The project ‘Working with quality measures in train timetable planning’ (Swedish acronym ARKA) has investigated how quality measures for timetables can be used in the Swedish Transport Administration's long-term planning of the Swedish railway system. The project builds on previous research results from the Timetable Quality (TTK) project, which developed a framework for measuring various aspects of timetable quality. The ARKA project has focused on making these quality measures understandable and useful in the daily work of planners by developing digital decision support and visualisations. The aim has been to facilitate and improve decision-making in timetable planning and thus contribute to more robust and efficient rail traffic.The project has been conducted using a use-centred methodology, with 13 long-term planners, capacity experts and national coordinators participating in interviews, workshops and providing feedback on prototypes. Through this iterative approach, several types of visualisations were developed and evaluated that can be integrated into the planning process. The results from interviews and workshops show that visualising quality metrics has the potential to make it easier for planners to see and compare quality deficiencies in different solutions to a timetable. The ability to see the quality of the timetable also enables new systematic working methods to improve a timetable. The project created and evaluated prototypes for visualising theoretical feasibility, robustness, conflicts and application fulfilment. These measures were selected based on analyses of planners' needs. In addition to these quality measures, the progress of the planning work was also visualised in relation to adjacent geographical areas in order to determine how the work is affected by other planning areas.Appropriate visualisations also proved to facilitate communication with railway companies, as the advantages and disadvantages of the solutions can be easily shown and different planning decisions can be justified. In addition, it was pointed out that thistype of tool can help inexperienced planners to more quickly understand what characterises a good timetable, making the tacit knowledge of experienced employees more accessible. At the same time, the report emphasises the importance of developing these digital aids in collaboration with users and of taking organisational changes and training needs into account when introducing them.The conclusion is that effective and easy-to-use visualisations have the potential to improve planning work. For future development, continued use-centred design and a holistic perspective that also encompasses how this type of tool affects working methods and competence requirements are recommended. In the long term, decision support based on quality measures can contribute to more transparent, efficient and uniform processes for capacity planning in the railway sector

As vehicle automation technology continues to mature, there is a necessity for robust remote monitoring and intervention features. These are essential for intervening during vehicle malfunctions, challenging road conditions, or in areas that are difficult to navigate. This evolution in the role of the human operator - from a constant driver to an intermittent teleoperator - necessitates the development of suitable interaction interfaces. While some interfaces were suggested, a comparative study is missing. We designed, implemented, and evaluated three interaction concepts (path planning, trajectory guidance, and waypoint guidance) with up to four concurrent requests of automated vehicles in a within-subjects study with N=23 participants. The results showed a clear preference for the path planning concept. It also led to the highest usability but lower satisfaction. With trajectory guidance, the fewest requests were resolved. The study’s findings contribute to the ongoing development of HMIs focused on the remote assistance of automated vehicles.

Vehicle users’ adoption of vehicle-to-grid (V2G) is essential for the system's ability to perform V2G grid services. What charging preferences, needs and routines do EV users have and why? What future expectations do EV users have for bi-directional charging? To answer these research questions, a multimethod study is performed (interviews and survey). The following themes were identified as critical for the acceptance of V2G technology in the everyday life of the interviewees: Convenient and resilient home, minimum range for emergencies, fear of battery degradation, trust in system providers, economic and social incentives, user preferences and need for control. Linear regression models identified associations between sociodemographic characteristics and evaluations of V2G in terms of sustainability and efficiency. The interest in creating resilient homes among certain consumers and EV drivers suggests a demand for services that integrate technologies for home energy efficiency and V2G.

Remote operation of highly automated vehicles (HAVs) may include occasional assistance from a human remote operator that is located outside the HAVs. Remote assistance typically delegates only highlevel guidance tasks to the remote operators such as authorizing a driving maneuver or specifying a new driving path. As remote assistance is fairly unexplored, there are still several research challenges. These challenges were discussed by experts from academia and industry in a multidisciplinary workshop at the 2023 IEEE Intelligent Vehicles Symposium. As a result of the workshop, this paper presents a list of most pressing research questions in the following areas: human-machine interaction and human factors, design of the remote station, design of the HAVs. It also outlines a roadmap for future research on remote assistance of HAV, thereby informing interdisciplinary studies and facilitating the benefits of HAVs before full autonomy can be reached.

Remote control technology for machines and robots has experienced significant advancement in many domains where visual information delivery is essential. Safety management at airports is one field that benefits from remote control systems, enabling operators to scan the airstrip for obstacles and debris. Depth perception and proper view position are critical in remote control systems, where operators need to accurately perceive 3D coordinates and maintain an appropriate perspective for performing tasks from a distance. This Demo paper presents a laboratory platform for an experimental study on human interaction with remote control systems using visual interfaces for inspection tasks to enhance airport safety management. The platform can evaluate the user experience of interfaces provided by First Person View, Third Person View, and Augmentation technologies. This platform enables exploration through controlled experiments and by user tests. These provide an avenue for assessing how these interfaces may affect human performance, depth perception, and user experience when conducting inspection tasks remotely. The findings will shed light on the strengths and limitations of each interface type, offering insights into their potential applications in various domains such as industrial inspection, surveillance, and remote exploration. 

