Real-Time Data and Simulation for Optimizing Regional Mobility in the United States

Highway congestion wastes over 3 billion gallons of fuel each year and causes 7 billion hours of lost productivity. Highway congestion costs freight movers ~$63 billion dollars per year, ranging from $5600-30,000 per truck (and is increasing). Research has shown the ability to introduce near-real time traffic monitoring and adaptive signal control (including small numbers of connected vehicles) can yield up to 30%reduction in congestion. Deploying this approach at a regional scale, that has high-volume and transient traffic, extreme data volumes, and potentially 100,000 vehicles, sensors, and control devices requires High Performance Computing (HPC). We created a ‘Digital Twin’ of the Chattanooga region with simultaneous pairing of both the virtual and physical world providing real-time situational awareness. This Digital Twin will be the basis of a cyber physical control system with high-speed bidirectional communication and control of the highway infrastructure and connected vehicles in the ecosystem to achieve a 20% energy savings in a region. If successful, the results of this project could be replicated region-by-region to commercialize the approach across the entire U.S., so that over the next 10 years, this project accelerates a reliable intelligent mobility system implementation to reduce overall mobility-related energy consumption by 20% and recover $100 Billion of lost productivity in congestion. The availability of real-time data from vehicles and the deployment of supporting infrastructure such as high-speed fiber networks has opened up an unprecedented opportunity to bring together high-performance computing, advanced mobility simulations, and existing transportation expertise to create a platform that could have a decadal impact in transforming regional mobility in the United States. We propose to optimize the movement of both people and freight in and around Chattanooga, TN, a representative urban/suburban region, by leveraging high performance computing, data analytics, and machine learning. Near real-time insights provided by the integration of data from emerging mobility technologies and services can inform all phases of strategic planning, design, operation, modernization, and decommissioning of ageing/legacy systems. Lessons learned and capabilities developed and deployed for regional mobility can be applied to optimize mobility nationally deploying region-by-region.