Solving Houston’s mobility challenges with better predictions and real-time data

Modernization of fleet schedules and route management 

At the dawn of EastBanc Technologies’ TransitIQ platform and app, a client wanted an app, so riders could see bus route predictions. This client was Houston Metro, the fourth most populous metropolitan area’s public transportation authority in the United States. Houston Metro became one of the first primary users of the TransitIQ white-label app, and this cooperation spawned multiple platform customizations and updates ultimately helping Houston Metro get better predictions for their routes and give their riders more certainty in their daily commute. 

Predictions and transparency in transportation 

The ultimate breakthrough in predicting the bus arrival times happened when Houston Metro held a competition to provide them with the most accurate prediction, which EastBanc Technologies won. From then on, we provided Houston Metro with predictions based on big data and the analytical platform, where you could evaluate the projections and see the data that led the system to make that prediction. The idea was to make the predictions transparent and show how we built them, so the system didn’t look like a black box where no one knew what was happening. Having a transparent system made the predictions better because people using it can track the quality of the predictions and give critical feedback. 

Business intelligence for transportation 

To look at the bus system performance from different points of view EastBanc Technologies’ team added the Business Intelligence unit to the platform. This platform had an automated anomaly detection and notification system that could show bus batching, vehicle history, run times, and service status. Ultimately, the business intelligence data gave control over thousands of moving parts and more opportunities to increase the accuracy of the predictive analytics. 

Using the new platform Houston Metro was able to see the full scale of how being data-driven affects their operations and how having the right data is the key. Recognizing its effect on predictions lead the Metro to update their internal policies and subsequently increase the accuracy of predictions and satisfaction of its riders.  

Making cities better with better predictions 

Based on the TransitIQ platform and using Big Data and prediction models, we built an app that offers riders the most efficient route and time predictions based on real-time traffic data and their location.  This gave Houston Metro the tools to manage their fleet and schedules in a new, more efficient way, reinforcing their reputation as one of the most advanced and awarded public transportation systems in the US.