Identifying atypical road curves
Reduce accidents with preventive road safety management
Each year, nearly 1.3 million people die in road traffic accidents around the world. Our vision is to leverage our expertise in driving behavior analysis to help reduce road mortality.
Collecting and analyzing crash data, defining high-risk areas, prioritizing road maintenance interventions, monitoring and assessing intervention effectiveness are key areas of focus for road infrastructure managers and city planners.By aggregating and analyzing driving behavior data, we put driving data in context and transform it by applying our proprietary algorithms on driving behavior analysis to deploy high added value services and support mobility and infrastructure stakeholders.
DDI data science teams have built an atypical curve dataset to help identify curves from atypical driver behavior : this includes curves where drivers have been surprised, where drivers have failed to assess the proper speed and trajectory , and where near miss events have occurred.This dataset helps identify curves which require a thorough analysis in the field, and which may not have been detected by analyzing only crash data and accident reports.
You can rank curves in your area thanks to Michelin DDI indicator (assessing the risk profile of the curve, correlated with crash data). This enables your teams to analyze potential root causes in the field and prioritize corrective actions such as road signage or broader hasard mitigation. This ultimately enables more effective risk reduction by improving infrastructure, minimizing near misses and preventing road accidents.
Reach the atypical curves API by clicking on this link
- DatasetAtypical curves analysis in France
Identify & qualify the risk profile of road curves for a given geographical area.