Analyzing Big Data To Create Sustainable Mobility Systems.
A collaboration between UC Berkeley and Lawrence Berkeley National Laboratory.
The Smart Cities Research Center strives to sustainably and equitably improve mobility and quality of life in our cities. We do this through advanced quantitative modeling of urban systems, using that data to power the complex, interdisciplinary decision-making required to manage modern cities.
We focus on optimizing mobility, energy, productivity, regional economics, and quality of life in our cities by increasing mobility system efficiency, reducing cost, reducing fossil fuel use and increasing the effectiveness of transportation.
Rich Geospatial Data
Meticulously process and clean billions of records of trip data - all while holding data privacy in the utmost regard.
Shatter boundaries on how fully and rapidly we can optimize and simulate mobility patterns across an entire region.
Embrace the intertwined nature of urban challenges, and consider the implications of our work holistically.
At the center of our work is Mobiliti, our cutting-edge software system that accurately simulates the movement of an entire population through a region’s road networks. Unlike traditional simulation capabilities, Mobiliti is able to handle the incredible volume of data that comes with modeling millions of trips across an entire metropolitan system.
Just how well does Mobiliti scale? For the entire San Francisco Bay area (population ~8 million), the system can simulate a whole day’s worth of trips in under four minutes.
This game-changing performance opens up incredible possibilities.
- Scenario plan for everything from major accidents to natural disasters.
- Run sensitivity analyses on your core traffic demand assumptions.
- Carry out ‘digital thought experiments’ on how to improve the accessibility and utilization of public transit options
- Model the energy-efficiency and carbon footprint of entire transportation systems.
- Rigorously simulate the impact of rolling out new transportation technologies and policies – from changes in highway safety guidelines, to introducing connected vehicles to the road.
- Test out innovative solutions to mobility and transportation problems by simulating the proposal on an urban scale.
- Apply high-performance computational strategies to discrete event-based systems in research areas beyond transportation.
We're experts in these areas
Sense-making of imperfect, massive geospatial datasets is foundational to everything else we do. We’re experts in efficiently determining staypoints, interpreting driver behavior, and even automatically detecting which intersections in a road network use stoplights.
The real power of Mobiliti is in being able to simulate emergent behavior when that equilibrium is disrupted. To do this effectively at the scale of billions of events per day, we’ve taken an innovative approach to parallel discrete event simulation – an algorithm through which the impact of sequential events on a system can be processed in parallel without losing the causality between those events.
The future of transportation management lies not only in understanding the state of the world, but also in proactively managing it. To this end, we’ve developed neural networks to accurately predict future highway traffic, and are investing in reinforcement learning approaches to manage dynamic traffic signal timing.
The GPS-based services we rely on today (Google Maps, Waze, Uber, Lyft) all optimize for minimizing vehicle travel time. But that approach comes with externalities – a famous example being quiet residential streets suddenly facing a deluge of Lyfts taking a shortcut. Our Mobiliti analytics allow us to explore the impacts of alternative routing strategies – on safety, on fuel consumption, and much more.