Japan has entered the field-testing stage of its "automated logistics road" plan about two years after announcing it, replacing human-driven trucks with unmanned carriers that move palletized freight around the clock. The concept of converting roads into logistics infrastructure is taking firmer shape as the country braces for a shrinking pool of truck drivers.
The Ministry of Land, Infrastructure, Transport and Tourism said on the 18th that a second round of demonstration tests began this month at a test track at the National Institute for Land and Infrastructure Management in Tsukuba, Ibaraki Prefecture, and at a facility inside Narita International Airport in Chiba Prefecture. The core of the tests is running three or more carriers autonomously at the same time. The trials will verify whether the unmanned carriers can negotiate curved sections smoothly and handle lane changes, merging, diverging and passing one another.
Dedicated Lanes Where Only Carriers Run at 70-80 Kilometers per Hour
The automated logistics road concept calls for creating dedicated freight space in highway medians, on shoulders or underground. Physically separated from ordinary traffic, the space would carry dedicated unmanned transport devices powered by electricity or other clean energy.
The system would work as follows. Once cargo measuring 1.1 meters on each side and 2.2 meters high is brought to a roadside hub, unmanned loading equipment such as an automated forklift places the pallet on a carrier. The carrier travels along the dedicated space to a hub near the destination, where the cargo is unloaded again without human hands and then loaded onto a truck for the final leg. The Japanese government raised its target carrier speed last year to 70 to 80 kilometers per hour from an initial 30 kilometers per hour, roughly matching current freight trucks.
The ministry intends the road mainly for small parcels such as online shopping deliveries. As e-commerce has grown, the average weight of a single shipment leaving Japanese factories and warehouses fell to 0.7 metric tons in 2021 from 2.43 metric tons in 1990. The design is meant to break up these frequent, less-than-truckload shipments into pallet units and move them without interruption along the automated logistics road. The ultimate goal is to meet rising logistics demand with fewer trucks and fewer workers.
Japan is also developing self-driving trucks for ordinary roads. The reason it is nonetheless weighing a costly redesign of road infrastructure is population aging. The government estimates that on the current trajectory, transport capacity will fall 34% short of required volume in fiscal 2030. An official at a South Korean logistics company said Japan views the loss of long-haul truck drivers to aging as a grave problem, adding that waiting for technology and legal frameworks to catch up until fully driverless vehicles are safe enough could prove too late, which is why this approach was devised.
Self-driving trucks on ordinary roads must respond in real time to unpredictable variables, including bad weather, debris on the road and other drivers who doze off or speed. They must also keep ample distance from other vehicles because of congestion and accident risks, which can raise efficiency concerns. On a dedicated road, by contrast, standardized carriers run continuously at a constant speed with fewer variables, making the threshold for full automation relatively low. The ministry estimates that the automated logistics road could cover up to 22% of the projected 900 million metric ton shortfall in transport volume in fiscal 2030.
127 Companies Including Amazon Japan Take Part, With Service Targeted for Mid-2030s
Japan aims to begin actual operations on part of the Tokyo-Osaka corridor by the mid-2030s. It is also considering expanding the network to the Kanto region and Hyogo Prefecture.
Major companies are taking part. Participants include consumer goods and retail firms such as Amazon Japan, Seven-Eleven Japan and Asahi Group Japan; delivery companies including Yamato Transport, Sagawa Express and Japan Post; and technology firms such as NEC, Fujitsu and Toshiba. As of March this year, 127 companies were involved, including some that have not been disclosed.
The limits are clear, however. Cargo must be transferred one additional time at both the origin and destination hubs. David Cebon, a professor at the University of Cambridge in Britain, told the German environmental outlet RESET that the need to handle freight twice cannot be avoided. He also noted that because the system can only run along fixed routes, it carries the same drawbacks as rail freight.
Cost is another challenge. A 2024 review panel estimated that building the dedicated route underground could push construction costs as high as 4 trillion yen. Switzerland, which pursued a similar concept earlier, is also known to be grappling with operational efficiency issues such as bottlenecks at hubs and with financing the investment.
South Korea is focusing on self-driving freight vehicles rather than dedicated roads. Major domestic logistics companies including CJ Logistics, Hanjin and Coupang Logistics Services are pressing ahead with autonomous driving technology. Hanjin began paid transport in July using a 25-ton self-driving truck, running a 118-kilometer route three times a week from Gunsan Port in Jeonbuk State through Hanjin's Jeonju parcel terminal to its Daejeon mega hub. CJ Logistics operates autonomous freight transport in downtown Daegu as well as on highways, with an 11.5-ton truck carrying actual cargo on a loop among four sub-terminals in the Daegu area, located 4.2 to 26 kilometers apart.
Industry officials say South Korea, unlike Japan, is not in a situation where the pace of labor shortages outstrips the pace of autonomous driving development. An official at a logistics company said the company plans to accelerate the commercialization of autonomous logistics based on its nationwide logistics network and actual operating data, adding that it will speed up smart logistics innovation by applying advanced technologies such as big data and artificial intelligence in the field.