TidalWave Streams Traffic Service for Connected Cars

Advances in connected vehicle technology and advanced driver assistance systems (ADAS) haven’t been able to tackle global traffic problems — at least not yet — but a new live streaming traffic information service could be a step forward.

Traffic control systems specialist Trafficware and Silicon Valley startup SWIM.AI, a software firm that combines edge computing and machine learning, announced the launch of TidalWave, a cloud-based, real-time traffic service.

The use of edge computing optimizes cloud systems by performing data processing at the edge of the network, near the source of the data. In this case, it’s located near or on transport infrastructure.

Now available nationwide, the Tidalwave service claims to deliver streaming traffic data with “sub-second accuracy,” performing traffic and signal analysis either at a city’s advanced traffic management system or on controllers at street level.

Based on an open source traffic data, with applications ranging from use in connected vehicle applications to smart city networks, the technology would replace historical cellular GPS data, which is currently used to measure roadway congestion and estimate travel times.

However, the speed and accuracy at which the data is collected, analyzed and made available can be slow and often does not reflect the actual experience of drivers.

“TidalWave was designed using the first of its kind, intelligent edge architecture for use by the connected vehicle, smart cities, and internet of things markets, and will lead the next transformative era of technology over the next decade,” Trafficware CFO Joe Custer wrote in a statement.

The companies describe the service as a simple software addition to existing city infrastructure, using edge computing to reduce data volumes and help with hardware savings.

A company release noted subscribers to the Tidalwave service receive traffic information from a real-time application programming interface (API) with no cost for the service to the city.

“TidalWave uses a disruptive approach based on edge learning and analytics. TidalWave analyzes, learns and predicts as data is created, at the edge, on existing hardware using a powerful edge compute/data fabric,” SWIM CEO Rusty Cumpston noted. “It delivers precise, granular traffic data at a resolution of hundreds of milliseconds, at a small fraction of the cost of central cloud-hosted learning and prediction.”

In addition to the benefits of real-time information the service provides, the build-out of 5G networks — considered critical to the performance of autonomous vehicle (AV) development — could make a major impact on reducing automobile traffic.

One of the key advantages of the upcoming 5G networks is the use of much higher frequency bands — Millimeter Waves — which broadcast at frequencies between 30 and 300 gigahertz.

These frequencies, due to the higher spectrum and wider channels, offer much faster transmission rates and extremely low latency — up to 100 times lower than current 4G networks.

Having gigabit speeds and low latency, down to one millisecond, is not enough to ensure quick response, especially on self-driving vehicles. However, the type of edge computing used in TidalWave will play a major role in closing that gap.

— Nathan Eddy is a filmmaker and freelance journalist based in Berlin. Follow him on Twitter @dropdeaded209_LR.

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