Due to the lack of active involvement in the driving situation and due to monotonous driving environments drivers with automation may be prone to become fatigued faster than manual drivers (e.g. ...Schömig et al., 2015). However, little is known about the progression of fatigue during automated driving and its effects on the ability to take back manual control after a take-over request. In this driving simulator study with Nö=ö60 drivers we used a three factorial 2ö×ö2ö×ö12 mixed design to analyze the progression (12ö×ö5ömin; within subjects) of driver fatigue in drivers with automation compared to manual drivers (between subjects). Driver fatigue was induced as either mainly sleep related or mainly task related fatigue (between subjects). Additionally, we investigated the drivers’ reactions to a take-over request in a critical driving scenario to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving.
Drivers in the automated driving condition exhibited facial indicators of fatigue after 15 to 35ömin of driving. Manual drivers only showed similar indicators of fatigue if they suffered from a lack of sleep and then only after a longer period of driving (approx. 40ömin). Several drivers in the automated condition closed their eyes for extended periods of time. In the driving with automation condition mean automation deactivation times after a take-over request were slower for a certain percentage (about 30%) of the drivers with a lack of sleep (Mö=ö3.2; SDö=ö2.1ös) compared to the reaction times after a long drive (Mö=ö2.4; SDö=ö0.9ös). Drivers with automation also took longer than manual drivers to first glance at the speed display after a take-over request and were more likely to stay behind a braking lead vehicle instead of overtaking it.
Drivers are unable to stay alert during extended periods of automated driving without non-driving related tasks. Fatigued drivers could pose a serious hazard in complex take-over situations where situation awareness is required to prepare for threats. Driver fatigue monitoring or controllable distraction through non-driving tasks could be necessary to ensure alertness and availability during highly automated driving.
•We investigated manual drivers’ reactions to Level 3 vehicles in repeated interactions.•Manual drivers rated driving in non-automated traffic as safer than driving in mixed traffic.•Manual drivers ...identified Level 3 vehicles in mixed traffic based on the status eHMI.•Manual drivers’ speed decreased as the penetration rate of Level 3 vehicles increased.
In the near future, conditionally automated vehicles (CAVs; SAE Level 3) will travel alongside manual drivers (≤ SAE level 2) in mixed traffic on the highway. It is yet unclear how manual drivers will react to these vehicles beyond first contact when they interact repeatedly with multiple CAVs on longer highway sections or even during entire highway trips. In a driving simulator study, we investigated the subjective experience and behavioral reactions of N = 51 manual drivers aged 22 to 74 years (M = 41.5 years, SD = 18.1, 22 female) to driving in mixed traffic in repeated interactions with first-generation Level 3 vehicles on four highway sections (each 35 km long), each of which included three typical speed limits (80 km/h, 100 km/h, 130 km/h) on German highways. Moreover, the highway sections differed regarding the penetration rate of CAVs in mixed traffic (within-subjects factor; 0%, 25%, 50%, 75%). The drivers were assigned to one of three experimental groups, in which the CAVs differed regarding their external marking, (1) status eHMI, (2) no eHMI, and (3) a control group without information about the mixed traffic. After each highway section, drivers rated perceived safety, comfort, and perceived efficiency. Drivers were also asked to estimate the penetration rate of CAVs on the previous highway section. In addition, we analyzed drivers’ average speed and their minimum time headways to lead vehicles for each speed zone (80 km/h, 100 km/h, 130 km/h) as well as the percentage of safety critical interactions with lead vehicles (< 1 s time headway). Results showed that manual drivers experienced driving in mixed traffic, on average, as more uncomfortable, less safe and less efficient than driving in manual traffic, but not as dangerous. A status eHMI helps manual drivers identify CAVs in mixed traffic, but the eHMI had no effect on manual drivers’ subjective ratings or driving behavior. Starting at a level of 25% Level 3 vehicles in mixed traffic, participants' average speed decreased significantly. At the same time, the percentage of safety critical interactions with lead vehicles increased with an increasing penetration rate of CAVs. Accordingly, additional measures may be necessary in order to at least keep the existing safety level of driving on the highway.
Forced and mixed convection has been investigated experimentally in a full scale passenger aircraft cabin mock-up. The mock-up represents a generic cabin section of the A380 upper deck. Large scale ...particle image velocimetry (PIV) and temperature field measurements were conducted in a cross sectional plane of the cabin mock-up. The flow fields for two different air inlet configurations were measured and analysed under isothermal and cooling conditions. Furthermore the flow rates at the different air inlet positions were varied while keeping the air exchange rate constant. Our extensive experimental parametric study demonstrates that the flow field in aircraft cabins is affected by various fluid mechanical phenomena. Interaction between the supplied air jets, negative buoyancy forces acting on these air jets and interaction of thermal plumes with the supplied air jets, all influence the flow field inside the cabin. The impact of these effects differs considerably depending on the ventilation configuration and relative mass flow settings at the supply inlets.
