The introduction of (fully) automated vehicles has generated a re-interest in motion sickness, given that passengers suffer much more from motion sickness compared to car drivers. A suggested solution is to improve the anticipation of passive self-motion via cues that alert passengers of changes in the upcoming motion trajectory. We already know that auditory or visual cues can mitigate motion sickness. In this study, we used anticipatory vibrotactile cues that do not interfere with the (audio)visual tasks passengers may want to perform. We wanted to investigate (1) whether anticipatory vibrotactile cues mitigate motion sickness, and (2) whether the timing of the cue is of influence. We therefore exposed participants to four sessions on a linear sled with displacements unpredictable in motion onset. In three sessions, an anticipatory cue was presented 0.33, 1, or 3 s prior to the onset of forward motion. Using a new pre-registered measure, we quantified the reduction in motion sickness across multiple sickness scores in these sessions relative to a control session. Under the chosen experimental conditions, our results did not show a significant mitigation of motion sickness by the anticipatory vibrotactile cues, irrespective of their timing. Participants yet indicated that the cues were helpful. Considering that motion sickness is influenced by the unpredictability of displacements, vibrotactile cues may mitigate sickness when motions have more (unpredictable) variability than those studied here.

Various studies have demonstrated a role for cognition on self-motion perception. Those studies all concerned modulations of the perception of a physical or visual motion stimulus. In our study, however, we investigated whether cognitive cues could elicit a percept of oscillatory self-motion in the absence of sensory motion. If so, we could use this percept to investigate if the resulting mismatch between estimated self-motion and a lack of corresponding sensory signals is motion sickening. To that end, we seated blindfolded participants on a swing that remained motionless during two conditions, apart from a deliberate perturbation at the start of each condition. The conditions only differed regarding instructions, a secondary task and a demonstration, which suggested either a quick halt ("Distraction") or continuing oscillations of the swing ("Focus"). Participants reported that the swing oscillated with larger peak-to-peak displacements and for a longer period of time in the Focus condition. That increase was not reflected in the reported motion sickness scores, which did not differ between the two conditions. As the reported motion was rather small, the lack of an effect on the motion sickness response can be explained by assuming a subthreshold neural conflict. Our results support the existence of internal models relevant to sensorimotor processing and the potential of cognitive (behavioral) therapies to alleviate undesirable perceptual issues to some extent. We conclude that oscillatory self-motion can be perceived in the absence of related sensory stimulation, which advocates for the acknowledgement of cognitive cues in studies on self-motion perception.

With the arrival of new technologies more en-route traffic information sources have become available, especially in-car information sources. The aim of this study is to gain more insight into the effect of multiple, and possibly conflicting, sources of information on route choice and driver behaviour. In a driving simulator experiment, participants were required to make multiple drives, each of which ended with a choice between the normal and an alternative route. On each trial participants received traffic information from a Variable Message Sign (VMS), i.e. a dynamic sign above the road providing descriptive traffic information in the form of expected travel times (ETTs), a navigation device providing in-car prescriptive route advice, or information from both sources. In the latter type of trial the information could be congruent or conflicting with regards to ETTs on the VMS and advise from the navigation. After each trial, participants indicated how much trust they had in the traffic information and their primary information source. A Bayesian model was used to quantify the propensity to switch to the alternative route. Results indicate that overall compliance was very high for the primary source even when the other source did not corroborate this information and that most participants preferred to use the information from a VMS. However, when both the VMS and the navigation device provided information and the VMS indicated the same ETTs for the normal and alternative route, route choice was influenced by the advice provided by the navigation device. Also, in this type of trial mean speed was significantly lower compared to trials in which the two sources were in conflict, indicating increased mental workload, most likely due to attentional dissonance: a situation in which stimuli compete for attention resulting in cognitive conflict and the need to inhibit non-relevant information. A deeper understanding of how drivers use multiple traffic information sources and cope with irrelevant information could support driver safety and comfort, increase the usability of information sources, and help reduce stress, anxiety, and information overload while driving.

