By: Kevin Andrews
Interest in autonomous technology is growing for both on-road and off-road applications. As the promise of self-driving cars draws nearer, consumers are interested in how autonomy can improve safety both in and out of the vehicle. Meanwhile, off-road vehicle operators’ interest is sparked by autonomy’s ability to mitigate challenges such as labor shortages, tough terrain and rising fuel costs.
Smart off-road equipment sales are projected to grow 35% in 2022 and then more than double by 2026.
Source: Freedonia Group, April 2022
Across both applications, autonomy encompasses a variety of degrees and functionalities—especially in off-road vehicles that take on tasks like compacting soil or spraying crops. When it comes to defining autonomy, there’s no single meaning. Here are some common questions we get: “Is automation the same as autonomy?” “Is it driver assistance?” “What about a connected worksite or command-and-control system?”
At Trimble, the short answer is “yes.” Autonomy includes all these points on the journey to more intelligent and efficient workflows—plus many more.
By 2024, the global autonomous vehicle market will be worth some $400 billion USD. In advanced economies, highways will be nearly driver-free by 2050.
Source: Statista, June 2022
The Society of Automotive Engineers has defined five levels of autonomy which are widely accepted. These are through the lens of the driver/operator of autonomous passenger vehicles.
They are:
- Level 1: driver assistance, everything on
- Level 2: partial automation, hands off
- Level 3: conditional automation, eyes off
- Level 4: high automation, mind off
- Level 5: full automation, steering wheel optional
This framework works well when your goal is to get a vehicle from point A to point B. But for off-road operators in industries like mining, agriculture and construction, navigating and steering a vehicle is only a small part of the workflow and rarely the end goal.
As a technology partner across a range of industries, Trimble has many other ways to measure the success of autonomous applications. One important way is by the volume of work done—this could be the amount of earth moved, the number of acres fertilized, or how many simultaneously occurring complicated tasks an operator must perform or oversee.
Farmers consistently using precision ag technologies saw a 4% increase in crop production, with an additionall 6% productivity gain achievable with full adoption.
Source: Association of Equipment Manufacturers, Feb. 2022
The five levels still apply, but for the off-road space, it’s helpful to think of a series of stages:
1. Operator Assistance
The operator or driver relies on a light bar or visual indicator to provide real-time information on where the vehicle or implement should be. This guidance informs decision making and improves efficiency. Examples include collision warning or notification of an object within the path.
2. Task Automation
A smart system can automatically complete a component of the job. Tasks that are currently being automated include blade control on a dozer, variable spraying rate on a tractor and lane keeping across a range of vehicles.
3. Supervised Autonomy
This is a higher level of automation where the operator is in a supervisory role but still responsible for reacting to unexpected conditions. The Horsch sprayer and Dynapac soil rollers each demonstrate this level of autonomy.
4. Full Workflow Automation
The end goal of fully autonomous capability and full workflow automation includes high-level reasoning and adaptive behavior of unmanned vehicles, optimizing for business needs and/or operating without direct supervision on site. Full autonomy can be giving a vehicle or machine a task for efficient and safe completion, as well as enabling full site autonomy, e.g., a connected worksite, TC1 or connected farm.
Autonomous vehicles boost mine productivity by 30%, due to longer production hours and improved tire life.
Source: Foundamental, February 2022
Trimble views autonomy not as a stack of technologies, but rather a matrix of capabilities that may fit into subgroups like “perception” and “control systems.” Within these groups, there are many separate and distinct building blocks. Detecting an object on a machine’s path is not the same as classifying a scene for path planning. The importance of each building block capability, or node in the matrix, varies according to the stage as defined above, the complexity of the task and the environment itself.
At Trimble, we recognize not all applications of autonomy need the same capabilities at the same pace or with the same scale. As we continue to develop new solutions—all built within our market-leading platform—and expand our reach, we’re better able to offer our clients and partners a range of solutions and capabilities to meet them wherever they may be on their journey to autonomy.
Header image: Trimble
This page was produced by North Coast Media’s content marketing staff in collaboration with Trimble. NCM Content Marketing connects marketers to audiences and delivers industry trends, business tips and product information. The GPS World editorial staff did not create this content.