The application of Particle Image Velocimetry (PIV) to measurement of flows on large scales is a challenging necessity especially for the investigation of convective air flows. Combining helium ...filled soap bubbles as tracer particles with high power quality switched solid state lasers as light sources allows conducting PIV on scales of the order of several square meters. The technique was applied to mixed convection in a full scale double aisle aircraft cabin mock-up for validation of Computational Fluid Dynamics simulations.
•We analyzed transitions of control from highly automated driving to manual driving.•We studied drivers’ reactions to sudden events after a take-over.•Drivers’ automation deactivation may not ...necessarily imply situation awareness.•Highly distracted automated drivers need more time to rebuild situation awareness.•Future systems should provide support before and after the automation deactivation.
Previous research has shown that drivers are generally able to deactivate the automation in an automated vehicle after a Take-Over Request (TOR) in a relatively short time frame of approximately 3–5 s on average (e.g. Gold, Körber, Hohenberger, Lechner, & Bengler, 2015; Melcher, Rauh, Diederichs, Widlroither, & Bauer, 2015). However, it is yet unclear if drivers are able to adequately react to unexpected traffic events shortly after the transition of control and some studies have shown that stabilizing the vehicle after this transition may take longer than deactivating the automation (e.g. Merat, Jamson, Lai, Daly, & Carsten, 2014). This study addresses this issue by examining the drivers’ reactions following a TOR during an automated drive with highly distracting Non-Driving Related Tasks (NDRTs). We investigated the reactions of N = 60 participants to five complex take-over scenarios with unexpected events after the TOR in a driving simulator study. Participants were assigned to two distracted conditions with automation (playing a game on a tablet pc, reading on a tablet pc), a no task condition and a manual driving condition.
90% of the participants in the distracted conditions deactivated the automation after 7–8 s. Brake reaction times to the unexpected event were comparable between automation and manual driving conditions. However, compared to manual drivers, distracted drivers with automation showed a delay of up to 5 s regarding the time to the first gaze to the side mirror and the first gaze to the speedometer after the TOR.
Distracted drivers are relatively fast at taking back control over the vehicle after an automated drive and are generally able to react to the onset of sudden events. However, they may require additional time and assistance to fully perceive and understand complex traffic situations and to reach a level of situation awareness comparable to manual drivers. Future research should therefore aim to support the driver during the transition to manual driving, in order to avoid critical situations and to systematically build up situation awareness.
To measure large-scale flow structures in air, a tomographic particle image velocimetry (tomographic PIV) system for measurement volumes of the order of one cubic metre is developed, which employs ...helium-filled soap bubbles (HFSBs) as tracer particles. The technique has several specific characteristics compared to most conventional tomographic PIV systems, which are usually applied to small measurement volumes. One of them is spot lights on the HFSB tracers, which slightly change their position, when the direction of observation is altered. Further issues are the large particle to voxel ratio and the short focal length of the used camera lenses, which result in a noticeable variation of the magnification factor in volume depth direction. Taking the specific characteristics of the HFSBs into account, the feasibility of our large-scale tomographic PIV system is demonstrated by showing that the calibration errors can be reduced down to 0.1 pixels as required. Further, an accurate and fast implementation of the multiplicative algebraic reconstruction technique, which calculates the weighting coefficients when needed instead of storing them, is discussed. The tomographic PIV system is applied to measure forced convection in a convection cell at a Reynolds number of 530 based on the inlet channel height and the mean inlet velocity. The size of the measurement volume and the interrogation volumes amount to 750 mm × 450 mm × 165 mm and 48 mm × 48 mm × 24 mm, respectively. Validation of the tomographic PIV technique employing HFSBs is further provided by comparing profiles of the mean velocity and of the root mean square velocity fluctuations to respective planar PIV data.