This study provides a comprehensive overview of the way consumers and car sellers are currently informed about Advanced Driver Assistance Systems (ADAS). In order to gain any economical, comfort and safety benefits from automated car systems, drivers need to know how to safely and efficiently use them. Still, it remains largely unknown if, and how, consumers are informed about ADAS when buying a car. Naturally, sales staff has to be accurately informed and instructed as well to inform customers. Two separate nationwide surveys were administered among consumers and car sellers across The Netherlands to gain insight on how they are currently informed about ADAS. The results of our study show several issues about the way that both consumers and car sellers are informed about ADAS. First, almost a quarter of the drivers did not receive any information about the ADAS in the car that they bought. Of the drivers that did receive information, only 9% was able to try out the automated systems before taking the car home. Almost 40% of the car sellers did not receive (sufficient) information about ADAS. However, brand dealers more often received sufficient information about ADAS compared to independent dealers. These issues need to be addressed now to avoid unsafe use of ADAS, but also unsafe use of more complex automated systems that are being incorporated into commercial cars. We propose several opportunities for improvement and standardization which may be implemented by the automotive industry, stakeholder organizations or the government.

In conditionally automated driving, drivers do not have to monitor the road, whereas in partially automated driving, drivers have to monitor the road permanently. We evaluated a dynamic allocation of monitoring tasks to human and automation by providing a monitoring request (MR) before a possible take-over request (TOR), with the aim to better prepare drivers to take over safely and efficiently. In a simulator-based study, an MR + TOR condition was compared with a TOR-only condition using a within-subject design with 41 participants. In the MR + TOR condition, an MR was triggered 12 s before a zebra crossing, and a TOR was provided 7 s after the MR onset if pedestrians crossing the road were detected. In the TOR-only condition, a TOR was provided 5 s before the vehicle would collide with a pedestrian if the participant did not intervene. Participants were instructed to perform a self-paced visual-motor non-driving task during automated driving. Eye tracking results showed that participants in the MR + TOR condition responded to the MR by looking at the driving environment. They also exhibited better take-over performance, with a shorter response time to the TOR and a longer minimum time to collision as compared to the TOR-only condition. Subjective evaluations also showed advantages of the MR: participants reported lower workload, higher acceptance, and higher trust in the MR + TOR condition as compared to the TOR-only condition. Participants' reliance on automation was tested in a third drive (MR-only condition), where automation failed to provide a TOR after an MR. The MR-only condition resulted in later responses (and errors of omission) as compared to the MR + TOR condition. It is concluded that MRs have the potential to increase safety and acceptance of automated driving as compared to systems that provide only TORS. Drivers' trust calibration and reliance on automation need further investigation. (C) 2019 Elsevier Ltd. All rights reserved.

Partially automated car systems are expected to soon become available to the public. However, in order for any of the potential benefits of automated driving to arise, the driver and car need to establish effective, efficient and satisfactory interactions. Otherwise, the driver may rely too much on the automated car system, leading to dangerous situations or not relying on the system at all, making the automation pointless. This study studied whether the current method of providing information on (automated) car systems to drivers, which is mainly through owner's manuals, can bring the driver's mental model in accordance with the car's capabilities. A total of 28 participants took part in a video- based driving simulator experiment. The participants were split into two groups: the first received no information about the system while the second did receive specific information about functionalities and system limitations. Each participant was seated in a driving simulator and experienced a partially automated car driving in city situations by means of videos projected on the outer screen. Participants were asked to indicate through the push of a button on the steering wheel if they felt that the car could no longer cope with the situation, and would take back control from the car if they were driving it on the real road. Each video was categorized as 'requires a take-over' or 'does not require a take-over' before the experiment, based on the system descriptions the participants received. Overall, the system information did not appear to support the participants in correctly deciding whether to take over or to rely on the system. The mental models of the participants did not seem to (sufficiently) change through the system information. Owner's manuals may not be sufficient for future systems to provide drivers the necessary tools to be able to decide whether it is necessary to take back control of the car. In-vehicle support, tuned to the driver and the specific situation may be needed to safely guide this process. (C) 2018 Elsevier Ltd. All rights reserved.

