Alternative options for dealing with automation failures: Automated stopping vs. Taking over manual control

Previous research has investigated the driver’s ability to resume control after an automation failure. This study considers situation criticality, safety and difficulty between take-over and automated stop scenarios. Findings are reported of an experimental study investigating different strategies to take back control of an automated road vehicle. The study had a mixed factorial design with automation being the between-participants factor with two levels, SAE Level 1 vs. SAE Level 3. Urgency (High vs Low) and Take-Over Mode (Manual, Automated Stop) were the within participants factors. Dependent variables were: i) Minimum Time-to-Collision (TTC), ii) Self-reported Situation Criticality and Perceived Safety and iii) Percentage of Gazes to [the] Road Centre. Overall, 36 participants took part, with half assigned to either level of the Automation factor. The automated driving experience was designed to fail during participation. This required the driver to take-over manual control or have the system bring the vehicle to an automated stop. Results revealed that during manual take-over of control, measures of time-to-collision, perceived criticality and safety were worse and fixations to the forward view increased when compared to the Automated stop condition. Manual take-over of control in a high-urgency situation revealed higher criticality (shorter time-to-collision and lower perceived safety) and more difficulty (increasing fixations to the road centre) than in a low-urgency situation. The study points to an automated stopping manoeuvre being the preferable strategy to manual take-over of control.     

On computing ELECTRE's credibility indices under partial information

The ELECTRE family of decision aid methods is a well‐known approach to help decision makers (DMs) advance in a decision process. Among the most recent methods in the family, ELECTRE IS, III, and TRI compute fuzzy indices for the credibility of a given action outranking some other. We consider the case when the DMs are unsure which values each parameter should take, which may result from insufficient, imprecise or contradictory information, as well as from different preferences among a group of DMs. In the framework of a robustness analysis approach, where DMs provide only partial information on the parameter values (through constraints on acceptable combinations), we study how to find whether an outranking among two actions in an ELECTRE method is robust. In this context, we study the resulting nonlinear problems of optimizing a credibility index (under the type of constraints that we consider to appear in practice) and present some examples. Copyright © 1999 John Wiley & Sons, Ltd.     

Exploring the usage of supervised driving automation in naturalistic conditions

This study reports usage of supervised automation and driver attention from longitudinal naturalistic driving observations. Automation inexperienced drivers were provided with instrumented vehicles with adaptive cruise control (ACC) and lane keeping (LK) features (SAE level 2). Data was collected comparing one month of driving without support to two months where drivers were instructed to use automation as desired.On highways, level 2 automation was used respectively 63% and 57% of the time by Tesla and BMW users, with peak usage during slow stop-and-go traffic (0–30 km/h) and higher speeds (>80 km/h). On roads with speed limits below 70 km/h, automation was used less than 8%, and use on urban roads was incidental rather than habitual. Automation usage increased with time in trip, but no clear time of day effects were found. Head pose data could not classify driver attention, and we recommend gaze tracking in future studies. Head pose deviation was selected as alternative indicator for monitoring activity. Comparing among forms of automation usage on the highway, head heading deviation was smallest during ACC use, but did not differ between automation and baseline manual driving. Head heading deviation during manual driving was smaller in the baseline than the experimental phase, which suggests that motives for manual highway driving may be attention related. Automation usage did not change much over the first 12 weeks of the experimental condition, and there were no longitudinal changes in head pose deviation.     

Semi-automated versus highly automated driving in critical situations caused by automation failures

The purpose of this study was to examine the effects of vehicle automation and automation failures on driving performance. Previous studies have revealed problems with driving performance in situations with automation failures and attributed this to drivers being out-of-the-loop. It was therefore hypothesized that driving performance is safer with lower than with higher levels of automation. Furthermore, it was hypothesized that driving performance would be affected by the extent of the automation failure. A moving base driving simulator was used. The design contained semi-automated and highly automated driving combined with complete, severe, and moderate deceleration failures. In total the study involved 36 participants. The results indicate that driving performance degrades when the level of automation increases. Furthermore, it is indicated that car drivers are worse at handling complete than partial deceleration failures.     

