport

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Area of Science:

Transportation Science
Data Management
Urban Planning

Background:

The proliferation of data sources and models in mobility and transport has led to complexity in integration and management.
Existing data models often overlap and can be used interchangeably for similar innovative solutions.
This complexity hinders the efficient exploitation of data for smart city applications.

Purpose of the Study:

To provide an overview of data models and standards in the mobility domain and their interrelationships.
To explore the potential exploitation of these data models for operational city transportation management.
To investigate the use of data models in feeding simulation and optimization processes for infrastructure planning.

Main Methods:

Literature review of existing data models and standards in the transportation sector.
Analysis of data model overlaps and potential for alternative exploitation.
Case study application within the Snap4City platform context for operational processes.

Main Results:

Identified significant complexity and overlap among various mobility data models.
Demonstrated the feasibility of using data models for operational city transport management.
Showcased the integration of data models for simulation, optimization, and planning processes.

Conclusions:

Standardization and integration of mobility data models are crucial for efficient smart city solutions.
The Snap4City platform facilitates the exploitation of diverse data models for enhanced transport management.
Effective data model utilization supports both tactical control and strategic planning of urban transport infrastructure.