Photo: Steve Jurvetson. Uber acquired startup OTTO to lead its autonomous vehicle efforts.

Synopsis by Kyndall Krist


In 2016, the American Transportation Research Institute’s (ATRI’s) Research Advisory Committee (RAC) ranked “Analysis of Autonomous Truck Impacts” as its top research priority. Autonomous vehicle (AV) technologies have the potential to dramatically impact nearly all aspects of the trucking industry. A fully autonomous truck will have the ability to identify, interact with and safely react to all aspects of the driving environment without a driver in control of the wheel.

In this study, ATRI’s research objectives included offering background on the current state of AV technologies as well as outlining the impacts of autonomous truck (AT) deployment.


Autonomous Vehicle Scale

ATRI stresses the importance of understanding the different levels of autonomy, each of which comes with different technologies, functionalities and expectations. The following list illustrates the six different categories of autonomous vehicle systems, defined by the Society of Automotive Engineers (SAE).

  • Level 0 (L0) No Automation: The driver does everything. Large trucks have traditionally been in this group.
  • Level 1 (L1) Driver Assistance: An automated system on the vehicle can sometimes assist the human driver in conducting some parts of the driving task. Examples of technologies that fall into this category would be electronic stability control and adaptive cruise control.
  • Level 2 (L2) Partial Automation: An automated system on the vehicle can conduct some parts of the driving task, while the human continues to monitor the driving environment and performs the rest of the driving task. When two or more L1 systems work together, such as collision mitigation systems, the vehicle falls into the L2 category.
  • Level 3 (L3) Conditional Automation: An automated system can conduct some parts of the driving task and monitor the driving environment in some instances, but the human driver must be ready to take back control when the automated system requests. An example of this level would be the Freightliner Inspiration Truck, which can operate autonomously with close driver oversight.
  • Level 4 (L4) High Automation: An automated system can conduct the driving task and monitor the driving environment, and the human need not take back control, but the automated system can operate only in certain environments and under certain conditions.
    • Ottomotto LLC (now owned by Uber) tested this technology, letting the driver set the delivery vehicle on autonomous mode for the 120-mile highway route. Once activated, the driver entered the truck’s sleeper berth area and remained there for the rest of the interstate travel. While this was a well-planned event and was monitored by a police cruiser, it demonstrated that L4 technology works and could be available to motor carriers in the future.
  • Level 5 (L5) Full Automation: The automated system can perform all driving tasks, under all conditions, that a human driver could perform. Although a driver is not required for an L5 truck to move from an origin to a destination, it does not mean a driver would not be on-board or necessary. Commercial drivers would be responsible for a number of critical freight movement tasks beyond maneuvering the vehicle.


Technologies that Enable Automation

Vehicle automation is predicated on a variety of technologies that allow for different levels of functionality and capability. The following list describes the technologies most commonly associated with autonomous vehicles:

  • Radar utilizes several specific radio frequencies to provide continuous monitoring of distance (and to some degree, object size) by measuring the time it takes the radio waves to travel to an object and back. In a trucking application, sensors are installed on the front bumper area of the vehicle, utilizing both long- and short-range radar.
  • LIDAR is a concept similar to radar that uses lasers (instead of radio waves) to collect information about the surrounding environment. While LIDAR has distinct advantages over radar, the “size, weight, cost and power consumption” of the equipment has hindered adoption.
  • Video camera systems are utilized to read signs, roadway striping and other features of the surrounding transportation infrastructure and environment. Current video camera applications aid truck drivers in maintaining lanes and warning of a possible collision with both vehicles and pedestrians. In an AT, the same functions may exist, but would be automatic.
  • 9 Dedicated Short-Range Communications (DSRC) is a specific range of the 75 MHz spectrum that was set aside by the Federal Communications Commission (FCC) in 1999 for use in intelligent transportation systems. Since 5.9 DSRC only has a range of up to 1,000 meters, embedded DSRC transceivers are needed approximately every quarter mile to ensure continuous connectivity. While the DSRC range is short, the 5.9 GHz frequency permits very fast data transmission rates.
  • 4G/5G Long-Term Evolution (LTE) is a high-speed wireless communications platform that is most commonly used by smartphones. The next generation of this terrestrial platform is often called 5G LTE. The 5G platform is expected to be “10 – 100 times faster than today’s average 4G LTE connections,” and could enable cellular communications to support collision avoidance and truck platooning. While capable of operating over a much longer range than 5.9 DSRC, 4G wireless communications have a slower rate of data transfer.
  • Differential Global Positioning System (DGPS) builds upon Global Positioning System (GPS) by adding ground-based correction stations that act as a third reference point between the vehicle and a GPS satellite. This increases accuracy from within several meters to several centimeters. Such accuracy, if employed in real time, could help maintain a travel lane when markings are missing.


