AI-powered PNT with situational awareness will be the difference in winning or losing on the battlefield. PNT is integral to our everyday life: mapping, mining, farming, etc. BlueSpace Positioning System (BPS) debuted at CES 2024 with its best-in-class CTE (<0.3% drift error) in GPS-denied areas. BPS is powered by our AI engine to provide not only accurate positioning but also situational awareness and mapping.

“This incident was unique..” says Cruise. Was it though? Not for us.

They can call it “rare” or “unique” and that special circumstances led to the failure mode, to BlueSpace it’s all the same. It is the case of getting to accurate motion consistently, reliably, and generically.

“Failure to realize a long-term, aspirational goal” seems to be the verdict for conventional approach to autonomy. Ford and Volkswagen threw in their towels and stopped funding Argo.ai’s autonomy efforts. There is one common thread across this, the time and capital expenditure of chasing one edge case after another. Failure to see is not only an unrealized goal but it is a fatality with no recourse. That’s why BlueSpace presents a robust and scalable solution that can work alone, or provide a redundancy for an existing software stack. Given the holidays, we didn’t want to be macabre, so we share a light-hearted yet poignant example of what failure to see for AVs could result in.

Just as several AV companies have started small scale deployments, there’s been declining confidence in the future of AVs - “USD100Bn invested, nothing to show for it” has been the rhetoric. Coincidence? We think not.

In the past few months, there have been several reports of AVs malfunctioning to the point of holding up traffic for hours or worse, getting into accidents. This begs the question, are AVs ready to share the road? 

Whether it’s Tesla’s L2 autopilot, FSD, or Mercedes L3 that’s driven millions of miles, the question that inevitably pops into anyone’s head stepping into the vehicle is, will my mile (or kilometer for the rest of the world!) in the car be safe? The track record does raise eyebrows…

In the US every year, there are 1-2 million deer vehicle collisions (“DVC”) (source: Freakonomics). The result: hundreds of deaths, tens of thousands of injuries, and billions in damages. Of course if you had a $185,000 Bentley that is equipped with ADAS (Advanced Deer Alert System) you should be able to potentially dodge that deer collision. If you’re in Australia, kangaroos are the biggest danger, making up 90% of animal-vehicle collisions (source: Mashable). Of course, there is an ADAS solution for that too - enter kangaroo detection vehicle!

A company’s definition of diversity will always vary. Diversity is not only defined by race, age, religion, or ethnicity. It can also be defined as varied perspectives, differing experiences and multiple approaches to the same problem. What diversity gives to an organization is monumental. Studies have shown that companies with greater diversity in their teams are +30% more likely to financially outperform their industry peers (McKinsey & Company). At BlueSpace, we aim to enable autonomy for all, by providing software that works across various modes of transportation - private passenger vehicles, public transportation, and more. Solving for scalability and accessibility of autonomy can only be done by building a diverse team.

BlueSpace was created with the thesis that improving the reliability and accuracy of perception will unlock autonomy and unleash commercialization, adoption, and trust in the technology.

Our last blog [link here] discusses how BlueSpace's industry-leading motion accuracy software is critical for safe and scalable ADAS/AD applications.

What the Current Metrics Tell Us

In our last post, we shared how BlueSpace is accelerating autonomy with our motion first approach to autonomous perception. Our 4D Predictive Perception’s ability to measure the true motion state of all objects in all environments provides the AV/ADAS stack a level of motion accuracy previously not possible through traditional deep learning approaches.

AV Journey

Since the original DARPA Grand Challenge in 2004, millions of miles and billions of dollars have been funneled into self-driving systems, yet none have managed to reach scale. Robotaxi services are confined to small subsections of cities and autonomous trucks still utilize safety drivers on some sections of highways. Even in off-road environments such as mining, where autonomous equipment has been deployed for years, it is estimated that under 5% of vehicles operate autonomously.