The advancement of autonomous vehicles is here now!

The advancement of autonomous vehicles is here now!

The head of on-road strategy and marketing at Trimble Autonomy, Louis Nastro, of Trimble, explains why autonomy on your terms is crucial for today's and tomorrow's cars. Trimble Autonomy is in the driver's seat when it comes to resolving manufacturers' problems with autonomous and semi-autonomous vehicular systems because it already has millions of miles of real-world data available and is being utilized to support safety-critical applications. Here, Louis Nastro of Trimble outlines the problems that exist today and how the best solutions revolve around gathering the appropriate data, synthesizing and evaluating it, confirming its accuracy, and relaying it to the vehicles at the appropriate time. Automotive OEMs and key suppliers are moving quickly because they understand that obtaining high-accuracy positioning and orientation in support of safety-critical applications will be at the heart of the roadmap for autonomous vehicle growth. Continue reading as Nastro gives a brief overview of the industry's past, present, and future for autonomous cars and trucks.

What is essential for automakers and the general public to successfully adopt self-driving cars and trucks on a large scale?

The data are everything. It is impossible to emphasize the value of accurate positioning. And you cannot do this without focusing on the data. OEMs and Tier 1 and Tier 2 suppliers support this idea. Focusing on every data point possible requires gathering, evaluating, and validating data before communicating the conclusions to the systems and individuals who require them, when they require them, and according to their conditions. Consider the vast amount of data you receive from land mapping, radar, lidar, vehicle sensors, smart roads, etc., and how you must combine data sets by obtaining and integrating real-time and near-real-time data. The systems and software in vehicles must evaluate this data, translate it from the physical world into the digital world, and then translate it back into the physical world. Vehicles must map as they travel.

What lessons has Trimble learned that can securely expedite the auto industry's transition to autonomy?

About 20 years ago, when we first started down the road to autonomous vehicles, we believed all that was required was the safe transportation of a vehicle from point A to point B. However, it wasn't enough. We are now putting the data first. We came to understand that the car is a mobile mapping system that continuously records data about its surroundings. Therefore, our attention was on examining and describing all of that geographic data. We now consider cars and trucks to be more of a high-definition mobile mapper than just autonomous vehicles. This change in direction encouraged us to pose new queries and come up with fresh concepts.

We have provided high-precision positioning systems to the automobile industry for more than 20 years, and many top OEMs and top-tier suppliers make use of our technology. Being experts in automotive autonomy is not enough for us. The transportation, geospatial, agriculture, and construction businesses of Trimble have all given significant data that is used to create solutions for automakers to address autonomy-related problems. Unsurprisingly, data-based solutions are virtually usually at the core of the solutions. And we use our cross-platform toolbox of hardware and software to meet the mobility needs of our clients.

Vehicles produce a large amount of data and knowledge. How does this help drivers?

First and foremost, keep in mind that the next mile that a driver is about to travel is what matters most to them. You enter the room by carefully choosing your position. Systems using global positioning satellites (GNSS) are widely used. To give our integrity monitoring solution's client—and ultimately, the user in the vehicle—assurance that the reported result matches the precise vehicle location, we need to make sure that a very precise solution is qualified from both an Automotive Safety Integrity Level (ASIL) certification standpoint and a technical standpoint.

Naturally, automobiles have a variety of sensors in their onboard systems. However, it can be a serious problem if there is a driving snowfall and your radar stops working, your ultrasonics stop working, for example, or if they become blocked with road grime, snow, and ice. Everything we've learned so far has helped power a system that enables drivers to rely on existing data to constantly locate lane-level locations as we advance in our gradual march toward autonomy. You will still be able to locate yourself even if your sensors aren't working. To perform real-time quality assurance and quality control with both online and offline operations, it is essential to quantify, collect, and qualify data, as well as to ensure the integrity of maps and other types of data.

In addition to a precise location, we also stand out thanks to our other value packages. With the help of real-time online and offline procedures, the Trimble system offers sensor fusion, qualification, calibration, and the capability to transform all that data into useful insights. In other words, the relevant information, when evaluated correctly, enables drivers to always be aware of their whereabouts.

What does the road plan for autonomy look like in the future, and how does Trimble fit in?

With accurate placement, Trimble's onboard procedures can already direct moving vehicles. The future, though, is in the data leverage points. This technology's main evolutionary feature, especially as sensors advance significantly more over the next five years. Consider the things your smartphone accomplished using 2G technology, then consider the possibilities presented by 5G. In our industry, everything is moving at a breakneck pace. We'll receive additional data products as there is more data available. A road will be examined thousands, if not millions, of times every day rather than just once.

We are making use of both what is happening within the car and outside of it. There are a lot of moving pieces, including the way radar and lidar, and camera data are employed. What image resolution are they? Do we have enough sensor data overlap to protect from issues? What are the results of the data? We are in a unique position to use that information to our clients and their consumers' advantage both now and in the future.

Do we already have a glimpse of that future?

Definitely. A portion of that future is already in motion. The Trimble RTX Integrity monitoring system, which we recently developed, regularly verifies the accuracy of corrective data processed by the pertinent GNSS network. To guarantee that location data is accurate the first time around, this is then transmitted to users in the agriculture, GIS, construction, and automotive industries. The RTX Integrity system verifies repairs data in the network server before the data is broadcast using a special two-step procedure. The entire data-transmission process is also subjected to a further post-broadcast examination, which can find and fix additional mistakes. To deliver an even more highly precise and dependable location, the integrity monitoring system is entirely automated and responds in only seconds to detect, isolate, and block incorrect data.

How does the modern system function?

Independent monitoring stations for RTX Integrity are placed strategically throughout the RTX Fast networks in the United States, southern Canada, and Europe. These stations keep an eye on the output of data throughout several RTX placement steps. During the integrity-protection procedure, any questionable satellite data is eliminated, and location is calculated solely using verified data. The independent monitoring stations are powered by Trimble Alloy GNSS reference receivers and utilize redundant internet connectivity for increased dependability. No other positioning network, as of yet, provides the same level of data-integrity verification across such vast and connected regions. The development of new parallel technology that uses our geospatial heritage to demonstrate to the industry what is possible lends credibility to our history and previous innovations in addition to those that have already taken place.

What does Trimble's future look like in the next five years?

Not just for passenger cars, delivery trucks, and other types of vehicles, shared mobility is our main focus. Last-mile delivery vehicles will also be crucial. Particularly in light of the severe driver shortage, which only increases the need for autonomous systems and services and, in turn, increases the requirement for improved safety solutions, we are looking at evolving various use cases. As a result, we are also emphasizing vehicle surveillance while they travel their routes and on-board and remote piloting. The focus of the near future will be on gathering and combining more information from various sensory inputs, with a focus on location awareness. Furthermore, it goes beyond simply being the most accurate. Due to the necessity of standing by your findings, the integrity monitoring component will continue to be crucial.

Naturally, for Trimble, it's all about the demands of the client and how we can address their problems. We accompany them on every leg of their journey. Facts and data are important. Where we excel is in that. Our clients are aware of the quietly confident corporation that Trimble has always been. We consider ourselves as the professionals who get the job done - and so do our customers and partners. As a result, when we conduct collaborative and consultative work for the industry, it's focused on domain expertise and "simply the facts." They are aware that the key components of autonomous and semi-autonomous mobility solutions are found in the undercarriage, chassis, and central nervous systems of vehicles.

Delivering autonomy on our partners', clients', and drivers' terms is what the next five years are all about. We are certain that we will continue to provide for OEMs and leading suppliers wherever they are on the future road.