Fully automated driving has posed more challenges than expected, and remote operation of heavy vehicles is increasingly getting attention. Therefore, human remote operators may have an essential role in compensating for the technological shortcomings in vehicle automation. This poses challenges in designing the work of human remote operators of automated heavy vehicles. This paper presents findings from a research project performed in collaboration between the RISE Research Institutes of Sweden and Scania. In the project, human-automation interaction requirements and challenges for remote operator work were explored through a simulator study. Before the study, three main operator tasks were defined: assessment, assistance, and remote driving. The simulation occurred in a transportation scenario where operators handled ten trucks driving on a public road and confined areas (transportation hub). Fifteen participants completed the study. The results provide examples and insights into classical automation-related challenges in a new context – the remote operation of heavy vehicles. Instances of challenges with situational awareness, out-of-the-loop, trust, and attention management were found and are discussed in relation to HMI design and requirements.

Autonomous shared ride vehicles may be prone to similar social issues and non-ideal passenger behaviors as today’s public transit. Such issues may include passengers littering, harassing others, and creating an environment that is generally unpleasant for riders. Transportation user experience designers should preemptively consider such scenarios early in their design work to help develop possible interfaces to manage social order and maintain good rider experience. Through a short video prototype, we present three possible non-ideal scenarios that may occur on shared autonomous shuttles and provide three potential solutions to begin a discussion around how to design for such non-ideal situations.

This study investigates interactive behaviors and communication cues of heavy goods vehicles (HGVs) and vulnerable road users (VRUs) such as pedestrians and cyclists as a means of informing the interactive capabilities of highly automated HGVs. Following a general framing of road traffic interaction, we conducted a systematic literature review of empirical HGV-VRU studies found through the databases Scopus, ScienceDirect and TRID. We extracted reports of interactive road user behaviors and communication cues from 19 eligible studies and categorized these into two groups: 1) the associated communication channel/mechanism (e.g., nonverbal behavior), and 2) the type of communication cue (implicit/explicit). We found the following interactive behaviors and communication cues: 1) vehicle-centric (e.g., HGV as a larger vehicle, adapting trajectory, position relative to the VRU, timing of acceleration to pass the VRU, displaying information via human-machine interface), 2) driver-centric (e.g., professional driver, present inside/outside the cabin, eye-gaze behavior), and 3) VRU-centric (e.g., racer cyclist, adapting trajectory, position relative to the HGV, proximity to other VRUs, eye-gaze behavior). These cues are predominantly based on road user trajectories and movements (i.e., kinesics/proxemics nonverbal behavior) forming implicit communication, which indicates that this is the primary mechanism for HGV-VRU interactions. However, there are also reports of more explicit cues such as cyclists waving to say thanks, the use of turning indicators, or new types of external human-machine interfaces (eHMI). Compared to corresponding scenarios with light vehicles, HGV-VRU interaction patterns are to a high extent formed by the HGV’s size, shape and weight. For example, this can cause VRUs to feel less safe, drivers to seek to avoid unnecessary decelerations and accelerations, or lead to strategic behaviors due to larger blind-spots. Based on these findings, it is likely that road user trajectories and kinematic behaviors will form the basis for communication also for highly automated HGV-VRU interaction. However, it might also be beneficial to use additional eHMI to compensate for the loss of more social driver-centric cues or to signal other types of information. While controlled experiments can be used to gather such initial insights, deeper understanding of highly automated HGV-VRU interactions will also require naturalistic studies. Copyright © 2022 Fabricius, Habibovic, Rizgary, Andersson and Wärnestål.

Small electric Autonomous Delivery Vehicles (ADV) can play an important role in future logistic chains under the last mile deliveries. In terminals where ADV are loaded with goods it is important that the interactions between the ADVS and the goods handling personnel is safe. Two workshops with developers of self-driving vehicles, researchers in the area of human-machine interaction and goods handling personnel form Postnord were conducted to identify challenges, needs and requirements regarding the design of ADV and the terminals för ADV. Due to COVID19, the workshops were carried out online and a video was shown to the participants demonstrating an ADV operating in a location representing a terminal. The two main objectives for this study were to gain understanding of the interactions between the ADV and human operators in the terminal and to identify high-level functional requirements for safe and efficient deployment of ADVs in terminals. The identified use cases related to (i) the ADV’s operations in the terminal, from entering to leaving the terminal and (ii) use cases where human operators interacted with the ADV, e.g. for loading/unloading goods. For each use case a high-level functional requirement was formulated. Human operators will most likely have important roles in delivery chains with ADV, such as loading and unloading of goods, as well as managing problems the ADV cannot solve. Consequently, how to design the human - ADV interactions will be critical from safety and efficiency points of view.

Autonomous vehicles are becoming a reality with great potential. However, persons with blindness, deafblindness, and deafness, who usually receive information and guidance from the driver, could miss information when travelling in an autonomous car. In this case study, 15 people with hearing and vision impairments explore and compare trips with and without vibrotactile guidance (using Ready-Ride or Ready-Move) in a simulated autonomous vehicle in real traffic (using a Wizard-of-Oz method). The study investigated if vibrotactile aid could enable persons with blindness, deafblindness, and deafness to use autonomous vehicles. Different phases of a trip (before, during, and after) were analysed. The study shows that people with functional impairments such as blindness, deafblindness, and deafness can perform trips independently if given information adapted to their needs through auditory, tactile, or visual information channels. It would be difficult for the target groups to travel without any additional communication aid, such as a vibrotactile guidance aid for all phases of the trip, especially for those with blindness. In all rides with the simulated autonomous car (Wizard-of-Oz set up) without vibrotactile guidance, the driver or assistant (in at least one phase of the trip) had to intervene for the research participants with blindness to complete the trip and continue the study. The study also highlights the usability of the vibrotactile guidance aid and identifies areas in need of improvement.