What happens when drivers of automated vehicles take over control in critical lane change situations?

According to legislation, take-overs initiated by the driver must always be possible during automated driving. For example, when drivers mistrust the automation to handle a critical and hazardous lane change, they might intervene and take over control while the automation is performing the maneuver. In these situations, drivers may have little time to avoid an accident and can be exposed to high lateral forces. Due to lacking research, it is yet unknown if they recognize the criticality of the situation and how they behave and perform to manage it. In a driving simulator study, participants (N = 60) accomplished eight double lane changes to evade obstacles in their lane. Time-to-collision and traction usage were varied to establish different degrees of objective criticality. To manipulate these parameters as required, participants were triggered to take over control by an acoustic cue. This setting shows what might happen if drivers disable the automation and complete the maneuver themselves. The results of the experiment demonstrate that drivers rated objectively more critical driving situations as more critical and responded to the hazard very fast over all experimental conditions. However, their behavior was more extreme with respect to decelerating and steering than necessary. This impaired driving performance and increased the risk of lane departures and collisions. The results of the experiment can be used to develop an assistance system that supports driver-initiated take-overs.     

Cognitive load while driving impairs memory of moving but not stationary elements within the environment

The negative impact of cognitive load, such as cell phone conversations, while driving is well established, but understanding the nature of this performance deficit is still being developed. To test the impact of load on awareness of different elements in a driving scene, memory for items within the environment was examined under load and no load conditions. Participants drove through two different scenarios in a driving simulator, were periodically interrupted by a pause in the driving during, and were asked questions regarding moving and stationary objects in the environment. Participants in the load condition drove while concurrently counting backwards by sevens. Results indicate that driving under load conditions led to diminished knowledge of moving, but not stationary, objects in the scene. This result suggests not all types of knowledge are equally impaired. Potential implications for current theories of cell phone use while driving and applied attention theory are discussed.     

An international survey on the incidence and modulating factors of carsickness

About two in three people have experienced carsickness at some point in their life (Reason & Brand, 1975). Little is known about current numbers of sufferers, cultural differences, or which modulating factors are being perceived as most relevant. Therefore, given a global increase of interest in carsickness driven by the development of automated vehicles, this survey intended to assess the status quo of carsickness in different parts of the world. We conducted an online survey with N = 4,479 participants in Brazil, China, Germany, UK and USA. 46% of participants indicated they had experienced some degree of carsickness in the past five years as a passenger in a car. When including childhood experiences, this rate increased to 59%, comparable to the 1975 findings by Reason and Brand. The highest and lowest incidence of carsickness was reported in China and Germany, respectively. In all countries, men and older participants reported a lower incidence of carsickness as compared to females and younger participants. The main modulating factors were found to be driving dynamics, visual activities, and low air quality. This study showed that carsickness still affects about 2/3 of passengers and discusses how its occurrence relates to in-transit activities and other modes of transport. The research provides a sound basis to further study how carsickness develops and to investigate countermeasures to potentially reduce it.     

中国古代医德教育对现代医学生医德教育的启示

医德医风已成为全社会普遍关注的焦点,特殊职业要求医务工作者应具有高尚的医德,而高尚医德的培养应从医学生教育阶段开始,努力提高医学生的医德素养。我国传统的医德教育方法,如医学生人品的选拔,老师言传身教,徒弟满师传统等等对于培养现代医学生关爱病人、救死扶伤的医德风范仍具有积极的借鉴意义。     

A correlation between sickness or injury within two weeks,chronic diseases and fatigue among adults aged 18–45 years

To investigate the prevalence of fatigue, the relationship between sickness or injury within two weeks, chronic diseases and fatigue among adults aged 18–45 years. Thousand five hundred and seventy nine individuals were included in this cross-sectional study. The Chalder Fatigue Scale (CFS) was used to assess fatigue defined as CFS score ≥4. The prevalence of fatigue was 25% in this study. Our results showed that only sickness or injury within two weeks (odds ratio [OR]: 2.440) and chronic diseases (OR: 1.727) were significantly related to fatigue. Moreover, their ORs for fatigue remained the same in all models (binary logistic regression models with adjusting for demographic and health-related characteristics one by one). In conclusion, fatigue was prevalent among adults aged 18–45 years. Sickness or injury within two weeks and chronic diseases were the risk factors for fatigue independent of demographic and health-related characteristics.     

