儿童运动视觉表象操作水平的发展及影响因素

采用计算机软件控制实验,以暴露运动一段行程后进入遮蔽的光点为刺激物,光点以三种不同运动速度、三种不同运动行距组合呈现,要求儿童判断光点到达目标位置时按键反应。结果表明：5—19岁儿童运动视觉表象操作水平的发展存在5一8岁、11—14岁两个加速期;客体运动速度对运动视觉表象操作绩效有显著影响,5、8、11岁组快速较中速下．5．8岁组中速较慢速下操作准确性均有显著降低;客体运动行距对运动视觉表象操作绩效也有显著的影响．5、8、11岁组右目标位置下较中目标位置下操作准确性显著降低;性别对运动视觉表象操作水平无显著影响。     

与立体视觉相关的视诱发电位研究

在微机上编制能产生动态随机点立体图（ＤＲＤＳ）,亮暗类棋盘格和随机点背景三种图形刺激的软件．记录了３４例正常人在这三种刺激下的ＶＢＰ．其结果为：（１）ＤＲＤＳ刺激下的ＶＥＰＮ１波潜伏期为２６５±２５ｍｓ,基波能量占总交流能量的６３．２±１８．９％．（２）亮暗类棋盘格刺激下的ＶＥＰＮ１波的潜伏期为１９０±２２ｍｓ,基波能量占总交流能量的３９．２±１９．６％．（３）随机点背景刺激下的ＶＥＰ波则为一些杂乱的小波．结果提示：动态ＲＤＳ刺激下的ＶＥＰ除在潜伏期方面具有特异性外,并在谐波的能量分布上也具有特异性,且客观性更强．根据这些特征有助于对立体视觉功能进行客观性评价．     

Random error in additive decompositions of multiattribute utility

Decomposition is a common strategy for dealing with the complexity of multiattribute decision problems. A cognitively demanding task is broken down into tasks requiring simpler, perhaps easier, judgments which can then be aggregated. But individual judgments can be inconsistent in systematic or random fashion and when aggregated there is the possibility of propagation of this inconsistency. In this paper inconsistency in the form of random error is investigated in the context of additive decomposition of multiattribute utility. The process of aggregation of random error is studied and a comparison made with random error in holistic estimates of multiattribute utility. Conditions under which decomposition improves the consistency of the multiattribute utility estimate are presented and discussed.     

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.     

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.     

Operant-contingency-based preparation of children for functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is used to study brain function during behavioral tasks. The participation of pediatric subjects is problematic because reliable task performance and control of head movement are simultaneously required. Differential reinforcement decreased head motion and improved vigilance task performance in 4 children (2 with behavioral disorders) undergoing simulated fMRI scans. Results show that behavior analysis techniques can improve child cooperation during fMRI procedures.     

Dorsal stream deficits suggest hidden dyslexia among deaf poor readers: correlated evidence from reduced perceptual speed and elevated coherent motion detection thresholds

Prelingual deafness and developmental dyslexia have confounding developmental effects on reading acquisition. Therefore, standard reading assessment methods for diagnosing dyslexia in hearing people are ineffective for use with deaf people. Recently, Samar, Parasnis, and Berent (2002) reported visual evoked potential evidence that deaf poor readers, compared to deaf good readers, have dorsal stream visual system deficits like those previously found for hearing dyslexics. Here, we report new psychometric and psychophysical evidence that deficits in dorsal stream function, likely involving extrastriate area MT, are associated with relatively poor reading comprehension in deaf adults. Poorer reading comprehension within a group of 23 prelingually deaf adults was associated with lower scores on the Symbol Digit Modality Test, a perceptual speed test commonly used to help identify dyslexia in hearing people. Furthermore, coherent dot motion detection thresholds, which reflect the functional status of area MT, correlated negatively with reading scores in each visual quadrant. Elevated motion thresholds for deaf poor readers were not due to general cognitive differences in IQ but were specifically correlated with poor perceptual speed. With IQ controlled, a highly reliable right visual field advantage for coherent motion detection was found. Additional analyses suggested that the functional status of dorsal stream motion detection mechanisms in deaf people is related to reading comprehension, but the direction and strength of lateralization of those mechanisms is independent of reading comprehension. Our results generally imply that dyslexia is a hidden contributor to relatively poor reading skill within the deaf population and that assessment of dorsal stream function may provide a diagnostic biological marker for dyslexia in deaf people.     

Representational momentum in older adults

Humans have a tendency to perceive motion even in static images that simply “imply” movement. This tendency is so strong that our memory for actions depicted in static images is distorted in the direction of implied motion - a phenomenon known as representational momentum (RM). In the present study, we created an RM display depicting a pattern of implied (clockwise) rotation of a rectangle. Young adults viewers’ memory of the final position of the test rectangle was biased in the direction of continuing rotation, but older adults did not show a similar memory bias. We discuss several possible explanations for this group difference, but argue that the failure of older adults to shown an RM effect most likely reflects age-related changes in areas of the brain involved in processing real and implied motion.     

Two-step communication for the interaction between automated vehicles and pedestrians

An important challenge of automated vehicles (AV) will be the cooperative interaction with surrounding road users such as pedestrians. One solution to compensate for the missing driver-pedestrian interaction might be explicit communication via external human machine interfaces (eHMIs). Additionally, implicit communication such as a vehicle pitch motion might support AVs when interacting with pedestrians. While previous work explored various explicit and implicit communication cues, these concepts communicated the intention of the AV at one single time point. Currently, empirical findings on two-step communication lack so far. In this study, we empirically test the effect of a two-step AV communication that uses an implicit cue at a long distance and subsequently provides an implicit or explicit cues at a short distance. We compared its efficiency to single-step communication concepts providing implicit or explicit cues at the shorter distance only. To explore whether the right communication cue is used at the right distance, we analyzed pedestrians’ fixations while approaching an AV using an eye tracking device.We conducted a virtual reality study (N = 30) with AV communication concept that provided an active pitch motion or an eHMI and compared them with a two-step AV communication concept that provided an additional active pitch motion at a long distance when approaching the pedestrian. Furthermore, we recorded pedestrians’ fixation behavior while the AV approached.Consistently to previous work, single-step AV communication showed a beneficial effect on crossing behavior. Pedestrians initiated their crossing earlier while approaching an AV with an active pitch motion or an eHMI compared to the baseline condition. While active pitch motion reduced subjective safety feeling, eHMI increased it. However, the two-step communication concept did not further improve pedestrians’ crossing initiation times and their safety feeling. The pattern of fixation behavior differed as a function of AV distance. When the approaching AV was far away, pedestrians exclusively looked at the environment. During the approach, pedestrians gradually fixated the bumper and the hood and only then the windshield of the AV. Hence, it seems to be useful to present an AV intent communication at a certain distance from the pedestrian. These findings posit the importance of considering pedestrians’ fixation behavior when developing communication concepts between AVs and pedestrians.