Literature Reviews

When electrified, automated heavy-duty trucks can have dramatic reductions in air pollutant emissions that harm human health. A lifecycle analysis study found that the health impact costs of an automated diesel heavy duty truck were twice that of an automated electric heavy-duty truck, and that the automated electric truck caused 18 percent fewer fatalities compared to the automated diesel truck [1].

A 2024 study modeled reductions in damages from air pollution from the introduction of automation and partial electrification in long haul trucking, finding that for long haul routes under 300 miles, electrification reduces air pollution and greenhouse gas damages by 13 percent, and for routes above 300 miles, electrification of only urban segments facilitated by hub-based automation of highway driving reduces damages by 35 percent [2].

To date, much of the research related to health and vehicle automation has focused on passenger vehicles. Additional research is needed to understand potential health impacts of heavy-duty vehicle automation beyond reductions in air pollution, as well as of different types of heavy-duty vehicles and adoption scenarios.

Autonomous vehicles have the potential to reduce fuel consumption through automated acceleration and braking, platooning to reduce air resistance, vehicle design, fuel switching, routing efficiency, and traffic congestion reduction [1]. However, there is also the possibility that automation of vehicles will lead to increase in vehicle usage, and subsequently fuel consumption and emissions [1].

The effect of automation of heavy-duty vehicles can reduce energy consumption and benefit the environment, depending on the fuel source [2]. One study estimated that an automated diesel heavy duty truck reduces greenhouse gas emissions by 10 percent compared to a conventional heavy-duty truck [2]. Meanwhile, an automated battery electric heavy duty truck would reduce life cycle greenhouse gas emissions by 60 percent compared to the conventional heavy-duty truck [2]. However, there are trade-offs between fuel sources for automated heavy-duty trucks, including the mineral resource losses [2]; the battery manufacturing required for automated electric heavy-duty trucks increase mineral intensity significantly compared to automated diesel heavy-duty trucks [2]. Additionally, automation decreases energy intensity of heavy-duty trucks, which decreases through automation, the increase in power generation required for electrified heavy duty trucks may outweigh the benefits from automation [2].

Further research is needed related to the effect of different electricity generation methods on automated heavy-duty truck emissions, as well as with different vehicle design and weight assumptions. Research is also needed related to environmental effects of other heavy-duty vehicles and equipment, such as automated buses and specialized equipment.

Research is sparse regarding the effects of heavy duty applications of C(AV)s on municipal budgets. However, a research project at the University of Oregon studied how autonomous vehicles will change local government finances, using waste collection as a case study [1]. The case study analyzed costs in Asheville and Chapel Hill and found that in the long term moving solid waste refuse collection to automated vehicles and more highly automated systems could create large cost savings [1].

Heavy-duty automated vehicles (AVs) could potentially reduce emissions and improve social equity by reducing disparities of residents’ exposure to vehicle emissions and associated health risks. The environmental impacts from heavy-duty vehicles diesel exhaust are particularly severe for residents living close to roadways with heavy truck traffic, such as freeways and major arterial routes in goods movement corridors [1]. Research consistently shows that communities of color and low-income groups are disproportionately situated in areas affected by freight traffic [2], [3], [4]. Patterson and Harley [1] shows that trucks with emission control strategies could result in decreased exposure disparities for pollutants quantified by the intake differentials of two corridors in the San Francisco Bay Area. Operations for designated truck routes, and restrictions on truck parking and engine idling in or near residential neighborhoods can also mitigate the disparities of traffic-related air pollution [5], and automation of heavy-duty vehicles can facilitate the enforcement of these regulations, leading to a more equitable distribution of environmental impacts.
The advent of heavy-duty AVs could also affect employment by disproportionately affecting low-wage jobs in traditional employment sectors. A key concern is the potential displacement of truck drivers [6], [7]. Nikitas et al., [8] concluded that AVs could generate labor market disruption and new layers of employment-related social exclusion based on an online survey of 773 responses from an international audience. Fleming [9] indicated that the technological unemployment on truck drivers will have less economic impact due to the current shortage of truck drivers and aging workforce. Nevertheless, it is crucial for policymakers and urban planners to develop robust retraining programs to prevent these workers from being replaced by higher-wage tech employees.
Overall, heavy-duty AVs have multiple benefits such as reduced driver costs for freight transported by trucks [10], saved fuel consumption and emissions due to platooning and smoother driving [11], [12], [13], and increased safety [14]. However, the study on the equity impacts of heavy-duty vehicles is sparse. Current areas for future research include: 1) exploring the environmental impacts of heavy-duty AV operations, 2) examining the effects of heavy-duty AVs on job markets and identifying effective retraining programs for displaced workers, and 3) analyzing the disparities in potential benefits and risks that heavy-duty AVs pose to different socioeconomic groups.