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks

The accuracy of science depends on the precision of its methods. When fields produce precise measurements, the scientific method can generate remarkable gains in knowledge. When fields produce noisy measurements, however, the scientific method is not guaranteed to work – in fact, noisy measurements are now regarded as a leading cause of the replication crisis in psychology. Scientists should therefore strive to improve the precision of their methods, especially in fields with noisy measurements. Here, we show that automation can reduce measurement error by ∼60% in one domain of developmental psychology: controlled-rearing studies of newborn chicks. Automated studies produce measurements that are 3–4 times more precise than non-automated studies and produce effect sizes that are 3–4 times larger than non-automated studies. Automation also eliminates experimenter bias and allows replications to be performed quickly and easily. We suggest that automation can be a powerful tool for improving measurement precision, producing high powered experiments, and combating the replication crisis.     

Developing human-machine trust: Impacts of prior instruction and automation failure on driver trust in partially automated vehicles

To prompt the use of driving automation in an appropriate and safe manner, system designers require knowledge about the dynamics of driver trust. To enhance this knowledge, this study manipulated prior information of a partial driving automation into two types (detailed and less) and investigated the effects of the information on the development of trust with respect to three trust attributions proposed by Muir (1994): predictability, dependability, and faith. Furthermore, a driving simulator generated two types of automation failures (limitation and malfunction), and at six instances during the study, 56 drivers completed questionnaires about their levels of trust in the automation. Statistical analysis found that trust ratings of automation steadily increased with the experience of simulation regardless of the drivers’ levels of knowledge. Automation failure led to a temporary decrease in trust ratings; however, the trust was rebuilt by a subsequent experience of flawless automation. Results showed that dependability was the most dominant belief of drivers’ trust throughout the whole experiment, regardless of their knowledge level. Interestingly, detailed analysis indicated that trust can be accounted by different attributions depending on the drivers’ circumstances: the subsequent experience of error-free automation after the exposure to automation failure led predictability to be a secondary predictive attribution of drivers’ trust in the detailed group whilst faith was consistently the secondary contributor to shaping trust in the less group throughout the experiment. These findings have implications for system design regarding transparency and for training methods and instruction aimed at improving driving safety in traffic environments with automated vehicles.     

Audiovisual time-to-collision estimation for accelerating vehicles: The acoustic signature of electric vehicles impairs pedestrians' judgments

To avoid collisions, pedestrians intending to cross a road need to accurately estimate the time-to-collision (TTC) of an approaching vehicle. For TTC estimation, auditory information can be considered particularly relevant when the approaching vehicle accelerates. The sound of vehicles with internal combustion engine (ICEVs) provides characteristic auditory information about the acceleration state (increasing rotational speed and engine load). However, for electric vehicles (EVs), the acoustic signature during acceleration is less salient. Although the auditory detection of EVs has been studied extensively, there is no research on potential effects of the altered acoustic signature of EVs on TTC estimation. To close this gap, we compared TTC estimates for ICEVs and for EVs with and without activated acoustic vehicle alerting system (AVAS). We implemented a novel interactive audiovisual virtual-reality system for studying the human perception of approaching vehicles. Using acoustic recordings of real vehicles as source signals, the dynamic spatial sound field corresponding to a vehicle approaching in an urban setting is generated based on physical modeling of the sound propagation between vehicle and pedestrian (listener) and is presented via sound field synthesis (higher-order Ambisonics). In addition to the auditory simulations, the scene was visually presented on a head-mounted display with head tracking. Participants estimated the TTC of vehicles that either approached at a constant speed or accelerated positively. In conditions with constant speed, TTC estimates for EVs with and without AVAS were similar to those for ICEVs. In contrast, for accelerating vehicles, there was a substantial effect of the vehicle type on the TTC estimates. For the EVs, the mean TTC estimates showed a significant overestimation. Thus, subjects on average perceived the time of arrival of the EV at their position as longer than it actually was. The extent of overestimation increased with acceleration and presented TTC. This pattern is similar to a first-order TTC estimation representing a failure to consider the acceleration, which is consistently reported in the literature for visual-only presentations of accelerating objects. In comparison, the overestimation of TTC was largely reduced for the accelerating ICEVs. The AVAS somewhat improved the TTC estimates for the accelerating EVs, but without reaching the same level of accuracy as for the ICEVs. In real traffic scenarios, overestimations of the TTC of approaching vehicles might lead to risky road-crossing decisions. Therefore, our finding that pedestrians are significantly less able to use the acoustic information emitted by accelerating EVs for their TTC judgments, compared to accelerating ICEVs, has important implications for road safety and for the design of AVAS technologies.     

