Autonomous Trucks can Help Address Industry Challenges

IDTechEx examines the benefits automation can bring to the trucking industry, such as helping overcome the growing driver shortage.

IDTechEx Research
DTNA is working with Torc Robotics to develop and test autonomous trucks.
DTNA is working with Torc Robotics to develop and test autonomous trucks.
Daimler Trucks North America

Implementation of autonomous technology can offer many opportunities to the trucking industry. The IDTechEx report “Mobile Robots, Autonomous Vehicles, and Drones in Logistics, Warehousing, and Delivery 2020-2040” analyzes various aspects of autonomous trucking. It outlines the latest trends and developments, discusses the remaining challenges and development opportunity, and offers a long-term market perspective and forecast.

This report offers a detailed analysis of technology, markets, and players active in using autonomous mobility across the entire logistic and delivery value chain. This includes autonomous robots in factories and fulfillment centers, autonomous industrial vehicles such as forklifts, autonomous trucks and vans, and last mile delivery pods, robots, and drones.

Structural pain points

The trucking industry is suffering from multiple pain points, one of which is the shortage of long-haul drivers. The American Trucking Association estimates that the U.S. industry alone currently suffers a shortage of 60k drivers. This is forecast, based on current trends, to rise to 160k drivers by 2028. Clearly, this acts as a limiting factor constraining growth.

The addressable market is also significant. In the U.S., it is estimated that 1.9M people are employed as heavy and tractor-trailer truck drivers. The average salaries are around 41.3k$/yr. As such, the amount spent on driver wages each year in the U.S. alone is $78 billion. In time, this colossal sum can be transferred from wages to technology and service costs offered by autonomous truck developers.

ZF's Innovation Truck includes several automated systems aimed at improving safety.ZF's Innovation Truck includes several automated systems aimed at improving safety.ZF

Unlike the case in private autonomous cars, there exists a clear commercial incentive. Furthermore, there are early hints that autonomous driving can optimize fuel consumption, e.g., 7-10%, and also reduce tire damage.

Finally, there is the question of safety and asset utilization. Currently, driving hours are constrained by regulation in order to boost safety, which is a major challenge. According to statistics from G7, the largest commercial vehicle management platform in China, there is a major vehicle accident in every 25 logistic vehicles per year. This limits asset uptime. It is hoped that autonomous driving can increase safety and asset uptime.

Autonomous mobility has thus the potential to address many clear pain points. So the question is, what is the technology and commercial status, and what does the future market deployment look like?

Starting from highways

Trucks are already equipped with higher levels of ADAS function. For example, Daimler is now offering cruise control on 100% of its trucks. When it comes to higher levels of autonomy, two different routes are being taken.

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Multiple firms are developing technology to first automate highway driving. The argument here is that highways are simpler environments in relative terms compared to chaotic urban driving. The roads can often be long and straight, especially in large parts of the U.S. This relaxes the challenge in autonomous driving. On the other hand, the speeds are high, and the braking distances are long, e.g. 100 m. As such, the perception technology will need to see much further ahead than might be the case with cars. This places additional requirements on the sensor suite technology (radar, lidar, camera, etc), as well as the software. This requirement will likely lead to different technology choices compared to cars. Furthermore, the vibration levels on ICE trucks, likely used in long-haul, are more severe, placing further challenges on long-term component reliability, especially if mechanical non-solid-state solutions are deployed.

In addition, there is a challenge of what to do when the truck is about to enter the more chaotic urban environment. Various solutions have been proposed, including humans taking over at change-over centers located near the city edges. The argument here is that fewer drivers will be needed given the shorter trip times in the final miles and that more drivers are likely to be available since it is not long-haul. As such, this arrangement will still reduce the payroll burden and help alleviate the driver shortage challenge. Teleoperation will likely also play a role at this stage.

The business model choice is also interesting. Some are developing the technology, hoping to sell it as an autonomous vehicle. Others are proposing to offer the fleets in a transport-as-service model, charging perhaps 40-50 cents per km driven. The latter will likely result in a lower barrier to purchase, as well as faster time-to-market and generated income. It will also offer the chance to gather data, iterate, and improve the design especially the software. It will, however, require sufficient funding to absorb and maintain the cost and risk of autonomous trucks on the provider’ books, which can be a challenge for start-ups grabbling with high development costs. The former model will resemble the classic car-sell model. However, it will represent a larger barrier to purchase, as many truck fleet operators have geared their finances to service their operating costs and will not easily be able to muster up enough capex to pay for the currently much higher cost of autonomous trucks. The solution will likely reside in innovative financing offered by major manufacturers.

Starting closer to home

The other approach is to start in very constrained environments. For example, TuSimple has suggested that in China it is focused on low-speed autonomous solutions for port logistics. Einride is also focused on low-speed transport between a warehouse and terminal. The roadmap is to go from fenced to nearby environments (already done) before graduating the technology to rural, then highway, and then final urban.

The idea here is that low-speed operation in a controlled environment lowers the technological complexity, thus cutting down the deployment challenges and time. It will provide, nonetheless, a chance to deploy a fleet, which in turn allows the business model to be refined, the value proposition to be demonstrated in collaboration with a customer and in a real scenario, and the software stack iterated and upgraded to achieve better results.

TuSimple and ZF recently announced a partnership to co-develop components to create autonomous trucks.TuSimple and ZF recently announced a partnership to co-develop components to create autonomous trucks.TuSimple

Read more: TuSimple Partnering with ZF on Development of Autonomous Trucks

These conditions have allowed the design of truly driverless trucks from the bottom-up. As such, the autonomy level is high. Currently, there are teleoperators remotely monitoring and controlling the driverless trucks. The key to making commercial sense is that the fleet size to teleoperator ratio be made as large as possible, e.g. >>10. This requires technological innovation, especially better autonomy and safety at the vehicle level, which would translate into lower required intervention numbers by the teleoperators.

The decision to start from low-speed constrained environments allows limited trip distances. This, in turn, will enable the deployment of fully electric trucks. They are easier to design and control as the system is electric. Given the lower part numbers and increasingly modular traction platforms, it aids designs of novel form factors. It will, however, require better route planning to best utilize the battery and to minimize charging downtimes. The trend towards electrification in light commercial vehicles, as well as heavy-duty trucks, is very significant. 

The short- and long-term outlooks

The chart below shows the current status and outlook. Today, the accumulated fleet size is still small. Essentially, the suppliers as well as the end users are jointly learning. There are multiple projects live across the world. Some companies have recently failed, e.g. Starsky as expected, but new ones, especially in Europe where there is a gap, are expected to form. 

Overall, there is a market pull for autonomous driving. The realization is in this case largely technology limited. This cannot be said about every sector which autonomous mobility seeks to penetrate. In some cases, it is a technology looking for a problem.

IDTechEx assess that the market will remain in the learning phase until 2024. Within this time accumulated fleet sizes will certainly increase, but the character of the market will be one of early deployment and learning. Level 4 autonomy in certain highway conditions and teleoperated or telemonitored driverless low-speed trucks in constrained environments will take off likely beginning from 2024. True level 5 will take long. The research firm currently estimate that this will require longer than a decade realize. By that time, however, level 4 (or teleoperated driverless trucks) will also have made a significant impact, representing more than 20% of annual truck sales.

In the end, this is a colossal transition that simply cannot be ignored even in the current climate of cash flow challenges in the industry.