Studies considering the impacts of automated trucks on the workforce find that automation may first effect long-haul trucking or over-the-road drivers [1]. These drivers travel throughout a region or the continental United States for work, typically on a limited set of federal interstates and highways. Wang et al. [2] suggest assessing the potential for job displacement by looking at growth in alternative positions with similar requirements for skills, knowledge, and abilities in a truck operator’s home state. According to their study, only 10 states have sufficient alternative employment opportunities to absorb a greater than 15% displacement in truck driving jobs, indicating a need for worker retraining if trucking displacements.

A survey of trucking logistics managers, supervisors, and drivers found that drivers were the most likely to believe that automated trucks would reduce the size of the U.S. truck driving workforce (62%), followed by supervisors (50%), and managers (25%) [3]. Interviewees in this study noted that they thought the introduction of additional technologies into trucking, such as automation, would lead to a shift towards younger drivers rather than older drivers.

Scholars have posited that freight transfer hubs will be placed near interstate highways and on the fringes of regions where automated trucks drop trailers to be picked up by human-operated trucks [1], [2]. However, this is an emerging area of practice and available research has not yet considered implications for land use.

Vehicle automation can reduce the risk of crashes from driver factors, such as fatigue, impairment, distraction, or aggression, which are the cause of or contribute to over 90 percent of all vehicle crashes [1]. Common reasons for single vehicle truck crashes include driving too fast for conditions or curves, falling asleep at the wheel, and vehicle component failures or cargo shifts [2]. For lower levels of vehicle automation, systems that include speed advisories, automatic speed adjustments, driver alertness monitoring, and safe stop ability in the event a driver becomes non-responsive could improve safety [2]. Potential negative safety effects of partial-automation systems like adaptive cruise control include a false sense of security and inattentive drivers [3].

Higher levels (Levels 4 & 5) of heavy-duty vehicle automation have potential to improve safety more dramatically by eliminating human error [3]. However, the technology is still advancing for heavy duty vehicles, and additional safety testing is needed before Level 4 freight trucks are commercially deployed at-scale [3], [4]. Vehicle platooning where trucks travel in a group and the vehicles in the center do not all require drivers is a potential intermediary step towards fully driverless vehicles [3].

Additional research is needed to understand how vehicle platooning, higher levels of vehicle automation (Levels 4 and 5), vehicle designs and weights, and types of heavy-duty vehicles (e.g., buses and specialized equipment) will impact safety and vehicle crash rates.

Autonomous vehicles (AVs) applications can be categorized into a) private autonomous vehicles, b) shared autonomous taxis and c) heavy duty autonomous vehicles like trucks and buses. Research studies [1] based on simulation and hypothetical models suggest that connected and autonomous vehicles (CAVs) will result in increased vehicle miles, shift from active travel to more autonomous vehicle (AV) travel, and more urban sprawl. Thus, these technologies seem to be in conflict with sustainability goals. However, AVs can be environmentally friendly and have social equity benefits if used for public transport, shuttles and shared use mobility. Based on public perception [1], AVs are well accepted for public transport among the public as opposed to being used as personal vehicles.
Mouratidis & Cobeña Serrano [2] analyzed the intention for using autonomous buses within a case study area to see user perceptions of AVs. They observed that travelers would be willing to adopt autonomous buses if these offer more frequent departures. López-Lambas & Alonso [1] observed autonomous buses to decrease congestion, intersection wait time and reduce emissions as factors to influence perception of acceptance of these technologies.
Automated applications for trucks have received a lot of attention over the years due to ease of platooning with freight and the potential network wide operation and fuel consumption benefits. Z. Wang et al. [3] tested connected eco-driving system on heavy duty trucks in Carson, California on two corridors with six intersections. They observed smoothing of speed profiles when trucks approached signalized intersections and showed 9 percent and 4 percent fuel savings in acceleration and deceleration phases. Lee et al. [4] analyzed the safety and mobility of different market penetrations of truck platoons using simulation. They observed that safety improved with 2.5 percent higher speed difference by increasing market penetration rate of truck platoons. M. Wang et al., [5] tested truck platooning under different penetration rates in a simulation environment and observed truck platooning to reduce congestion and improve throughput at higher market penetration rates. They observed significant variability in merging speed under saturated traffic.
The literature has focused more on the benefits of AVs in personal vehicles than the use of heavy duty AVs. Additional research is needed regarding the use of heavy duty AVs for public transport, as well as potential system impacts of automated trucking.