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Gainesville and Connected Signals delivering real-time traffic signal data to reduce red-light crashes and improve fuel efficiency

In April 2017, the City of Gainesville, Florida began work on a pilot project with Connected Signals, Inc., a provider of real-time, predictive traffic signal information, as part of the University of Florida Transportation Institute’s I-STREET testbed. I-STREET was created in partnership with Florida Depart of Transportation’s (FDOT) Connected Vehicle Initiative to test connected and autonomous vehicle technologies.

The pilot, one of the first of its kind in Florida, has continued to roll out, and today nearly all of Gainesville’s traffic signals are online with Connected Signals’ smart signal information.

Connected Signals securely aggregates real-time signal information via its patented data-capture device and feeds it through predictive algorithms to determine information (such as when lights will be changing from red to green and vice versa).

Connected Signals’ prediction engine uses advanced machine learning and statistical techniques to integrate a broad range of information, including current light state, light timing plans, time of day, vehicle and pedestrian calls, and historical behavior to determine when a light will change, and certainty about the prediction.

The information is then delivered to Gainesville drivers via Connected Signals’ free Enlighten mobile phone app. This information will ultimately also be made available through direct integration into connected cars’ displays and powertrains.

Cell phone GPS systems are typically noisy and relatively inaccurate, making it difficult to determine exactly where a user is and how fast they are going. This can be an issue when trying to determine which light a user is approaching. It presents even greater problems when trying to detect when a red light is being (or is about to be) run, where false positives could be distracting.

Connected Signals has developed advanced techniques for localization that help address these issues. Some of these are already fielded in existing applications, while others will be deployed in future products. For vehicle-based applications, even more accuracy can be achieved by obtaining information from vehicle systems (GPS, speedometer, turn signals, brake pedal status, etc.), resulting in a broader range of supported functionality.

Available features currently include red light countdowns and green-wave speed indicators so that drivers make smarter decisions: to take their foot off the pedal and coast to the light, to slow down sooner, or to not rush to “make a light” that is impossible to make, etc.

The green wave speed indicator is particularly effective in helping drivers to safely adjust their speed to get into a wave of green lights and avoid stopping altogether. This data, when shared with vehicle and drivers, can improve fuel efficiency by 8–15% and reduce red-light crashes by 25%.



Considering how many millions of gallons of fuel are wasted each year due to poorly timed lights, this could be a plus.

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