With the deployment of automated vehicle fleets, there will be a corresponding need for managing and operating vehicles remotely. This paper introduces the challenges for the human interface of such future automated fleet management interactions. Based on an analysis of the emerging operator workplace and digitization trends in the logistics domain, key requirements for human interface characteristics for these novel systems are proposed. By means of an expert-based review of human interfaces for automated logistics lfeet interaction systems, the current status with regard to the accomplishment of these requirements is analyzed. Next steps towards realizing future automated logistics fleet interactions are outlined. CCS Concepts: • Human-centered computing → Graphical user interfaces; User interface management systems; Walkthrough evaluations; • Social and professional topics → Automation. Additional Key Words and Phrases: fleet management, teleoperation, automation, workplace, requirements gathering
The role of humans in the logistics system is evolving. Key drivers for this change are technology advancements
through ongoing automation and digitalization, as well as social shifts, such as the aging population [
With the integration of more flexible driverless vehicle fleets, the human workplace will undergo a further significant
transition. While the role of the driver will decrease in significance, other roles will emerge that assure qualified and
responsible operation of the overall systems. The paradigm of the Logistics Operator 4.0 introduced by Cimini et al. [
We posit that answering this question about the operators and their interactions deserves explicit and systematic investigation. In this paper, we present the challenges for the human-centered design of ALFI, considering the emerging workplace requirements and required consolidations of the underlying technology. Furthermore, the gaps for the development of a future framework for designing automated logistics fleet interactions are analyzed, based on the state-of-the-art analysis of current operational systems. 2
First current proponents of automated logistics fleet systems focus on single use cases and vehicle types, for example
automated forklifts in a warehouse or automated trucks transporting goods between two co-located facilities. As
more sectors will use automated fleets, the need for more unified concepts for ALFI will correspondingly grow. These
should combine several types of remote interactions with multiple vehicles, which have so far been defined and
researched separately, such as fleet management, teleoperation, process management, trafic management, and vehicle
monitoring [
As Figure 1 shows, the design and deployment of HMI frameworks to support future automated fleet interactions is strongly influenced by the currently evolving human workplace environment and by the underlying technological enablers (see more details in Section 3). The underlying technology is furthermore also interacting with ALFI as only they can provide the data necessary for the interaction the users require. These systems range from route optimization over integration of legacy systems to the vehicle driving capabilities themselves (Section 4).
Clarify roles: Make tasks, KPIs, responsibilities transparent and manage the variety of operational scenarios Take account of diversity of users and multitude of work contexts Address known human factors issues: Out of the loop syndrome, latency issues, situational awareness through missing embodiment, workload, fatigue Enable communication: Interfacing with other organizations and handover to the next operation
Consolidation of heterogeneous subsystems: Integration of fleets (logistics, public transport, car sharing, trafic management), support of multiple use cases and scenarios Decision support: AI and Big Data analytics, optimization techniques Seamless Information Flow: Real-time access to data and information from multiple sources, to allow a more responsive real-time scheduling
As noted above, apart from Cimini et al. [
Current fleet management systems (FMS) are usually designed for specific use cases. Thus, the range of functions involved in FMS is broad and services are often engaged separately. But to gather an optimal performance in automated logistics fleet environments, an overall system that integrates the data from various functions is required. The challenge is to build an automated FMS which consolidates all available sources of data and information and avoids unnecessary overlaps to other systems. Furthermore it is relevant that an integrated concept allows reactions from the user interface as well as from the workplace.
Automated logistics fleet systems will comprehend many independent heterogeneous elements which are combined
to one consolidated system. One large and important part of logistics transport systems are AGVs. A good overview
of control algorithms and techniques with high potential are discussed for example in [
The main challenge in the design of an automated logistics fleet system, which is applicable to multiple use cases, is to integrate all these elements to one consistent and general system without overlapping elements. A crucial point will be the discussion on the possibilities of the digitalization of conventional processes or the eficient integration of legacy systems. This also leads to the question of data availability and the quality of the data. Due to the above mentioned dynamic development of workplace environments and processes, it is also important to enable for a modular, open and easily extendable system architecture.
The requirements from the operator workplace and the digital consolidation trends pose demanding requirements for the human machine interfaces of ALFI (see an overview in Figure 1). In order to investigate the current state-of-the-art, an expert-based analysis was conducted for six HMIs of fleet management systems developed and used by automated vehicle manufacturers, shuttle service providers and logistics hub operators.
Responsive design, clean and "one size fits all" are terms commonly used when designing interfaces, but are not as common in industry applications and therefore automated logistics fleets. As legacy interfaces are renewed, these design paradigms should also be taken into account. There are already some manufacturers incorporating these elements. Interfaces should not only be designed for one user but be adaptive to new users and diferent environments.
One of the manufacturers took this principle further and designed their system for ”ubiquitous controllability”, with a consistent conceptual design for desktop computers, mobile devices, touchscreens on and near the vehicle. However, what has so far been neglected by current systems is the adaptation to the diversity of users (e.g. regarding qualification level and age).
The analyzed systems were each tailored for the purpose of one single use case. Some systems focus on presenting the results of the automation in terms of KPIs (Is there money saved in the process and the output increased?). Others support the investigation of the actual vehicle (with regard to the current state, such as battery charging or failures). A third type of systems highlights the logistical process (e.g., what will be transported, where will it be transported and when?). No single system provided all necessary elements to enable a user wide interface which can be built on modular elements to enable an interface which fits the requirements of each user best. Future fleet management systems should provide spatial resolution as well as low level vehicle status information, dashboards for managers, and teleoperation possibilities built directly into the system.
Fleet management and teleoperation are regarded as separate issues, as the teleoperation driver needs special training and a driver’s license. For example in the case of transporting goods on a public road a truck driver’s license is needed. The current solution for connecting fleet- and teleoperation is by manually sending a teleoperation task from the fleet management to an always occupied teleoperation stand. The teleoperator is waiting at the teleoperation stand for new tasks and controls the vehicle if requested. Although this is a good separation of concerns, some context might be missing for the teleoperator to complete the required task as eficiently as possible. This includes the current position of the vehicle, the current load, why it failed and where it needs to go. To provide a more seamless hand over of the teleoperation task, the teleoperation and fleet management could be combined into a dedicated remote operator, who can, in case of a failure, also take over the control of the vehicle. It should be discussed in later work what method is more feasible. In any case, the workplace requirement of realistic simulation of the remote situation should be realized for situations in which teleoperation is required.
An aspect so far less regarded is the communication of the vehicle’s awareness and intent, as well as their reliability, in order to calibrate operators’ trust in the system capabilities. Another aspect that needs to be considered when realizing the above recommendation of integrating more spatial resolution and maps is a satisfactory Quality of Experience. Furthermore, with the increasing number of vehicles, more sophisticated attention management will be necessary, in order not to overload operators. 6
The above considerations highlight the need for a systematic user-centered investigation of automated logistics fleet
interactions. The next step in our research is to perform a task analysis, based on contextual interviews of current fleet
managers, teleoperators and experts in the human factors of logistics and transport. Once the data has been analyzed,
requirements can be gathered to generate design patterns [
This work is part of the project AWARD, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101006817. The content of this paper reflects only the author’s view. Neither the European Commission nor CINEA is responsible for any use that may be made of the information it contains.