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For some terminals, a high degree of automation in specific areas is an attractive vision. However, this will not happen in a single leap—for most, the path forward will be gradual and shaped by the existing infrastructure.
Consequently, manual and automated equipment will operate side by side for a period of time (see also: Container yard operations). Both approaches must integrate seamlessly, which presents a unique challenge.
Beyond the question of the extent to which operations can be automated, it is also crucial to consider how effectively the equipment and systems can interact with personnel within a mixed fleet.
The first step is visibility. A reliable overview of the locations and tasks of the equipment—as well as their interactions—is essential. Once established, technology can support traffic coordination, personnel safety, and operational task execution.
The goal of automation initiatives is to create a safer, more reliable, and more efficient terminal.
A mixed fleet doesn't just add another type of vehicle to those already in use; it introduces an extra layer of operational logic.
A human driver makes decisions individually, whereas an autonomous system responds based on established rules, digital instructions, and a predefined understanding of its environment.
Different manufacturers and generations of equipment may use different systems and provide varying levels of information. These systems provide different views of the operation.
The TOS manages terminal jobs and container movements, while positioning systems, vehicle controls and onboard equipment may provide additional information. The challenge is connecting these views so that the digital plan reflects what is happening on the ground.
This is precisely when managing a mixed fleet becomes complex. The fleet must be viewed as an integrated operation comprising different types of equipment. This requires a unified, comprehensive operational overview:
The first step in managing a mixed fleet is knowing what is happening at any given moment.
A clear operational overview integrates information regarding:
Position—where is the vehicle located?
Identity—which specific vehicle is it?
Status—is it available, in motion, waiting, or out of service?
Task—what assignment is it currently carrying out?
Verification—does the actual situation on the ground align with the expectations of the terminal systems?
Various technologies provide the necessary data:
Positioning systems supply the spatial component, while vehicle identification links movements to specific pieces of equipment. Onboard systems and telemetry provide additional information regarding device status and operational condition. Integration with the Terminal Operating System (TOS) incorporates the planned task and the context of the container being handled (see also: Terminal automation and what to look for).
These combined data points yield valuable operational insights. This is particularly critical when operational boundaries are crossed—for instance, if a manually operated truck enters an area where automated vehicles are also in use. In other scenarios, a vehicle might deviate from its assigned route, or a task might change while a vehicle is already in transit.
In such cases, those in charge must be able to draw upon a common data foundation in order to assess the situation and determine the next steps. Not all vehicles need to use the same technology; the key is for the various systems to exchange all relevant information. This information must then reach the individuals or systems responsible for taking the appropriate action.
Automation changes the interaction between humans and machines, but it does not entirely remove humans from the equation.
In a mixed fleet, drivers, technicians, and other personnel work side by side with autonomous vehicles. When they enter areas where automated processes are taking place, it is essential—beyond simply knowing the vehicle's location—to understand what is happening in its immediate environment.
Only in this way can collision risks be mitigated, adherence to defined operational zones ensured, and warnings issued if equipment or individuals move into unexpected areas. The goal is not to blindly automate safety-related decisions, but rather to provide both sides with better information.
This information also proves valuable following an incident. Precise records regarding locations, movements, and status make it easier to understand the sequence of events and identify where processes or infrastructure require improvement.
Vehicle breakdowns, blocked lanes, or interrupted automated processes can affect multiple workflows and lead to delays in other areas. It is therefore essential to contain the impact.
First, it is necessary to understand the consequences: Which tasks depend on the affected vehicle? Are alternative resources available? Does traffic need to be rerouted, or should certain operational movements be temporarily suspended? Personnel can only evaluate these questions and make well-founded decisions if there is a shared operational picture.
Flexibility is crucial: Depending on the situation, it may be necessary, for example, to reassign tasks to other vehicles. In a mixed fleet, this requires both manual and autonomous systems to be able to respond to changes without creating new conflicts.
While technology supports these decisions, clear responsibilities and emergency procedures are essential. It must be defined who is authorised to intervene, how changes are to be communicated, and when regular operations can resume.
In the case of a "greenfield" terminal, the desired technology can be incorporated into the planning from the very beginning and considered across all operational areas. The situation is different for "brownfield" sites—that is, existing facilities.
In such cases, the operational framework—including equipment, infrastructure, Terminal Operating System (TOS) processes, and workflows—is already in place. Some components may be decades old, while others might be state-of-the-art. Replacing everything at once is rarely feasible—and often not even necessary.
A modular approach makes far more sense. It allows operators to focus initially on specific, urgent operational challenges. For instance, one area might require better visibility regarding vehicles, while another could benefit from optimised traffic management.
