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How we created HOV-specific ETAs in Google Maps

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The shift to sustainable travel modes like electric vehicles (EVs), carpooling, and public transit, has made travel times more varied. This is largely due to the availability of dedicated lanes, such as carpool lanes, also called high-occupancy vehicle (HOV) lanes, which are reserved for vehicles with multiple passengers and are designed to move traffic more efficiently during peak hours. As a result, HOV lanes are typically faster than general lanes during rush hour. For example, in Utah’s Salt Lake Valley, the average speed in HOV lanes was recorded at 68.18 mph compared to 58.60 mph in general lanes, a difference of about 16%.

Accurate estimated time of arrival (ETA) predictions and optimized routing are key to improving the commuting experience. With precise ETAs, travelers can make better decisions, save time, and even contribute to reducing congestion and emissions. With this in mind, Google Maps recently introduced a feature that lets drivers select routes that include HOV lanes and see that route’s ETA. In this blog post, we explain how we developed this feature and developed a classification system to determine HOV trips from non-HOV trips, which led to the launch of HOV specific ETAs in Google Maps.



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AI Research

The new frontier of medical malpractice

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Although the beginnings of modern artificial intelligence (AI) can be traced
as far back as 1956, modern generative AI, the most famous example of which is
arguably ChatGPT, only began emerging in 2019. For better or worse, the steady
rise of generative AI has increasingly impacted the medical field. At this time, AI has begun to advance in a way that creates
potential liability…



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Pharmaceutical Innovation Rises as Global Funding Surges and AI Reshapes Clinical Research – geneonline.com

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Pharmaceutical Innovation Rises as Global Funding Surges and AI Reshapes Clinical Research  geneonline.com



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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review – Cureus

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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review  Cureus



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