Now, WaveSense is pretty much starting from scratch as far as mapping data is concerned, so how does it plan to grow and expand its service area?
“Unlike camera or Lidar maps, our solution does not require post-processing, we use the raw data straight away. First we’ll be covering the top ten metropole areas where high-value services such as automated parking could be offered. Boston (only a few miles from where the company is based) has about 2400 lane miles to cover. That’s not significant and we can create these maps. We are not going to map every single road in the US but fill the high-value maps first. Same for parking, there are about 30 to 40 parking locations in Boston”.
Bolat says he received a lot of interest from other markets, such as oil & gas operations, airports, large logistics and distribution centers and other environments that typically have a low feature surface environment in contrast to the rich sub-surface environment that GPR has access to.
For these other markets, WaveSense could design bespoke solutions. Utilities can create maps of sub-surface infrastructures and there are other pockets of value, explained Bolat, although those are not the company’s primary market.
“Most of our pilot activities happen in Boston and Detroit, but we are open to mapping partnerships” answered the CEO when asked if he could envisage to deploy WaveSense’s technology into fleets of autonomous vehicles being trialled or tested extensively on the country’s roads. He anticipates that the final product design could be shrunk to a 67x30cm plate about 3cm thick, to be fixed underneath the car.
According to Bolat, success in deploying autonomous vehicles will all be down to safety, and WaveSense is precisely trying to create a valuable brand around safety. “It is all about the utilisation rate of vehicles. The ride-hailing market needs autonomous vehicles able to operate even in very inclement weather” concluded the CEO, referring to fog and snow covered roads where visual markings can’t be relied upon.
WaveSense - https://wavesense.io