How Autonomous Trucks Are Reshaping Businesses

The trucking industry is facing a growing shortage of drivers that threatens massive economic repercussions. According to the American Trucking Association, the driver deficit could exceed 160,000 by 2028, while the demand for trucking services is projected to skyrocket in coming years [1]. This combinations of factors poses logistical nightmares for shippers. However, autonomous trucking promises a lifeline through automating driving tasks.

YearDriver Shortage Forecast

With the rapid development of self-driving technology in recent years, autonomous trucks are poised to gain significant mainstream adoption across logistics businesses within the next 3-5 years. From industry giants like UPS to disruptive startups like TuSimple, companies are aggressively piloting autonomous trucks to improve logistics operations.

Beyond merely alleviating driver shortages in the short term, self-driving trucks promise to fundamentally reshape transportation businesses. This technology enables radical improvements in asset utilization, efficiency, costs and overall capabilities compared to traditional trucking. However, fully implementing autonomous fleets involves surmounting complex challenges around technology readiness, scaling, infrastructure needs and transitional impacts on labor and regulation.

The Driver Shortage Crisis Facing Logistics

In 2021, the American Transportation Research Institute estimated that the trucking industry was short approximately 80,000 drivers, despite aggressive hiring efforts [2]. This deficit is projected to worsen dramatically in coming years as current drivers retire and demand for trucking services explodes.

trucks on highway
The shortage of truck drivers in the US could exceed 160,000 by 2028 (Image credit Mateus Campos Felipe on Unsplash)

Goldman Sachs forecasts that domestic freight volumes in the US could grow by over 50% by 2030 [3]. Yet without enough drivers to meet demand, this would cripple supply chains and business operations. Autonomous trucking provides a technological solution to address perpetual recruiment and retention struggles in the industry stemming from an aging workforce and demanding job conditions.

Self-driving trucks can operate without stopping for breaks or sleep to maximize productivity. They also eliminate overhead costs associated with human labor, with estimates projecting over $168 billion could be saved annually across the trucking industry [4]. With such colossal economic incentives, logistics businesses are aggressively pursuing autonomous capabilities.

Major Industry Investment in Self-Driving Trucks

From transportation giants to Silicon Valley tech startups, there is surging investment across the industry towards developing and deploying autonomous trucks. Key players are making rapid progress.


With over 20 million miles of real-world testing across multiple truck platforms under its belt, Waymo is an industry leader pushing autonomous technology [5]. Waymo trucks utilize lidars, radars and cameras paired with advanced AI algorithms to enable complete self-driving abilities.

The company is already working closely with firms like C.H. Robinson and J.B. Hunt on pilot programs hauling freight. Waymo focuses exclusively on software and hardware for retrofitting onto conventional trucks rather than manufacturing vehicles.


Founded by former leaders from Tesla, Uber and Google‘s early self-driving car project, Aurora aims to develop autonomous technology for multiple vehicle types including semi trucks [6]. With partnerships across the industry, Aurora completed its first commercial pilot in 2021 transporting freight autonomously in Texas.

Leveraging machine learning and AI breakthroughs in recent years, Aurora‘s FirstLight technology stack incorporates robust mapping, routing, motion planning and object detection capabilities. Its next-generation Driver product focuses on enabling unmanned autonomous trucking operations with remote monitoring.

Toyota & Embark

Automaker Toyota invested $400 million into self-driving truck startup Embark in 2022 to accelerate developing and scaling autonomous semi trucks [7]. Integrating Embark‘s expertise in software for unmanned trucking with a specialized Toyota truck platform aims to rapidly get autonomous fleets on roads.

Embark has piloted self-driving trucks able to pick up and deliver freight entirely autonomously across long stretches of highway. It plans to expand driving capabilities to handle complex urban areas and loading docks within years through machine learning advancements.

Collectively, these major initiatives illustrate the transition towards autonomous trucking is well underway. With continued progress, widespread adoption is imminent.

How Do Self-Driving Trucks Work?

Autonomous trucks incorporate a suite of sensors – including cameras, lidars and radars – paired with powerful onboard computers running advanced AI algorithms [8]. This hardware and software stack enables them to perceive and map environments, locate themselves precisely, plan optimal routes, predict behaviors of other vehicles, and execute driving maneuvers without human input.

autonomous truck sensors
Autonomous trucks utilize cameras, lidars, radars and other sensors to navigate (Image credit: Chris Liverani on Unsplash)

Lidars constantly scan surroundings to generate real-time 3D representations of roads, obstacles and signs. Radars measure distances to objects. Cameras classify items in view. Onboard computers then fuse this sensory input to determine location precisely and plan optimal driving actions leveraging AI models. These systems enable trucks to operate fully autonomously including overtaking, merging lanes, parking and more based on dynamic conditions.

