SynthCity Case Study – Genoa, Italy

🏙️ SynthCity Case Study – Genoa, Italy SynthCity is a multimodal synthetic urban mobility dataset generated through microscopic traffic simulation with Eclipse SUMO, using the city of Genoa, Italy, as a case study. The dataset was created from publicly available urban data, integrating: 🗺️ OpenStreetMap (OSM) for the transportation network; 🚍 GTFS public transport data for Genoa; 🧮 Origin–Destination (OD) matrices describing mobility demand across the city. The original daily mobility demand was temporally distributed to reproduce intra-day traffic variations and more realistic peak-hour patterns. SynthCity provides data at three complementary levels: 🚌 Public transportation — stop-level transit operations and passenger-related events; 🚗 Private transportation — individual simulated vehicle trips; 🌐 Transport-network usage — traffic conditions at the level of individual road-network edges. The release includes both nominal mobility conditions and selected anomalous urban mobility scenarios, allowing direct comparison between regular and disrupted operating conditions. 📂 Files included in this release 🚌 SynthCity_Genoa_April2022_PublicTransport_Nominal.csv This file contains the nominal public transportation dataset generated for the Genoa case study during the simulated weekdays of April 2022. Each record describes a public-transport event at stop level and includes information related to simulated transit operations, such as vehicle, route, trip and stop identifiers, arrival and departure times, and passenger-related quantities such as boarding and alighting counts. This file represents the reference public-transport operating condition, without injected disruptions, and can be used as the baseline for comparison with the metro-strike scenario. 🚗 SynthCity_Genoa_April2022_PrivateTrips_Nominal.csv This file contains the nominal synthetic private-vehicle trips generated across the Genoa transportation network. Each entry represents an individual simulated trip and describes the corresponding vehicle movement, including origin and destination information, departure and arrival times, travelled route, route length and other trip-level mobility information. The file provides a fine-grained representation of private urban mobility under regular conditions and can support trajectory analysis, travel-time modelling, mobility-demand studies and traffic-behaviour analysis. 🌐 SynthCity_Genoa_April2022_NetworkEdges_Nominal.csv This file contains the nominal road-network usage dataset. Unlike the private-trip dataset, which describes individual vehicle movements, this file provides an edge-level representation of traffic conditions across the road network. Records are associated with SUMO network edges and describe how each road segment is used over time. The dataset includes traffic-related indicators such as vehicle flow, traffic density, mean speed and road-segment characteristics. This file represents the main network-level baseline against which the anomalous road-closure and special-event scenarios can be compared. 🚇 SynthCity_Genoa_2022-04-25_PublicTransport_MetroStrike.csv This file contains public-transport data for the metro-strike anomalous scenario. The scenario models a complete, 24-hour suspension of Genoa's subway service on 25 April. All trips associated with the Genoa metro route MM-91 Brin – De Ferrari – Brignole are removed from the simulated public-transport service for the entire day. The disruption causes mobility demand that would normally be served by the metro to affect alternative public-transport services, particularly bus routes serving areas close to metro stations. The file can be used to investigate: changes in public-transport demand; increased pressure on alternative transit services; changes in stop-level passenger activity; effects of a large-scale transit disruption. For comparative analyses, this file should be considered together with: SynthCity_Genoa_April2022_PublicTransport_Nominal.csv 🚧 SynthCity_Genoa_2022-04-04_NetworkEdges_RoadClosure.csv This file contains edge-level traffic data for the road-closure anomalous scenario. The scenario models the temporary closure of a segment of Via Canevari, an important arterial road in Genoa used by both private and public transportation. The closed road segment becomes inaccessible during the disruption interval, forcing vehicles to reroute through alternative paths in the surrounding transportation network. The resulting dataset captures effects such as: 🔀 traffic rerouting; 🚙 redistribution of vehicle flows; 🛣️ changes in road-segment usage; 📉 changes in edge-level speed; 📈 congestion propagation to neighbouring roads; 🧩 network response to infrastructure disruption. For comparison with regular traffic conditions, this file should be analysed together with: SynthCity_Genoa_April2022_NetworkEdges_Nominal.csv 🏟️ SynthCity_Genoa_2022-04-11_NetworkEdges_StadiumDemand300pct.csv This file contains edge-level traffic data for the special-event / increased-demand anomalous scenario. The scenario reproduces a major event at the Genoa stadium by increasing travel demand toward the stadium area. Mobility demand from the rest of the city toward Zones 42, 37 and 69 is increased by 300%, with the additional demand concentrated during the event arrival period. The dataset captures how this localized demand surge affects the surrounding road network, including changes in traffic pressure, density, flow and mean speed at road-segment level. The file can be used to investigate: 🎫 event-driven mobility demand; 📈 temporary traffic surges; 🏟️ congestion around major venues; 🌐 propagation of localized demand through the wider network; 🚦 network response to sudden and spatially concentrated mobility changes. For comparison with nominal network behaviour, this file should be analysed together with: SynthCity_Genoa_April2022_NetworkEdges_Nominal.csv 📊 Dataset composition Mobility component Nominal condition Anomalous scenarios 🚌 Public transportation 5,607,953 records 937,233 records 🚗 Private transportation 2,581,172 records 381,381 records 🌐 Transport-network edges 58,685,598 records 8,190,843 records The three components provide complementary levels of observation, ranging from individual vehicle trips and public-transport operations to aggregated traffic behaviour across the urban road network. 🧪 Anomalous scenarios SynthCity includes three representative disruption types: 🚇 Metro Strike — full suspension of Genoa's subway service and redistribution of demand toward alternative public transport; 🏟️ Special Event — a 300% increase in travel demand toward the stadium area; 🚧 Road Closure — temporary closure of a major arterial road with traffic rerouting and congestion redistribution. These scenarios are intended to support what-if analyses of how an urban transportation system reacts to unexpected or abnormal mobility conditions. 🎯 Potential use cases The dataset can support research in areas including: 🤖 AI-based mobility prediction and demand forecasting; 🚦 traffic prediction and traffic-management strategies; 🔎 anomalous mobility detection; 🚌 public-transport demand analysis; 🧠 data-driven Intelligent Transportation Systems; 🧩 transportation-network resilience; 🏙️ urban mobility modelling; 🧪 simulation-based benchmarking; 🔀 disruption and rerouting analysis; 📊 comparison between nominal and anomalous mobility conditions. 💻 Software and reproducibility The datasets were generated using the SynthCity framework, a modular simulation-based approach for automatically introducing configurable mobility anomalies and producing structured synthetic mobility datasets. Source code and additional implementation details are available at: https://github.com/dera8/SynthCity 📜 Preferred citation If you use this dataset, please cite: D. Russo, F. Rocco Di Torrepadula, L. Libero Lucio Starace, S. Di Martino, and N. Mazzocca,“A Framework for Generating Synthetic Urban Mobility Datasets With Customizable Anomalous Scenarios,”IEEE Open Journal of Intelligent Transportation Systems, vol. 6, pp. 1439–1458, 2025.DOI: 10.1109/OJITS.2025.3626948