The Simplest Axiom System for Plane Hyperbolic Geometry

We provide a quantifier-free axiom system for plane hyperbolic geometry in a language containing only absolute geometrically meaningful ternary operations (in the sense that they have the same interpretation in Euclidean geometry as well). Each axiom contains at most 4 variables. It is known that there is no axiom system for plane hyperbolic consisting of only prenex 3-variable axioms. Changing one of the axioms, one obtains an axiom system for plane Euclidean geometry, expressed in the same language, all of whose axioms are also at most 4-variable universal sentences. We also provide an axiom system for plane hyperbolic geometry in Tarski's language L _B which might be the simplest possible one in that language.     

On simulating non-normal distributions

Six different algorithms to generate widely different non-normal distributions are reviewed. These algorithms are compared in terms of speed, simplicity and generality of the technique. The advantages and disadvantages of using these algorithms are briefly discussed.The author would like to thank an anonymous referee for his comments and suggestions which lead to the inclusion of the section A Comparative Study.     

A one-boundary drift-diffusion model for time to collision estimation in a simple driving task

ABSTRACT

Driving is a complex everyday task. Every year a huge number of driving accidents around the world causes serious physical and mental injuries and deaths. The correct estimation of the remaining time to reach the other vehicles on the road, known as time to collision (TTC), is an important factor to avoid accidents. In this study, we aimed to use a drift-diffusion model (DDM) to better understand the participants’ estimation of TTC in two driving experiments. Both experiments were the same, except that in one of them participants were asked to finish the experiment as fast as they could, while in the other experiment there was no time constraint. DDM fitted the data from all participants well in both experiments according to the chi-square goodness of fit criterion. Also, results showed that time pressure increases subjects’ estimated TTC, the rate of accumulation of sensory information and the response threshold.     

论中国古代心理治疗方法

中国古代的心理治疗主要包括以认知、行为和情志为操作对象的一系列方法,这些治疗方法设计精巧．疗效迅捷,在治疗中注重个体差异性和治疗的整体性,具有明显的古代中国本土特色。     

Upper bounds for Kruskal's stress

In this paper the relationships between the two formulas for stress proposed by Kruskal in 1964 are studied. It is shown that stress formula one has a system of nontrivial upper bounds. It seems likely that minimization of this loss function will be liable to produce solutions for which this upper bound is small. These are regularly shaped configurations. Even though stress formula two yields less equivocal results, it seems to be expected that minimization of this loss function will tend to produce configurations in which the points are clumped. These results give no clue as to which of the two loss functions is to be preferred.This study has been supported by the Nederlandse Organisatie voor Zuiver-Wetenschappelijk Onderzoek (Netherlands Organization for the Advancement of Pure Research), under grant 56-146.Comments by Willem Heiser and Frank Critichley have been very helpful.The second author presently is employed by the Netherlands Central Bureau of Statistics, Voorburg.     