Projections, Timelines and Costs

The level of research and development (R&D) investment in autonomous vehicle technology will likely drive the speed at which L3 – L5 vehicles enter and replace the existing U.S. vehicle fleet. In January 2016, the U.S. Department of Transportation (DOT) made a commitment to autonomous vehicle research with the announcement of “a 10-year, nearly $4 billion investment to accelerate the development and adoption of safe vehicle automation through real-world pilot projects.” The intent of this investment is to support the ongoing work of the private sector.

Regarding AT projections and timelines, IHS Automotive states that “autonomous truck sales could reach 60,000 annually by 2035 [or] 15% of sales for trucks in the big Class 8 weight segment.” There are currently 3.46 million Class 8 trucks in the U.S. If, hypothetically, 60,000 autonomous trucks were added annually starting today (instead of 20 years from now), it would be more than five years before ATs made up 10% of the total fleet. Thus, the IHS prediction does not see rapid adoption in the shorter term.

The cost of trucks with autonomous systems will be greater than a standard truck. Since there are no commercially available systems at the time of publication, estimates are relied on for this report. For the OTTO retrofit and the Freightliner Inspiration, a figure of $30,000 per truck automated systems cost has been published. One report looked at costs incrementally, and estimated that additional costs per truck for hardware and software would be as follows:

  • L3: $13,100 added to truck price
  • L4: $19,000 added to truck price
  • L5: $23,400 added to truck price

These costs are mainly related to software, and do not include inspection, maintenance or updates. As these technologies become more widely adopted, prices are likely to decrease. At the moment, due to numerous unknowns related to software investment needs and industry regulations, an accurate return on investment (ROI) analysis is not possible.


Government Impediments and Catalysts

In addition to public impediments and catalysts, the ATRI report provided a range of government impediments to AT deployment, along with potential solutions. It noted, for example, that state law and federal motor carrier safety regulations have not yet begun to address autonomous environment. In fact, many rules within the Federal Motor Carrier Safety Regulations (FMCSRs) conflict with or do not address autonomous trucks. This will require a major overhaul of state laws pertaining to commercial vehicles as well as the FMCSRs.


Impact of Autonomous Trucks on the Trucking Industry’s Top Issues

ATRI annually conducts a survey of motor carrier executives and commercial drivers to identify the industry’s top issues. ATRI’s autonomous vehicle report goes into detail regarding how ATs and AVs impact the trucking industry with emphasis on 2015’s top 10 concerns. The following list summarizes the top 10 issues and the key autonomous truck benefit for each.

  • Hours of service: Allows for driver rest and productivity to occur simultaneously.
  • Compliance, safety, accountability: Will decrease raw SMS scores, though percentile scoring needs to change.
  • Driver shortage: Driving is more attractive with higher productivity, less time away from home and additional logistics tasks. Fewer drivers may be needed.
  • Driver retention: Companies with autonomous technology may attract and retain drivers.
  • Truck parking: If “productive rest” is taken in the cab during operations, less time will be required away from home at truck parking facilities, and fewer facilities will be needed.
  • Electronic logging device (ELD) mandate: Modifications will be necessary depending on level of autonomy.
  • Driver health/wellness: The driver could be less sedentary and injuries could be reduced.
  • The economy: Carriers that use AT may see productivity and cost benefits.
  • Infrastructure/congestion/funding: Urban congestion could be mitigated through widespread use of AVs (including cars).
  • Driver distraction: Drivers will not be distracted from driving if the vehicle is in autonomous mode.



Autonomous truck technology is on a course that will fundamentally change the trucking industry. Shifts of this magnitude do not come often, and may prove to be as momentous as the building of the Interstate System and deregulation.

The technology to demonstrate L3 – L5 operations exists today, though motor carriers do not currently have access to AT systems. That will change in the coming years as systems are further developed and commercialized. Individual motor carriers, and the trucking industry as a whole, can use that time for planning an approach to this technology, both in terms of regulatory and operational changes.

For carriers, there are still many unknowns, particularly the ROI. On the investment side of the ROI equation, there is only a sense of what the current “demonstration” systems cost. There is a fair amount of speculation as well. The technology is in a pre-deployment stage of development, and with no clear price points it is difficult to assess value to ATs. The industry understands that whatever the initial price is, per-unit technology costs do tend to decrease with widespread adoption.

On the benefit side, the two critical positives are productivity and safety. With changes to the FMCSRs, particularly though an adaptation of the hours of service for AT users, there is the potential that individual over-the-road drivers will be able to operate in what is essentially a team environment. The systems will operate the vehicle during interstate travel while the driver rests, and the driver will take over on secondary roadways. The elimination of human error-related crashes also has the potential to save the industry billions of dollars annually.


You can download a full copy of this report on ATRI’s website at

ATRI is the trucking industry’s 501c3 not-for-profit research organization. It is engaged in critical research relating to freight transportation’s essential role in maintaining a safe, secure and efficient transportation system.

Source: “Identifying Autonomous Vehicle Technology Impacts on the Trucking Industry,” American Transportation Research Institute. November 2016.