This project was developed for the Asian Development Bank (ADB) AI for Safer Roads Challenge.
The solution evaluates whether existing speed limits are appropriate for the surrounding road environment using:
- Safe System principles
- Explainable AI
- GIS-based risk assessment
- Risk-based intervention prioritization
- Road Safety Risk Scoring
- Explainable AI (SHAP)
- Priority Intervention Ranking
- Interactive GIS Risk Map
- Policy-Oriented Recommendations
- notebooks/ : Main analysis notebook
- outputs/ : Assessment outputs and datasets
- maps/ : Interactive web maps
- visualizations/ : Figures and dashboards
- reports/ : Executive summaries and recommendations
- Interactive Risk Map
- Priority Segments Dataset
- GeoJSON Outputs
- Explainability Analysis
- Policy Recommendations
The framework combines:
- Safe System principles
- Machine learning-based assessment
- Explainable AI (SHAP)
- Risk prioritization
- Geographic visualization
The objective is not merely to reproduce historical speed limits.
The framework assesses whether current speed limits are appropriate and identifies locations where interventions may improve road safety.
The generated spatial outputs (GeoJSON and tabular datasets) are designed to be compatible with enterprise geospatial platforms such as ESRI ArcGIS, supporting future deployment and decision-support workflows.
- Findings Summary:
docs/ADB_AI4SaferRoads_Findings_Summary.pdf - Submission Overview:
docs/challenge_submission_overview.md - Main Analysis:
notebooks/ADB_AI4SaferRoads_SafeSpeed_Assessment.ipynb
The datasets used in this project were provided under the ADB AI for Safer Roads Challenge Data Use Agreement and are not included in this repository.
See:
data/DATA_NOT_INCLUDED.md