Building the Future

How Autonomy Can Reshape Construction

By Adam Khaw, Head of Autonomy, Danfoss Power Solutions

The construction industry is currently facing a labor shortage that’s forecasted to intensify over time. According to the Associated Builders and Contractors (ABC), in 2025 the industry will need to recruit an estimated 454,000 new hires on top of the normal hiring pace to meet labor demands. ABC cites several causes for the shortage, including “outsized retirement levels, megaprojects in several private and public construction segments, and cultural factors that encourage too few young people to enter the skilled construction trades.”

Looking deeper into the first factor, over 20% of construction workers are over 55 years of age. Their impending retirement means the loss of job site headcount and experience. The result is fewer workers overall and less experienced workers operating machinery, which could lead to higher rework and decreased productivity levels.

By transitioning the skill and experience an operator would typically demonstrate onto the machine, autonomy can provide a solution for the lack of skilled labor in construction. The productivity of the machine and the operator is amplified while precision tasks are performed faster and more accurately. Autonomy is ideal in any off-highway sector seeking to increase safety, boost productivity, and enable greater precision.

Before digging into how autonomy delivers these benefits, let’s clarify what is meant by autonomy in the off-highway machine industry.

Defining Autonomy

Many discussions around autonomy focus on self-driving vehicles. The reality is more nuanced and there are important distinctions between autonomy in on- and off-highway vehicles. In passenger cars and trucks, the goal is to automate the vehicle. In off-highway machines, the goal is to automate the tasks the vehicle performs. The more automated tasks are, the more autonomous the vehicle appears.

When it comes to off-highway machinery, five defined levels of autonomy differ slightly from the levels of autonomy in passenger vehicles. The levels of off-highway autonomy are:

Level 1: The driver controls most functions, including specific operations such as steering; these can be taken over by the machine at the operator’s discretion.

Level 2: In certain settings, the machine can steer, accelerate, and brake while the operator is still directing and monitoring the action of the vehicle; this lightens the operator’s load while still  engaging them in driving.

Level 3: More complex actions are controlled and executed by the machine. In the right conditions, a machine can manage most driving aspects, including monitoring the environment. This allows the operator to control other implements on the machine and steer their focus away from driving for short durations.

Level 4: The machine can operate without human input or oversight, and multiple autonomous machines can work together on one site.

Level 5: The machine can operate without human input or oversight, but it can be controlled off-site; this is known as unsupervised autonomy.

When people think of autonomy, many think of driver-less or cab-less machines. While autonomous machines do exist today, they are often expensive and intricate; as a result, they have yet to fully penetrate the market. In the next 15 or 20 years, this reality may shift. For now, the state of the art is semi-autonomous functionality that increases machines’ ease of use and precision — in other words, level 3 autonomy. These machines enhance job site productivity and safety, even when staffed with a brand-new operator.

Autonomy in Construction

While other off-highway sectors, such as agriculture, have relatively advanced autonomy, construction could see rapid development as new workers enter the industry. As previously mentioned, autonomous and semi-autonomous functionality improves safety, productivity, and precision, regardless of operator experience. In construction, this will lead to reduced rework and faster job completion.

Hyper-repetitive tasks are ideal candidates for automation. In construction, rollers and compactors are good examples. Soil compaction and asphalt rolling require highly skilled operators. Costly rework or accelerated road deterioration may result if these tasks are not done properly. By using autonomous functionality, these machines can compact soil or roll asphalt with proper overlaps and accuracy regardless of who is behind the wheel. In addition, an operator in a tandem roller with a limited field of view can be more aware of their surroundings.

Development efforts focused on obstacle detection and avoidance are particularly relevant in construction due to large machines experiencing significant blind spots. Accidents still happen even today when a driver doesn’t see someone standing or working near a machine. Damage to nearby structures is also common. Collisions can be prevented by adding obstacle-detection functionality to machines.

Path recording and following is another example of semi-autonomous operation relevant to construction. Such functionality is ideal for pipeline and power line work as well as other applications in which a machine needs to follow a long stretch of road or ground. This functionality enables an operator to drive a path while recording speed, waypoints, and tasks the machine does. A less experienced operator can then manage the machine as it follows the recorded path.

Blind spot detection has proven successful in construction, along with semi-autonomous functions that help inexperienced operators rely on the machine. Many original equipment manufacturers (OEMs) in the construction industry have introduced advanced operator-assist features that keep operations consistent and repeatable. Auto-grade and auto-dig in excavators, along with boom kick-out and bucket positioning in wheel loaders are all examples of existing functions on job sites. Automation of precise tasks that would otherwise require the effort of skilled professionals is an ideal area that would benefit from continued development.

Autonomy in construction is ultimately about finding the right use cases. In relation to the previous example of automating repetitive tasks, solar farm construction would be an ideal candidate. Solar sites require numerous post placements at precise intervals. On megaprojects, haulers could be automated if they operate solely within the confines of the site. This would mimic quarrying or mining, where rock haulers transport loads from excavators to a rock crusher or conveyor system. Two haulers and one excavator could be operated simultaneously by a single operator who would record paths in each dump truck and oversee all trucks while operating the excavator.

Engineering Future

Autonomy has the potential to unlock significant construction industry advantages, making the choice to use machines with autonomous functionality an easy one for contractors. For OEMs, however, automating machines can be complicated. The process presents new challenges pertinent to software and hardware. Autonomy requires perception sensors such as lidar and radar, global positioning, high-power processors, and other technologies that may be new to design engineers. These technologies are not plug-and-play, and the sensors are not one-size-fits-all. Applications and environments have unique needs that demand different solutions. A significant amount of engineering work is required to integrate these devices and services into a system.

Another challenge is knowing exactly what and how to automate. Single-use machinery such as soil compactors that perform repetitive tasks are relatively simple and straightforward to automate. Having said that, many types of construction machines are multifunctional. Skid steer loaders, for example, can perform many operations. Excavators are also highly versatile, meaning many possible tasks can be automated. In addition, construction machinery often operates in complex, dynamic job sites rather than one static environment, making autonomous operation more of an obstacle.

Autonomy offers a great deal of potential and many exciting engineering possibilities. The responsibility falls on OEMs to identify problems that need to be solved at the ideation phase in the design process. This requires collaboration with product, systems, and software teams, as well as autonomy experts before any lines of code are written. Larger OEMs have an advantage with their established in-house teams focused on solving engineering challenges. With the construction machinery market dominated by several large OEMs, smaller and mid-sized OEMs risk falling behind.

As autonomy evolves, many suppliers and systems integrators offer solutions for automating machines. The Danfoss autonomy team, for example, offers products and services that support the full machine development cycle, including software, hardware, and engineering services. By building upon a foundation of field-tested solutions, smaller OEMs can remain competitive in a rapidly evolving industry and position themselves for the future of autonomous machinery.

In conclusion, contractors should be proactive in considering machines with autonomous functionality, and OEMs should determine whether adding this functionality to a machine will enhance its value to end-users. Navigating the complexities of integrating autonomous solutions requires strategic planning and collaboration, but the potential benefits for both OEMs and the industry at large are significant and worth the time investment. Workforce development alone cannot solve the construction industry’s pressing labor shortage. Technology, such as autonomy, can help bridge the gap and help contractors achieve more with fewer resources.