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10 October 2025In recent years, the idea of self-driving trucks has shifted from science fiction to tangible pilot projects, and the implications for last-mile delivery are profound. As consumers demand faster, cheaper, greener shipping, logistics providers are beginning to see autonomous trucks not as a distant curiosity but as a potential backbone for the middle and final stages of goods delivery.
In this article, we explore how autonomous trucking fits into last-mile strategies, what challenges remain, and how the logistics ecosystem may evolve — especially in Germany and the whole Europe.
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Why autonomous trucks matter for last-mile delivery
Last-mile delivery remains the most expensive and complex leg of logistics. In urban areas, dense road networks, traffic, parking constraints, and labor costs drive inefficiencies. In rural or peripheral zones, low density means vehicle utilization is low and cost per parcel is high. Autonomous trucks offer a rethinking of how goods move from regional hubs closer to the customer.
While fully autonomous trucks are unlikely to replace delivery vans knocking on doors tomorrow, their greatest value lies in transfer hub networks — where autonomous vehicles handle the heavy lifting between distribution centers or regional depots, and smaller electric vans, robots, or drones complete the final leg. Models such as autonomous transfer hub networks (ATHNs) propose precisely that: layering driverless trucking on mid-mile paths and humanless or assisted deliveries at the endpoint.
By shifting hub-to-hub traffic to autonomous systems, logistics firms can reduce redundancy, shrink handling costs, and free up human drivers to focus on intricate urban routes. This hybrid architecture is seen by many analysts as the most feasible path forward in the near to medium term.
Current deployments and pilot projects
Global interest in autonomous trucks is accelerating, though mostly at pilot scale. In Germany, an IVECO heavy-duty truck equipped with autonomous software from Plus is running along a DSV route in Baden-Württemberg and Hessen, carrying goods for dm-drogerie markt. This test employs a driver-supervised arrangement — still with human oversight — but serves as a stepping stone toward greater autonomy.
In the U.S., Aurora recently launched fully driverless tractor-trailers between Dallas and Houston, delivering commercial freight without a safety driver onboard. Aurora’s advance, while context-specific, signals that regulatory ecosystems may be loosening in certain jurisdictions to allow real-world deployment.
Other players focus on the middle mile. Gatik, for instance, deploys Level 4 autonomous trucks on fixed routes between distribution sites and retail nodes, bridging the gap that lies between highway freight and urban delivery.
These hybrid and incremental approaches underscore that fully driverless, door-to-door trucking is not yet the norm — but that pieces of the autonomous puzzle are already in motion.
Technical foundations and route planning
Autonomous trucks rely on rich sensor suites (lidar, radar, cameras), vehicle-to-everything (V2X) communications, and advanced AI to perceive the environment, predict motion, and make path decisions. For long corridors, mapping and scene understanding become easier (fewer dynamic obstacles, more familiarity), making highway segments the natural starting line for autonomy.
Route planning also plays a crucial role. In hybrid systems that combine trucks, drones, and sidewalk robots, cooperative scheduling is needed — for example, trucks serving as mobile launch platforms for drones, or coordinating charging stops mid-trip. Researchers recently proposed a “multi-platform vehicle routing problem with drones and robots” model (VRP-DR) in which trucks carry drones, support en-route recharging, and manage docking flexibility to optimize time and cost.
In practice, the scheduling and recharging constraints — battery capacity, payload weight, dwell times — pose large challenges. Yet integrating autonomous trucks into that ecosystem can greatly improve flexibility and cost effectiveness for dense delivery corridors.
Benefits: cost, speed, and sustainability
Cost reduction is the most talked-about benefit. The autonomous last-mile delivery market is growing rapidly: in 2024, it was estimated at USD 1,615.4 million, and it’s projected to reach USD 5,930 million by 2030 (CAGR ~24.8 %). In Germany alone, the autonomous last-mile market was about USD 172.7 million in 2024, expected to rise toward USD 635 million by 2030.
By automating trucking in the middle phase, unit costs per parcel can shrink because labor, idle time, driver break rules, and inefficiencies are reduced. In addition, autonomous vehicles can operate more continuously (overnight, off-peak), making better use of infrastructure.
Speed and consistency improve when autonomous trucks adopt strict schedules and avoid human errors. Predictability in arrival windows can allow downstream delivery systems to better batch and optimize last-mile legs.
Sustainability is also a major driver. Autonomous trucks will mostly operate on electric or hydrogen platforms, reducing CO₂ and pollutant emissions compared to diesel vehicles. Studies that combine drone and truck systems show emission reductions of 20-30%, along with cost savings over traditional fuel-based fleets. Autonomous systems also reduce congestion by optimizing routes and reducing redundant trips.
Further, integrating autonomous trucking into urban areas means fewer large vans crisscrossing residential streets; instead, bulk loads are funneled efficiently to local microhubs.
