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On our path to contribute to Safer Roads, we asked a simple but relevant question: What’s the most dangerous time of day to be on the road? General intuition tells us that commute hours are usually the worst. Is this true? And if so, how much? To answer this question, we deep dived on our historical records and looked into ride records, as well as road incidents registered (hard brakes and collisions).

As mobility, autonomous systems, and digital infrastructure evolve, the demand for up-to-date, high-accuracy mapping has never been greater. Traditional HD mapping approaches, reliant on expensive, slow-to-update sensor fleets, struggle to keep pace with rapidly changing road conditions. This analysis presents a new paradigm in mapping where dash cams capture real-time data from hundreds of thousands of vehicles, delivering fresh mapping data at a fraction of the cost. This technology provides unmatched freshness, cost efficiency, and scalability, revolutionizing how we map the world around us.

There’s a difference between what maps show and what actually exists in the real world. While humans can adjust to missing data, new (software-) map users, from AVs to driver assist functions (such as Intelligent Speed Assist), cannot. While some map layers, such as the base map, seldom change, additional map layers, such as road furniture (e.g. traffic signs), or lane information change more often. To ensure safety for AV applications, the data in all relevant map layers should be highly accurate, with any change quickly detected and updated on the map.