On defining words, some scenarios and vectors in the 'autobiography' of C. G. Jung

Having first considered recent research into the circumstances surrounding the production and publication of the 'autobiography' of Jung, the author concludes that in spite of its being the work of several authors, it nevertheless constitutes a whole. Taken from whichever angle, they all point to Jung's particular inquiry into the unconscious, as it emerges through Jung's own words. The author goes on to suggest both a lateral and a structural reading of MDR (Memories, Dreams, Reflections) which in turn reveals, on the basis of the several dreams reported, the central 'fantasy' which inspired Jung's research and his oeuvre. Finally, he discusses the idea of the collective or impersonal unconscious and highlights the emphasis Jung places on processes which unfold according to rhythms which are associated with distinct scales, depending on whether they are those of the individual, the clan or the culture.     

Alternate methods and software for calculating interobserver agreement for continuous observation data

Portable electronic data collection devices permit investigators to collect large amounts of observational data in a form ready for computer analysis. These devices are particularly efficient for gathering continuous data on multiple behavior categories. We expect that the increasing availability of these devices will lead to greater use of continuous data collection methods in observational research. This paper addresses the difficulties encountered when calculating traditional interobserver agreement statistics for continuous, multiple-code scoring. Two alternative strategies are described that yield interobserver agreement values based on the exact time of behavior code entries by the primary and secondary observers.Work on this paper was supported in part by NICHD Grants P01HD15051 and R01HD17650 and Office of Special Education and Rehabilitation Services Grant G008302980.     

Parameters, Predictions, and Evidence in Computational Modeling: A Statistical View Informed by ACT-R

Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive theories, encouraging a "model fixed, data variable" paradigm that makes it difficult to interpret model predictions and to account for individual differences. This article proposes a likelihood-based, "data fixed, model variable" paradigm in which models are treated as stochastic processes in experiments with participant-to-participant variation that can be applied to a broad range of mechanistic cognitive architectures. This article discusses the implementation and implications of this view in model validation, with a concrete focus on a simple class of ACT-R models of cognition. This article is not intended as a recipe for broad application of these preliminary, proof-of-concept methods, but as a framework for communication between statisticians searching for interesting problems in the cognitive modeling sphere, and cognitive modelers interested in generalizing from deterministic to stochastic model validation, in the face of random variation in human experimental data.     

略论应用伦理学的对象、任务和方法

应用伦理学以道德与实践的关系为对象。其任务主要有：1．为提高人的道德素质服务;2．为促进社会明发展服务;3．为协调人与自然的关系服务;4．为培育人的理想信念服务。其研究方法有：依托实践,归演理念;一无为主,综合创新;以人为本,德福并举。     

Mimic automata: A novel formal model for mimic computing

In this paper, we aim to establish a mathematical model for mimic computing. To this end, we present a novel automaton called a mimic automaton. First, a one-dimensional cellular automaton is used for expressing some dynamic changes in the structure of a computing unit, a sequential automaton is employed to describe some state transitions, a hierarchical automaton is employed to express the different granularities of some computing units, and a probabilistic automaton is used to depict some random changes of a computing unit. Second, a mimic automaton is obtained by combining the various types of automata mentioned above in a certain logical relationship. Compared with the existing models of mimic computing, the new model portrays the operational semantics for a mimic computing system, and it can directly describe the behaviors of a system. Furthermore, the new model possesses a stronger generality.     

Evidence for dissociable neural mechanisms underlying inference generation in familiar and less-familiar scenarios

In this study, we investigated whether the left and right hemispheres are differentially involved in causal inference generation. Participants read short inference-promoting texts that described either familiar or less-familiar scenarios. After each text, they performed a lexical decision on a letter string (which sometimes constituted an inference-related word) presented directly to the left or right hemisphere. Response-time results indicated that hemisphere of direct presentation interacted with type of inference scenario. When test stimuli were presented directly to the left hemisphere, lexical decisions were facilitated following familiar but not following less-familiar inference scenarios, whereas when test stimuli were presented directly to the right hemisphere, facilitation was observed in both familiar and less-familiar conditions. Thus, inferences may be generated in different ways depending on which of two dissociable neural subsystems underlies the activation of background information.