"Autonomous Truck Readiness Depends on What Happens When Conditions Deteriorate"
An autonomous truck may detect an obstacle during a demonstration and still face a different test at a working site. Dust can obscure sensors. Lighting changes across a shift. People and vehicles enter shared operating areas. Readiness depends on whether the truck can recognize those conditions, respond safely and stop when its perception is no longer reliable.
Written responses to The Supply Chainer from Seyond and AIT Worldwide Logistics describe complementary barriers to deployment. Seyond focuses on sensing performance and maintenance. AIT questions how quickly the technology can overcome equipment costs and the complexity of everyday freight operations.
Test the Complete System in Its Working Environment
Oliver “Oli” Ramoli, Business Development & Manager Key Accounts EMEIA at Seyond, a LiDAR technology provider, said operators should assess the complete perception system where the vehicle will actually work. “Before deploying autonomous trucks, operators need to test the complete perception system in the environment where it will actually be used. That includes adverse weather, changing light conditions, blind spots and interactions with people and other vehicles.”
Ramoli also identified stationary objects, low-profile obstacles and partially hidden hazards as important test cases. Detection must occur early enough for the vehicle to stop safely. LiDAR supplies three-dimensional information about the surroundings, complementing cameras and radar, he said. The response did not specify minimum detection distances, acceptable error rates or stopping thresholds. It establishes the conditions operators should examine rather than a certification standard or evidence that a particular vehicle has passed.
Sensor Maintenance Becomes an Operating Requirement
Dust, mud and water droplets can impair optical sensing. Ramoli recommended adapting inspections and cleaning to actual conditions rather than relying solely on fixed intervals. A dusty quarry and a relatively clean logistics yard present different maintenance demands.
Diagnostics and continuous monitoring can help identify deteriorating perception where the system supports those capabilities. The vehicle must also recognize when sensing quality no longer supports safe operation.
That requirement connects maintenance directly to deployment planning. A truck’s availability depends partly on whether its sensors remain usable throughout the shift, and whether the operation can respond when they do not. A successful initial test cannot establish continuing readiness.
Commercial Coverage Faces a Separate Test
In a separate written reply to The Supply Chainer, Mike Rothacher, Executive Vice President, Road, at AIT Worldwide Logistics, described the technology as still being in its formative stages.
“At the outset, autonomous trucking could only be used for hauling hub-to-hub shipments. Direct delivery to consignees involves a variety of unsolved challenges such as schedule changes and navigating densely populated markets.” Rothacher estimated that autonomous vehicles would not exceed 1% of total U.S. load volume before 2029. That is AIT’s forecast, rather than an established adoption figure. He also cited equipment premiums, reliability and safety concerns as constraints, without supplying a supporting cost study or deployment model.
The two perspectives address different operating environments, but together expose the limits of treating autonomy as a single readiness milestone. A vehicle must perform within defined conditions, maintain that capability during work and fit the freight task being assigned.
For fleets and shippers, the practical question is how much of an operation can be served reliably within those limits. Demonstrating a journey is one step. Sustaining service when conditions change is the larger test.
