David Schmitt, on Transportation Forecasting
Description
In this episode, we delved into the dynamic realm of transportation forecasting, exploring a wide array of ideas and questions.
Our discussion with David began by examining the primary data sources and methodologies that drive modern transportation forecasting. We continued by highlighting the pivotal role of real-time data, GPS technology, and advanced algorithms in providing accurate insights into traffic patterns, public transit ridership, and the trajectory of mobility trends. We also discussed the integration of emerging technologies like autonomous and electric vehicles, showcasing their transformative potential in shaping transportation models and infrastructure.
From a consulting and practical perspective, we explored the challenges of ensuring the accuracy and reliability of transportation forecasts and contemplated the influence of AI and machine learning on the future of transportation forecasting.
United States