Many autonomous trucks also support vehicle-to-infrastructure (V2I) communication with smart roadways and cloud data services [9]. This allows accessing shared traffic updates, hazard warnings, mapping data and computing capabilities to enhance decisions. V2I promises to address limitations of onboard hardware for handling extreme edge cases down the line.

Moving forward, advances in AI and computing power will expand abilities to handle increasingly complex scenarios. But even with today‘s technology, self-driving trucks can safely automate common long-haul highway routes.

Benefits Over Traditional Trucking

Autonomous technology unlocks game-changing operational advantages for logistics companies compared to traditional manually-driven trucks:

Increased Productivity and Asset Utilization: Self-driving trucks don‘t require breaks, sleep or shift changes. This enables maximizing driving hours and load capacity to improve asset utilization over 20% [10]. They also optimize routing and efficiency.

Lower Labor Costs: Eliminating drivers slashes expenses by at least 10%, upwards of 40% for some fleets [11]. Savings stack up considering insurance, benefit, training and turnover costs per driver too.

Enhanced Safety: Over 90% of collisions involve human-error factors like distraction, fatigue or misjudgement [12]. Automation mitigates accident risks and liability costs through onboard safety systems monitoring road conditons continuously.

Fleet Data and Insights: Onboard sensors and connectivity provide rich data on truck performance, freight environmentals and driving analytics. This powers better maintenance and design decisions.

Collectively, such advantages will make autonomous trucking the predominant mode for consistently moving high volumes of goods over highways within years.

Challenges With Scaling Autonomous Trucking

Fully displacing manually-operated trucks will still realistically take over a decade though [13]. Some principal challenges slowing mainstream adoption include:

Technology Limitations: While highways are increasingly handled reliably, complex urban areas and loading docks still challenge self-driving software. Expanding capabilities requires vast, edge case training data.

Infrastructure Needs: Optimizing autonomous fleets may require tailored warehouses, loading bays, smart roadways and secured parking facilities equipped with chargers. Such infrastructure demands heavy investment.

Regulations: Laws around autonomous vehicles vary drastically between states and countries. Inconsistent policies combined with insurance liability issues pose legal barriers inhibiting large-scale rollouts. Changes typically trail technology.

Job Displacement: Automating driving eliminates trucker jobs, but could open up remote operating and new technical support roles. Smoothly transitioning the workforce remains an obstacle and ethical concern though.

Overcoming these challenges comes down to continued technological innovation paired with evolving regulations, infrastructure, and labor positions for an autonomous future.

Impacts on Maintenance and Facilities

With autonomous trucks likely to become mainstream on roads within years, how will maintenance adapt? Services will shift more towards preventative upkeep and rapid fixes to minimize service downtime. Highly advanced repair shops could also allow remote diagnosis and offsite automation.

Rather than traditional oil changes and engine work, maintenance will focus on keeping complex sensors, computers and software in working order. Trucks equipped with over-the-air update capabilities can push new code versions seamlessly. Machine learning-based analytics will also forecast problems before failures through predictive maintenance.

When hardware issues do occur, modular designs will accelerate swapping faulty components. We may see sensors designed for mechanics to easily detach and replace using common hand tools without fully entering pits [14]. Quick couplings for rerouting air, electric and data around the module simplify changeouts. Technicians can then refurbish parts offsite.

Moving forward, highly specialized autonomous service centers outfitted with cranes, assembly lines and technical workstations could enable pulling entire truck cabs carrying the vehicle???s critical computing stack. Fully remote and even automated diagnosis and repair would maximize uptime. Companies like Embark Trucks already emphasize the importance of serviceability engineering vehicles for reliability and access.

Ultimately maintenance processes will innovatively adapt around minimizing autonomous truck downtime through forecasting, modular designs and remote capabilities. Facility workflows may take cues from IT infrastructure management and electronics factories. But close collaboration between fleets, dealers and manufacturers starting today helps proactively optimize maintenance for a driverless tomorrow.

The Future of Autonomous Trucking

Industry experts predict autonomous trucks will dominate long-haul logistics within the next decade, supporting predictions that over 15,000 self-driving trucks could be operating on US roads by 2030 [15]. Continued innovation and increasing pilot deployments by major fleets signal the technology is mature enough for selective adoption today, then gradual mainstream integration.

While conquering edge cases and infrastructure needs postponing full automation a few more years, autonomous trucks clearly offer solutions to perpetual driver shortages and other industry woes. Their radical improvements over conventional trucks ensure logistics companies will continue aggressively adopting this technology. Automated trucking promises to reshape transportation far beyond merely reducing labor costs, instead enabling new paradigms for efficiency, reliability and capabilities across supply chains.

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