Comparing simulator sickness in younger and older adults during simulated driving under different multisensory conditions

Driving simulators are valuable tools for traffic safety research as they allow for systematic reproductions of challenging situations that cannot be easily tested during real-world driving. Unfortunately, simulator sickness (i.e., nausea, dizziness, etc.) is common in many driving simulators and may limit their utility. The experience of simulator sickness is thought to be related to the sensory feedback provided to the user and is also thought to be greater in older compared to younger users. Therefore, the present study investigated whether adding auditory and/or motion cues to visual inputs in a driving simulator affected simulator sickness in younger and older adults. Fifty-eight healthy younger adults (age 18–39) and 63 healthy older adults (age 65+) performed a series of simulated drives under one of four sensory conditions: (1) visual cues alone, (2) combined visual + auditory cues (engine, tire, wind sounds), (3) combined visual + motion cues (via hydraulic hexapod motion platform), or (4) a combination of all three sensory cues (visual, auditory, motion). Simulator sickness was continuously recorded while driving and up to 15 min after driving session termination. Results indicated that older adults experienced more simulator sickness than younger adults overall and that females were more likely to drop out and drove for less time compared to males. No differences between sensory conditions were observed. However, older adults needed significantly longer time to fully recover from the driving session than younger adults, particularly in the visual-only condition. Participants reported that driving in the simulator was least realistic in the visual-only condition compared to the other conditions. Our results indicate that adding auditory and/or motion cues to the visual stimulus does not guarantee a reduction of simulator sickness per se, but might accelerate the recovery process, particularly in older adults.     

A simulation sickness study on a driving simulator equipped with a vibration platform

Simulator sickness is a well-known side effect of driving simulation which may reduce the passenger well-being and performance due to its various symptoms, from pallor to vomiting. Numerous reducing countermeasures have been previously tested; however, they often have undesirable side effects. The present study investigated the possible effect of seat vibrations on simulator sickness. Three configurations were tested: no vibrations, realistic ones and some that might affect the proprioception. Twenty-nine participants were exposed to the three configurations on a four-minute long automated driving in a simulator equipped with a vibration platform. Simulator sickness was estimated thanks to the Simulator Sickness Questionnaire (SSQ) and to a postural instability measure. Results showed that vibrations help to reduce the sickness. Our findings demonstrate that some specific vibration configurations may have a positive impact on the sickness, thus confirming the usefulness of devices reproducing the road vibrations in addition to creating more immersion for the driver.     

Are novice drivers competent to take over control from level 3 automated vehicles? A comparative study with experienced drivers

With level 3 automated vehicles poised to appear on the roads soon, takeover remains a major challenge. At present, the effect of manual driving experience on takeover performance is unknown. Therefore, a simulator study was conducted to investigate the influence of driving experience (novice and experienced) on takeover performance in different takeover time budgets (7 s and 5 s) and in combination with a visual secondary task (i.e., surrogate reference task). Data from 48 young and middle-aged participants consisting of 24 novice and 24 experienced drivers were used for this study. Researchers found that the overall stability of evasive maneuvers by novice drivers was considerably worse than that by experienced drivers. A detailed analysis showed that the influence of driving experience on takeover stability was mainly reflected in longitudinal control rather than lateral control. A significant interaction between driving experience and visual secondary task showed that the latter had a substantial impact on the takeover stability of experienced drivers but not on that of novice drivers. Researchers also found that rich manual driving experience cannot make the takeover process of experienced drivers more stable than that of novice drivers under conditions of eye-off-road. In addition, no significant difference was found between novice and experienced drivers in automation disengagement time, takeover time and minimum time to collision. Results indicate that novice drivers have poor takeover stability and weak adaptability, but their longitudinal collision risk is not deteriorated by the lack of manual driving experience.     