Large-scale tomographic particle image velocimetry (tomographic PIV) was used to study large-scale flow structures of turbulent convective air flow in an elongated rectangular convection cell. Three ...flow cases have been investigated, that is, pure forced convection and mixed convection at two different Archimedes numbers. The Reynolds number was constant at
Re
= 1.04 × 10
4
for all cases, while the Archimedes numbers were
Ar
= 2.1 and 3.6 for the mixed convection cases, corresponding to Rayleigh numbers of
Ra
= 1.6 × 10
8
and 2.8 × 10
8
, respectively. In these investigations, the size of the measurement volume was as large as 840 mm × 500 mm × 240 mm. To allow for statistical analysis of the measured instantaneous flow fields, a large number of samples needed to be evaluated. Therefore, an efficient parallel implementation of the tomographic PIV algorithm was developed, which is based on a version of the simultaneous multiplicative reconstruction technique (SMART). Our algorithm distinguishes itself amongst other features by the fact that it does not store any weighting coefficients. The measurement of forced convection reveals an almost two-dimensional roll structure, which is orientated in the longitudinal cell direction. Its mean velocity field exhibits a core line with a wavy shape and a wavelength, which corresponds to the height and depth of the cell. In the instantaneous fields, the core line oscillates around its mean position. Under the influence of thermal buoyancy forces, the global structure of the flow field changes significantly. At lower Archimedes numbers, the resulting roll-like structure is shifted and deformed as compared to pure forced convection. Additionally, the core line oscillates much more strongly around its mean position due to the interaction of the roll structure with the rising hot air. If the Archimedes number is further increased, the roll-like structure breaks up into four counter-rotating convection rolls as a result of the increased influence of buoyancy forces. Moreover, large-scale tomographic PIV reveals that the orientation of these rolls reflects a ‘W’-like shape in the horizontal
X
–
Z
-plane of the convection cell.
The production and retention of written records was an important facet of pre-modern rulership and administration. While such documents’ contents have been well studied, much can still be learnt by ...examining these records as artefacts. This volume is devoted to the material features of a range of records from early China and medieval Europe, which shed new light on the functioning of government and the declarations of power contained within them.
•We studied mixed traffic interactions from a manual driver’s perspective.•Manual drivers can identify automated vehicles by their driving behavior.•Drivers rated interactions with automated vehicles ...as safe as those with manual drivers.•Strict rule-following can lead to manual drivers keeping short a time headway to lead Level 3 vehicles.•A status eHMI for Level 3 vehicles on the highway might not be recommendable.
Soon, manual drivers will interact with conditionally automated vehicles (CAVs; SAE Level3) in a mixed traffic on highways. As of yet, it is largely unclear how manual drivers will perceive and react to this new type of vehicle. In a driving simulator study with N = 51 participants aged 20 to 71 years (22 female), we examined the experience and driving behavior of manual drivers at first contact with Level 3 vehicles in four realistic driving scenarios (highway entry, overtaking, merging, introduction of a speed limit) that Level 3 vehicles may handle alone once their operational domain extends beyond driving in congested traffic. We also investigated the effect of an external marking via a visual external human–machine interface (eHMI), with participants being randomly assigned to one of three experimental groups (none, correct, incorrect marking). Participants experienced each driving scenario four times, twice with a human-driven vehicle (HDV), and twice with a CAV. After each interaction, participants rated perceived driving mode of the target vehicle as well as perceived safety and comfort. Minimum time headways between participants and target vehicles served as an indicator of safety criticality in the interactions. Results showed manual driver can distinguish CAVs from HDVs based on behavioral differences. In all driving scenarios, participants rated interactions with CAVs at least as safe as interactions with HDVs. The driving data analysis showed that manual driver interactions with CAVs were largely uncritical. However, the CAVs’ strict rule-compliance led to short time headways of following manual drivers in some cases. The eHMI used in this study neither affected the subjective ratings of the manual drivers nor their driving behavior in mixed traffic. Thus, the results do not support the use of eHMIs on the highway, at least not for the eHMI design used in this study.
ObjectivesTo explore the toxicity of low-dose methotrexate (MTX), an uncommon, but life-threatening event.MethodsWe analysed the presentation, course and risk factors of all patients admitted to the ...rheumatology ward with severe low-dose MTX toxicity. These patients were compared with patients without signs of relevant MTX toxicity.ResultsThe 12 patients admitted for MTX toxicity included 7 patients with rheumatoid arthritis, 2 with psoriatic arthritis or psoriasis, 2 patients with giant cell arteritis and 1 with myositis. 1 patient died from infections, while 11 survived under folinic acid administration. All patients suffering from severe MTX toxicity were older than 70 years and were therefore compared with 400 patients who were also older than 70 years, but without MTX toxicity. Of these 400 control patients, the group of patients not on MTX (n=232) had more renal impairment than the group of patients on MTX (n=168). Compared with the 168 MTX-treated patients without toxicity, the 12 patients with life-threatening toxic events had a lower median estimated glomerular filtration rate (eGFR) at the routine visit preceding the acute event (64 (range 32–77) vs 69 (range 8 to >90) mL/min x 1.73, p=0.0251). A multivariate analysis found that patients with toxicity were more frequently treated with diuretics (6/12 vs 24/168), proton pump inhibitors (PPIs; 10/12 vs 70/168) and levetiracetam (2/12 vs 1/168).ConclusionsPatients older than 70 years with lower eGFR and being on diuretics, but also on PPIs and levetiracetam, have a significantly higher risk for MTX toxicity.