Challenges and obstacles
Regulation and legal uncertainty remain among the greatest barriers. Public roads across Europe have fragmented regulations on vehicle automation, liability, and certification. Harmonizing protocols across national borders is complex, especially when autonomous vehicles cross jurisdictions. Many systems today still require human oversight or “safety drivers” during trials.
Public acceptance and trust pose another challenge. Research in Germany shows users’ acceptance is influenced by perceived safety, convenience, and ease of use. Some consumers may hesitate to receive parcels from a robot or driverless truck, demanding guarantees on reliability and security. Overcoming psychological barriers is as important as engineering progress.
Infrastructure constraints are significant. Roads must support reliable mapping, lane discipline, clear markings, and connectivity (5G, V2X). Charging networks must scale, especially for heavy electric trucks. In dense urban areas, infrastructure upgrades (smart intersections, dedicated lanes) may be needed for safe operation.
Technical edge cases like mixed traffic, pedestrians, inclement weather, unplanned roadworks, and GPS-denied environments remain hard to master. Handling rare events robustly is essential for safety and regulatory approval.
Workforce transition is a delicate issue. While autonomous trucking could reduce demand for traditional drivers, new roles — fleet monitoring, remote operation, system maintenance, data analysis — are emerging. Transition plans and reskilling will be vital.
Capital intensity and economics: building autonomous systems is expensive. Many early companies have struggled with funding. For example, Starsky Robotics — a pioneer — shut down in 2020, partly because investors underestimated the time and capital needed to mature the technology. Logistics firms must make long-term bets amid uncertain returns.
Transition path: hybrid models and phased adoption
Given these challenges, full driverless last-mile trucking is not immediate. The more viable path is phased adoption:
Hub-to-hub autonomy: Start by deploying autonomous trucks on controlled highway segments between major logistics hubs, where environmental variables are lower and mapping is simpler.
Semi-autonomous support for drivers: Provide driver assistance systems (lane-keeping, collision avoidance, platooning) to ease the transition and build familiarity with autonomy.
Autonomous feeder to microhubs: In lower-risk suburban or industrial zones, autonomous trucks can deliver to local micro-distribution centers, where final delivery is taken up by vans, robots, or drones.
Full door-to-door autonomy (long term): Only after robust safety validation, regulatory acceptance, and public trust mature can autonomous trucks connect directly to customers.
Researchers’ models already support the hybrid approach. For example, optimizing transfer hub networks shows that combining autonomous trucking in the core with human-driven legs at ends yields strong cost benefits.
Some pilot projects already reflect this: the German IVECO deployment remains supervised; Aurora’s Texas operation is limited to specific routes. Realistically, the fully autonomous last mile is the final frontier.
Implications for logistics providers, retailers, and cities
For logistics providers, the coming wave of autonomous trucks will demand strategic innovation:
Reevaluate network topology: More smaller hubs closer to consumption zones, integrated with autonomous routes, may outperform traditional centralized layouts.
Digital readiness: Investments in real-time telematics, route optimization, connectivity platforms, and AI operations will become essential.
Partnerships and innovation ecosystems: Collaborating with AV startups, infrastructure providers, telecom firms, and municipal authorities can allow early entry and influence over standards.
Cost modeling: Simulations must assess total cost of ownership, balancing autonomy investment versus labor savings, energy savings, and utilization.
Regulation engagement: Active dialogue at national and EU levels ensures that legislative frameworks don’t lag technology and that logistics firms’ interests are represented.
Retailers will benefit from faster, more predictable delivery windows and lower shipping costs. Consumers may one day see autonomous trucks as part of their daily delivery landscape — quiet, efficient, and reliable.
For cities, autonomous trucking may reduce congestion and emissions if integrated with smart infrastructure. But planners must adapt: allocate curbs, manage charging and routing, and anticipate new traffic patterns.
Outlook: when and how it might materialize
While projections vary, the autonomous last-mile delivery market is expected to grow rapidly. Some industry forecasts extend the total addressable market from USD ~1.6 billion in 2024 to nearly USD 6 billion or more by 2030.
In Europe — and specifically Germany — growth is projected at a CAGR of ~24.8%. Within a decade, we could see large swaths of intercity trucking handled autonomously, feeding regional hubs that feed microhubs via smaller autonomous systems.
Realistically, we are in a decade of transition. Between 2025 and 2035, robotics, connectivity, regulation, and public acceptance must mature in tandem. Intellectual leadership, first-mover pilots, and flexible network designs will favor logistics players that embrace change early.
Driving toward a smarter last mile
Autonomous trucks will not replace every delivery van tomorrow. But they can transform how goods move between hubs, reshape cost structures, and unlock more efficient last-mile networks.
The path forward is hybrid: driverless highways, microhub feeders, and human-orchestrated final legs. With strategic planning, technological investment, and regulatory alignment, the future of last-mile delivery could be quieter, cleaner, faster — and powered by autonomous trucks.