Takeover performance of older drivers in automated driving: A review

IntroductionThe introduction of automated vehicles to the road environment brings new challenges for older drivers. Level 3 of conditional automation requires drivers to take over control of their vehicle whenever the automated system reaches its limits. Even though autonomous vehicles may be of great benefit to older drivers in terms of safely maintaining their mobility, a better understanding of their takeover performance remains crucial. The objective of this review of the literature is to shed more light on the effects that aging has on takeover performance during automated driving.MethodsThree database searches were conducted: PsychINFO, Web Of Sciences, and TRID. Studies from the last decade which included groups of older drivers were reviewed.ResultsAfter checking through abstracts and texts of articles, 9 articles, 4 proceedings papers, and 1 technical report were included in this review. All studies included a driving simulator that refers to level 3 of automation (which requires supervision by the driver). Five out of fourteen studies showed that older adults had poorer takeover performance (in terms of takeover time and takeover quality) than younger adults. However, several factors, such as the type of non-driving related task (NDRT), were seen to influence takeover performance in older adults. Speed, type and duration of notification interval, distribution and duration of driving modes, and number of takeovers were all also factors of influence.ConclusionThis review synthesizes the results of 14 articles which investigate the effects of age-related changes on takeover performance. Various external factors as NDRTs, speed, type and duration of notification to take over, duration of the automated phase, distribution of the automated/manual phases may affect takeover performance in older adults. Even if the majority of articles showed that older adults are globally slower at taking over a vehicle than younger adults, findings concerning take over quality yield divergent results. It's probably due to age related cognitive changes, particularly in executive functions or to a great heterogeneity in this population. This literature review highlights the need to develop new research on the impact of aging on takeover performance.     

Supporting cooperative driving behaviour by technology – HMI solution,acceptance by drivers and effects on workload and driving behaviour

The paper compares and evaluates three different HMIs (Human Machine Interface) for an ADAS (Advanced Driver Assistance System) supporting cooperative interactions between drivers while merging and turning left. In road traffic, cooperation means that drivers (cooperation partners) coordinate their driving behaviour in a way that they facilitate each other’s intended driving manoeuvres. An experimental study was conducted with 30 participants in a static high-end simulator. The test scenarios included merging onto a motorway and turning left at a rural intersection. As independent variables, the HMI (Baseline vs. Sensor vs. C2X (Car-to-everything)) was varied in addition to the cooperation situation (merging vs. turning left). All HMI variants were based on a HUD (Head-Up Display). In the Baseline condition, the HMI only showed information about speed and navigation. The Sensor HMI visualised additionally the driving situation as it can be detected by the vehicle's own sensors. The C2X HMI was based on C2X communication and also represented the different phases of manoeuvre coordination with the cooperation partner. The traffic flow and the behaviour of the surrounding traffic did not differ between the different HMI variants, in order to ensure that the traffic situation did not influence the participants’ evaluation of the HMI variants. The dependent variables included subjective (e.g. acceptance, usability) and objective measures (e.g. driving and gaze behaviour). The results showed that a system supporting cooperative interactions is generally accepted by drivers. The most preferred system was the C2X HMI. The advantages of a C2X based HMI were an improved user experience leading to a greater intent to use the ADAS for cooperative driving interactions, increased system trust, and an easier handling of the system. The workload of the C2X HMI did not exceed the level reported for the Baseline or the Sensor HMI – although the C2X HMI presented more information. The results are used to derive indications for the design of assistance systems supporting cooperative driving behaviour.