<p>PLOSOne-data.</p>

Traffic, weather, and event data from 2017 to 2023 for Kandovan Road, a critical mountainous suburban route. Shahriar Afandizadeh published this dataset on figshare to support the evaluation of eight machine learning models for traffic prediction. The dataset underpinned a study where a Random Forest Regressor achieved an R² score of 0.88 for forecasting traffic flow under variable conditions.

Use Cases

• Train traffic forecasting models based on integrated traffic, weather, and event data mentioned in the description
• Compare performance of deep learning and traditional ML models like LSTM and Random Forest for time-series prediction
• Develop decision-support tools for traffic authorities based on real-time prediction visualization capabilities described
• Study the impact of environmental and calendar events on traffic patterns in mountainous suburban corridors

Strengths

• Integrates multiple data sources (traffic, weather, events) over a 7-year period from 2017 to 2023
• Served as the basis for a published study where models achieved an R² score of 0.88
• Available under a permissive CC-BY-4.0 license for reuse and modification

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment; the total size is only 243.5 KB, indicating a limited scope
• Geographic coverage is specific to a single road (Kandovan Road), limiting generalizability

Provenance

Source

figshare, author Shahriar Afandizadeh

Collection Method

Likely collected from traffic sensors, weather stations, and event calendars for the specified road.

Time Range

2017 to 2023

Freshness

Last updated 2026-05-05 17:24:34; freshness should be verified

Geography

Kandovan Road, a mountainous suburban route