Automated driving can fundamentally change road transportation and improve quality of life. However, at present, the role of humans in automated vehicles (AVs) is not clearly established. Interviews were conducted in April and May 2015 with 12 expert researchers in the field of human factors (HFs) of automated driving to identify commonalities and distinctive perspectives regarding HF challenges in the development of AVs. The experts indicated that an AV up to SAE Level 4 should inform its driver about the AV's capabilities and operational status, and ensure safety while changing between automated and manual modes. HF research should particularly address interactions between AVs, human drivers and vulnerable road users. Additionally, driver-training programmes may have to be modified to ensure that humans are capable of using AVs. Finally, a reflection on the interviews is provided, showing discordance between the interviewees' statements - which appear to be in line with a long history of HFs research - and the rapid development of automation technology. We expect our perspective to be instrumental for stakeholders involved in AV development and instructive to other parties.

Studies show that drivers' intention to use automated vehicles is strongly modulated by trust. It follows that their benefits are unlikely to be achieved if users do not trust them. To date, most studies of trust in automated vehicles have relied on self-reports. However, questionnaires cannot capture real-time changes in drivers' trust, and are hard to use in applied settings. In previous work, we found evidence that gaze behaviour could provide an effective measure of trust. In this study we tested whether combining gaze behaviour with Electrodermal Activity could provide a stronger metric. The results indicated a strong relationship between self-reported trust, monitoring behaviour and Electrodermal Activity: The higher participants' self-reported trust, the less they monitored the road, the more attention they paid to a non-driving related secondary task, and the lower their Electrodermal Activity. We also found evidence that combined measures of gaze behaviour and Electrodermal Activity predict self-reported trust better than either of these measures on its own. These findings suggest that such combined measures have the potential to provide a reliable and objective real-time indicator of driver trust. (C) 2019 Elsevier Ltd. All rights reserved.

•Highly automated driving (HAD) reduces workload considerably.•Adaptive cruise control (ACC) yields only a small reduction of workload.•ACC and HAD can improve but also degrade situation awareness.•Feedback can alleviate much of the Human Factors issues of ACC and HAD.

Recent technological developments have shown a transition from informative driving support systems to more automated vehicles. Although automated vehicles are designed to overcome limitations in human perception, decision making and response, there may be a downside to introducing these technologies. The downside is based on the new cooperation between the driver and the vehicle, leaving room for misinterpretation, overreliance on system performance and loss of situation awareness in case of requested transfer of control from the automated vehicle back to the driver. This article raises several human factors issues that are of importance when designing (semi-)automated vehicles, such as: the driver as a system monitor, situation awareness and system limitations. Various implications for the design of automated systems are discussed.

TrafficQuest inventariseert doorlopend de stand van zaken met betrekking tot en de richting waarin ontwikkelingen plaatsvinden. Verkeersmanagement staat nog maar aan het begin van veel veranderingen. Allerlei ontwikkelingen zullen het mogelijk maken effectiever, proactiever en netwerkbreed toe te passen. Daarvoor is verder onderzoek nodig. In het boekje De toekomst van verkeersmanagement wordt daarom een onderzoeksagenda gepresenteerd. Dit boekje is te vinden op de TrafficQuest website (www.traffic-quest.nl). Bij het schrijven van dit boekje, heeft TrafficQuest veel achterliggend materiaal over allerlei aspecten van verzameld. Dit materiaal wordt in een reeks van rapporten gepubliceerd worden. Deze rapporten volgen steeds het stramien: • Waar hebben we het over? • Hoever zijn we in Nederland? • Hoever zijn ze elders? • Wat hebben we eraan? • Waar gaan we naar toe? Dit rapport behandelt deze vragen voor het onderwerp human factors in verkeersmanagement. Echter, de vraag ‘hoever zijn ze elders?’ wordt niet besproken. Dat wordt voor een volgende keer bewaard.