A step-by-step approach keeps technology investments manageable. Another advantage is that the terminal can learn from each individual phase before moving on to the next.
The starting point could be, for example, a security issue, a congested storage area, inefficient truck movements, or a lack of visibility into equipment use. Once the necessary data and technologies are in place, functionality can be expanded incrementally.
Integrating new systems with existing ones is crucial. Automation should not result in a collection of isolated, standalone systems that require manual management by staff.
The goal is gradual improvement without disrupting ongoing operations: solve a specific problem, measure the results, integrate proven solutions, and build further from there.
The TOS remains the operational backbone. New technologies supplement it by providing additional information—such as equipment locations, vehicle status, telemetry data, job progress, or safety-related events. Through the use of APIs and standard interfaces, these data sources can be integrated without requiring the terminal to replace its core systems.
The same principle applies to equipment. While existing vehicles may not have been designed for automation, they can often be retrofitted with capabilities for identification, positioning, or communication. Newer, autonomous equipment can subsequently be integrated into this same, more comprehensive information environment.
In this way, the terminal retains its proven systems while incrementally expanding them with features that deliver genuine added value.
It is tempting to measure progress by the number of automated vehicles. However, this reveals little about whether the terminal is actually performing better.
A mixed fleet should be evaluated based on operational outcomes:
Safety
Reliability
Performance
Resilience
Can the terminal respond when equipment fails, traffic patterns shift, or an unexpected event disrupts the standard workflow?
These metrics provide a solid foundation for investment decisions. After all, even a relatively small technology project—one that eliminates a persistent bottleneck or enhances safety—can deliver greater value than a far more extensive automation initiative (learn more about port automation challenges).
For those in charge of a terminal, the crucial question is whether the technology helps move cargo more safely, reliably, and efficiently. If it does, then a mixed fleet—whether it consists of autonomous vehicles, manually operated ones, or a combination of both—is successfully fulfilling its purpose.
Collision-avoidance systems combine sensors, positioning information and onboard control logic to help detect potential hazards and reduce collision risk.
Proximity sensors
Project into the environment using technologies such as radar (radio waves), ultrasound (sound waves), or lidar (laser pulses). These sensors are often complemented by cameras.
Localisation systems
Satellite navigation, local positioning infrastructures (ultra-wideband, RFID), and other position-detection technologies (wheel odometry, inertial sensors such as accelerometers and gyroscopes, though these are not standard technologies).
A control unit in the vehicle assesses, based on available information, whether a danger is posed by another vehicle, a person, or some other obstacle. If a potential collision is detected, the system—depending on its design and safety certification—can warn the driver, restrict vehicle movement, or initiate automatic braking.
For most terminals, modernisation is gradual. The primary focus is on establishing a reliable overview of operations, coordinating different types of equipment, ensuring safety, and implementing effective incident management.
A modular approach allows terminals to build upon existing infrastructure, make targeted improvements where they will have the greatest impact, and evaluate the results before taking further steps.
The goal is not to automate every single vehicle. Rather, the objective is to make the entire operation safer, more reliable, and more efficient—regardless of the specific balance between manually operated and automated systems.
Delve deeper into one of our core topics: Port Automation
Gyroscopes are sensors that measure a vehicle’s angular velocity—how fast it rotates about its roll, pitch, and yaw axes. In position-detection systems, they do not measure position directly; instead, they help maintain the vehicle’s orientation so accelerometer readings can be correctly converted into velocity and position. In an inertial navigation system, gyro and accelerometer data are integrated from a known starting point, a process called dead reckoning. Gyro errors and drift accumulate over time, so they are commonly corrected with GPS, cameras, lidar, or other references. (2)
Wheel odometry is a robot-navigation method that estimates a vehicle’s position and orientation from its wheel movement. Encoders count wheel rotations, which are converted into distance travelled using wheel diameter and the robot’s kinematic model. By integrating these measurements over time, the system estimates how far and in what direction the vehicle has moved. It is inexpensive and fast, but errors accumulate because of wheel slip, uneven surfaces, and measurement noise, so it is often combined with cameras, lidar, IMUs, or GPS. (3)
Sources:
(1) https://www.sciencedirect.com/science/article/abs/pii/S1366554525005952
(2) Groves, Paul D. (2013): Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems. Artech House.
(3) Lynch, Kevin M.; Park, Frank C. (2017): Modern Robotics: Mechanics, Planning, and Control. Cambridge University Press.
Note: This article was partly created with the assistance of artificial intelligence to support drafting.