Traffic and Road Safety

Traffic and road safety research examines why crashes happen, how severely they injure people, and what conditions make roads more or less dangerous for drivers, cyclists, and pedestrians. By combining behavioral data, crash records, and spatial analysis, researchers build predictive models that can identify high-risk locations or driver patterns before a collision occurs rather than only after. Despite steady progress, accurately forecasting crash likelihood in complex urban environments and understanding how factors like congestion, road design, and human decision-making interact remains genuinely difficult. Active work is pushing toward better integration of real-time traffic data and machine learning to close those gaps and translate findings into interventions that measurably reduce harm.

Works

96,391

Total citations

988,868

Keywords

Traffic AccidentsDriver BehaviorInjury SeverityRoad SafetyPedestrian SafetyCrash Prediction Models