Automatiserade transporter har potential att minska trängsel och miljöbelastning och att öka trafiksäkerhet. Länder som USA, Kina, Norge, och Tyskland har alla pilotprojekt eller kommersiell drift av autonoma fordon för persontransport. I Sverige har flera piloter genomförts med mindre sofistikerad självkörning.Syftet med det här projektet var att analysera de hinder och möjliggörare som finns för en storskalig implementering av automatiserade transporter i Sverige och målet med projektet var att erbjuda Vinnova rekommendationer för att stötta införande av automatiserade transporter i SverigeProjektet inkluderade litteraturstudier, workshops, och intervjuer. Litteraturstudien visade att många initiativ fokuserat på möjliggörande teknologier inom automatiserade transporter i Sverige. Tidigare forskningsprojekt som fokuserat på kartläggning har identifierat viktiga hinder såsom otydlighet kring aktörsansvar och behovet av koordinerad samverkan. Framgångsrika internationella exempel, som Hamburgs samarbete med MOIA, kan tjäna som modell för svenska implementeringar. Det brittiska ramverket för autonoma fordon kan också ge vägledning för svensk lagstiftning.Projektet genererade en lista med rekommendationer för Vinnova. Fyra potentiella strategier för Sveriges roll inom automatiserade transporter identifierades och speglas i näringspolitiska och trafikpolitiska perspektiv. Fokus ligger i dessa strategier på att antingen attrahera internationella företag, genomföra stora effektfulla demonstrationsprojekt, stärka inhemska innovationer, eller att avvakta med AD.

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.

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.