Classification of driving workload affected by highway alignment conditions based on classification and regression tree algorithm

Objective: Guaranteeing a safe and comfortable driving workload can contribute to reducing traffic injuries. In order to provide safe and comfortable threshold values, this study attempted to classify driving workload from the aspects of human factors mainly affected by highway geometric conditions and to determine the thresholds of different workload classifications. This article stated a hypothesis that the values of driver workload change within a certain range.

Methods: Driving workload scales were stated based on a comprehensive literature review. Through comparative analysis of different psychophysiological measures, heart rate variability (HRV) was chosen as the representative measure for quantifying driving workload by field experiments. Seventy-two participants (36 car drivers and 36 large truck drivers) and 6 highways with different geometric designs were selected to conduct field experiments. A wearable wireless dynamic multiparameter physiological detector (KF-2) was employed to detect physiological data that were simultaneously correlated to the speed changes recorded by a Global Positioning System (GPS) (testing time, driving speeds, running track, and distance). Through performing statistical analyses, including the distribution of HRV during the flat, straight segments and P-P plots of modified HRV, a driving workload calculation model was proposed. Integrating driving workload scales with values, the threshold of each scale of driving workload was determined by classification and regression tree (CART) algorithms.

Results: The driving workload calculation model was suitable for driving speeds in the range of 40 to 120 km/h. The experimental data of 72 participants revealed that driving workload had a significant effect on modified HRV, revealing a change in driving speed. When the driving speed was between 100 and 120 km/h, drivers showed an apparent increase in the corresponding modified HRV. The threshold value of the normal driving workload K was between ?0.0011 and 0.056 for a car driver and between ?0.00086 and 0.067 for a truck driver.

Conclusion: Heart rate variability was a direct and effective index for measuring driving workload despite being affected by multiple highway alignment elements. The driving workload model and the thresholds of driving workload classifications can be used to evaluate the quality of highway geometric design. A higher quality of highway geometric design could keep driving workload within a safer and more comfortable range. This study provided insight into reducing traffic injuries from the perspective of disciplinary integration of highway engineering and human factor engineering.     

无人机操作主观心理负荷测评与心率数据比较

为探究在无人机实操试验的心理负荷测量中主观量表与心率测评工具的性能,招募14名从未接触过无人机操作的被试者,在参加飞行操作培训后进行4种不同难度的无人机飞行操作情景试验;使用Polar V800监测被试者试验过程中的心率变化,并在试验结束后采用NASA-TLX,MCH,SWAT 3种主观量表进行评分,以比较飞行难度间各...     

A theoretical and methodological framework for studying and modelling drivers’ mental representations

This article provides a synthetic overview of the research programme carried out at INRETS-LESCOT over the last 10 years, in view to studying and modelling the mental representations of car drivers. Theoretically, this research is in line with two complementary scientific traditions: Human Information Processing theories on the one hand, and theories of Operative Activity on the other. As discussed in Section 1 of the article, attention is given to the functional representations of drivers, constructed “by” and “for” the action, such as they are implemented in a driving situation, and taking into account both implicit and explicit dimensions. This aim directly impacts on the methodological approach implemented, in so far as it entails defining an “experimental continuum” ranging from naturalistic observations of the driving activity (on the open road), to setting up more controlled experimental protocols in order to permit in-depth, systematic and reproducible scientific investigations of drivers’ cognition. Section 2 of the article presents a synthetic view of these methods, while Section 3 presents several significant results obtained with them. Lastly, the final part of the article focuses on the computational formalism defined at INRETS-LESCOT (i.e. the driving schemas) designed to model driver knowledge and mental representations, and developed in a COgnitive Simulation MOdel of the DRIVEr called COSMODRIVE.     

Predicting work performance in nuclear power plants

Diagnosis and monitoring are the major tasks of an operator in main control room of nuclear power plants (NPPs). The operator’s mental workload influences his/her performance, and furthermore, affects the system safety and operations. This study investigated the operator’s mental workload and work performance of the NPP in Taiwan. An experiment including primary and secondary tasks was designed to simulate the reactor shutdown procedure of the fourth nuclear power plant (FNPP). The performance of the secondary tasks (error rate), subjective mental workload (NASA Task Load Index, NASA-TLX) as well as seven physiological indices were assessed and measured. The group method of data handling (GMDH) was applied to integrate these physiological indices to develop a work performance predictive model. The validity of the proposed model is very well with R² = 0.84 and its prediction capability is high (95% confidence interval). The proposed model is expected to provide control room operators a reference value of their work performance by giving physiological indices. Besides NPPs, the proposed model can be applied to many other fields, e.g. aviation, air transportation control, driving and radar vigilance, etc.     

Older driver training programs: A systematic review of evidence aimed at improving behind-the-wheel performance

IntroductionAge- and health-related changes, alongside declines in driving confidence and on-road exposure, have been implicated in crashes involving older drivers. Interventions aimed at improving behind-the-wheel behavior are diverse and their associated impact remains unclear. This systematic review examined evidence on older driver training with respect to (1) road safety knowledge; (2) self-perceived changes in driving abilities; and (3) behind-the-wheel performance. Method Nine databases were searched for English-language articles describing randomized controlled trials (RCTs) and non-RCTs of driver training interventions aimed at those aged 55+ who did not have medical or other impairments that precluded licensure. Quality appraisals were conducted using Cochrane’s Risk of Bias Tool (RoB) and Risk Of Bias In Non-randomized Studies – of Interventions tool (ROBINS – I). [PROSPERO; registration no. CRD42018087366]. Results Twenty-five RCTs and eight non-RCTs met the inclusion criteria. Interventions varied in their design and delivery where classroom-based education, or a combination of classroom-based education with on-road feedback, improved road safety knowledge. Training tailored to individual participants was found to improve self-perceived and behind-the-wheel outcomes, including crashes. Conclusions Interventions comprised of tailored training can improve knowledge of road safety, changes to self-perception of driving abilities, and improved behind-the-wheel performance of older drivers. Future research should compare modes of training delivery for this driver population to determine the optimal combinations of off- and/or on-road training. Practical applications Training programs aimed at older drivers should be supported by theory and research evidence. By conducting comparative trials with a sufficient sample size alongside well-defined outcomes that are designed in accordance with reporting guidelines, the most effective approaches for training older drivers will be identified.     

Assessing the safety criticality of driver behavior toward cyclists at intersections

Abstract

Objective: Detailed analyses of car-to-cyclist accidents show that drivers intending to turn right at T-junctions collide more often with cyclists crossing from the right side on the bicycle lane than drivers intending to turn left. This fact has led to numerous studies examining the behavior of drivers turning left and right. However, the most essential question still has not been sufficiently answered: is the behavior of drivers intending to turn right generally more safety critical than the behavior of those intending to turn left? The purpose of this article is to provide a method that allows to determine whether a driver’s behavior toward cyclists can retrospectively be assessed as critical or non-critical.

Methods: Several theoretical considerations enriched by findings of experimental studies were employed to devise a multi-measure method. This method was applied to a dataset containing real-world approaching behavior of 48 drivers turning right and left at four T-junctions with different sight obstructions. For each driver a behavior-specific criticality was defined based on both, their driving and gaze behavior. Moreover, based on the behavior-specific criticality of each driver, the required field of view to see a cyclist from the right was defined and was set into relation with the available field of view of the T-junction.

Results: The results show that only a small portion of the drivers within the dataset would have posed an actual risk to cyclists crossing from the right side. Those situations with a higher safety criticality did not only arise when drivers intended to turn right, but also left.

Conclusion: Therefore, the analysis can only provide an explanation for the higher proportion of accidents between drivers turning right and cyclists crossing from the right side in certain situations. Further research, for example analyses of exposure data regarding the frequency of turning manoeuvers at T-junctions, is needed in order to explain the higher proportion of accidents between drivers turning right and cyclists crossing from the right side.     

Ergonomics intervention on an alternative design of a spinal board

Nurses are often obliged to work in a 12-hr shift work system. We have decided to check whether such a working system constitutes an excessive load for nurses. On the basis of a questionnaire survey among nurses working in an 8-hr daytime shift system (169 nurses) and in a 12-hr shift (536 nurses), the amount of physical workload, work stress, and after-work activities were compared. Data analysis has shown that a 12-hr shift system is characterized by less significant physical workload but greater mental load. The nurses working in a 2-shift system were more tired after work, but they could spend more time on leisure activities and do housework. The data suggest that there are no significant contraindications for nurses to work in a 2-shift system.     

The safety implications of vehicle seat adjustments

INTRODUCTION: The goal of this study was to gather information on the preferred front seat position of vehicle occupants and to determine the impact of variation in seat position on safety during crashes. METHOD: The study evaluated the relationship between seat position and occupant size using the chi-square test and compared the risk of severe injury for small females and large males with regard to forward and rearward seat position using logistic regression. RESULTS: While smaller drivers sat closer to the steering wheel than larger drivers, front passengers of all sizes used similar seat positions. Additionally, the risk of injury was higher for small, unbelted females in rearward seat positions and large males (belted and unbelted) in forward seat positions. CONCLUSIONS: Occupants who adjust their seats to positions that are not consistent with required federal tests are at a greater risk for severe injury in a crash.     

COMPARING THE IMPAIRMENT PROFILES OF OLDER DRIVERS AND NON-DRIVERS: TOWARD THE DEVELOPMENT OF A FITNESS-TO-DRIVE MODEL

The purpose of this research effort was to compare older driver and non-driver functional impairment profiles across some 60 assessment metrics in an initial effort to contribute to the development of fitness-to-drive assessment models. Of the metrics evaluated, 21 showed statistically significant differences, almost all favoring the drivers. Also, it was shown that a logistic regression model comprised of five of the assessment scores could completely and accurately separate the two groups. The results of this study imply that older drivers are far less functionally impaired than non-drivers of similar ages, and that a parsimonious model can accurately assign individuals to either group. With such models, any driver classified or diagnosed as a non-driver would be a strong candidate for further investigation and intervention.     

Issues with using police citations to assign responsibility in quasi-induced exposure

Crash fault determination is one of the most critical issues in applications of quasi-induced exposure. Traditionally, the driver citation issued by the investigating police officer is the primary source to assign responsibility for motor vehicle crashes. Such citations are based on the “evidence” or observation of a moving violation (such as engaged hazardous actions) in combination with non-moving violations (such as suspended driver license) prior to the crash. The objective here is to identify the contributing factors that may lead to driver citations in two-vehicle crashes in addition to the hazardous action. Multivariate binary logistic regression modeling is employed to explore the behavior of the investigating police officer in terms of issuing citation at the crash scene. A series of explanatory parameters including roadway characteristics, environmental factors, and driver and vehicle attributes is assessed. The results show that whether the crash type was a hit-and-run, alcohol and illegal drug use, driver gender, driver age, and injury severity all appear to have significant impacts on the investigating officer’s decision-making. Specific examples are given to demonstrate how two factors hit-and-run and drinking status can skew the exposure estimates in the context of quasi-induced exposure. The findings will help to serve as a basis to select appropriate parameters in assigning crash responsibility in quasi-induced exposure applications; and we make recommendations to modify existing crash database for better safety research in the future.