The factors affecting the performance of the tunnel wall drilling task and their priority.

Clarifying the relationship between the man-machine environment and its impact on the tunnel wall drilling task performance (TWDTP) is crucial for enhancing the task performance. Based on a questionnaire survey, indicators of the man-machine environment that affect the TWDTP were proposed in this study, and exploratory factor analysis and a structural equation model were employed to examine the potential factors influencing the task performance and their degrees of influence. By comparing the discrepancy between the perceived performance and importance, the satisfaction of potential factors was evaluated, and the priority order for optimizing these factors was determined by considering the degree of influence and dissatisfaction. The results of survey data analysis based on actual tunnel drilling operation scenarios indicated that tools had the greatest impact on the TWDTP, followed by the quality of the physical environment, while human factors had the least influence on the task performance. Convenient functional maintenance is the key to improving the TWDTP, along with enhancing the quality of the working environment. Once these main aspects are optimized, it is important to consider additional factors such as availability of spare tools, efficient personnel organization, man-tool matching, and safety and health assurance. This research approach provides significant guidance in understanding the relationships between the man-machine environmental factors affecting the performance of complex engineering tasks and identifying key influencing factors, thus providing essential insights for optimizing the TWDTP.

Effects of a color gradient and emoji in AR-HUD warning interfaces in autonomous vehicles on takeover performance and driver emotions.

OBJECTIVE: This study examined the effects of color gradients and emojis in an augmented reality-head-up display (AR-HUD) warning interface on driver emotions and takeover performance. METHODS: A total of 48 participants were grouped into four different warning interfaces for a simulated self-driving takeover experiment. Two-way analysis of variance and the Kruskal-Wallis test was used to analyze takeover time, mood, task load, and system availability. RESULTS: Takeover efficiency and task load did not significantly differ among the interfaces, but the interfaces with a color gradient and emoji positively affected drivers' emotions. Emojis also positively affected emotional valence, and the color gradient had a high emotional arousal effect. Both the color gradient and the emoji interfaces had an inhibitory effect on negative emotions. The emoji interface was easier to learn, reducing driver learning costs. CONCLUSIONS: These findings offer valuable insights for designing safer and more user-friendly AR-HUD interfaces for self-driving cars.

A Self-Sensing and Self-Powered Wearable System Based on Multi-Source Human Motion Energy Harvesting.

Wearable devices play an indispensable role in modern life, and the human body contains multiple wasted energies available for wearable devices. This study proposes a self-sensing and self-powered wearable system (SS-WS) based on scavenging waist motion energy and knee negative energy. The proposed SS-WS consists of a three-degree-of-freedom triboelectric nanogenerator (TDF-TENG) and a negative energy harvester (NEH). The TDF-TENG is driven by waist motion energy and the generated triboelectric signals are processed by deep learning for recognizing the human motion. The triboelectric signals generated by TDF-TENG can accurately recognize the motion state after processing based on Gate Recurrent Unit deep learning model. With double frequency up-conversion, the NEH recovers knee negative energy generation for powering wearable devices. A model wearing the single energy harvester can generate the power of 27.01 mW when the movement speed is 8 km h-1, and the power density of NEH reaches 0.3 W kg-1 at an external excitation condition of 3 Hz. Experiments and analysis prove that the proposed SS-WS can realize self-sensing and effectively power wearable devices.

Harvesting Inertial Energy and Powering Wearable Devices: A Review.

Amidst the swift progression of microelectronics and Internet of Things technology, wearable devices are gradually gaining ground in the domains of human health monitoring. Recently, human bioenergy harvesting has emerged as a plausible alternative to batteries. This paper delves into harvesting human inertial energy that stimulates inertial masses through human motion and then transmutes the motion of the inertial masses into electrical energy. The inertial energy harvester is better suited for low-frequency and irregular human motion. This review first identifies the sources of human motion excitation that are compatible with inertial energy harvesters and then provides a summary of the operating principles and the comparisons of the commonly used energy conversion mechanisms, including electromagnetic, piezoelectric, and triboelectric transducers. The review thoroughly summarizes the latest advancements in human inertial energy-harvesting technology that are categorized and grouped based on their excitation sources and mechanical modulation methods. In addition, the review outlines the applications of inertial energy harvesters in powering wearable devices, medical health monitoring, and as mobile power sources. Finally, the challenges faced by inertial energy-harvesting technologies are discussed, and the review provides a perspective on the potential developments in the field.

The impact of subway car interior design on passenger evacuation and boarding/alighting efficiency.

This study investigated the impact of subway car interior design on passenger evacuation and boarding/alighting efficiency. The usability of pedestrian agent models was verified through real-life experiments. A seven-factor orthogonal simulation experiment was designed, using key geometric features of the subway car interior as variables. The results of the computer simulation showed that the impact of subway car interior design factors on evacuation and boarding/alighting time was not entirely consistent, with seat layout and door width being the most important factors affecting passenger movement. In the evacuation scenario, only the connectivity of the subway car has no effect on evacuation time, while in the boarding and alighting scenario, seat layout, car type, door width, and foyer width all significantly affect boarding and alighting time. Multivariate regression models were established to predict evacuation and boarding/alighting times through design features, which can explain 86.7% and 58.9% of the time variation, respectively. The research results were used to guide subway car design, and the proposed new scheme demonstrated better performance.

An optimal selection method for exterior design schemes of subway trains based on multi-level gray relational analysis.

To make appropriate decisions in the evaluation phase of the exterior design of subway trains, an optimal selection method was proposed based on multi-level gray relational analysis. The exterior design factors of subway trains were analyzed to construct an index system for design evaluation. The significance of each index was compared through an analytic hierarchy process. The correlation coefficient of each index in the plan was calculated through gray relational analysis to obtain the weighted correlation degree of each design scheme. The optimal selection of the exterior design of Guangzhou Metro Line 6 in China was considered as an example. Four types of subjects were recruited: professional designers, students majoring in design, subway train design experts, and subway passengers in Guangzhou. The weight of each index in the evaluation system was calculated using questionnaire scoring. Virtual simulation software was applied to evaluate the human factors related to each scheme. The indices in each plan were then scored to calculate the correlation coefficient and the overall correlation degree; and finally, the optimal selection was obtained. The results showed that it was practical to evaluate and optimize the exterior design of subway trains based on multi-level gray relational analysis. In the evaluation index system, the weights of technology, human factors, aesthetics, and culture were 0.517, 0.297, 0.099, and 0.087, respectively, which showed that technology had the greatest impact on the system, while human factors, aesthetics, and culture were useful complements. Our results showed that Design Scheme 1 was unsuitable as an optimization scheme due to the high escape window. Meanwhile, Design Scheme 2 was optimal overall, from a technical perspective. Design Scheme 3 was the best in terms of the escape window index (a human factor). Design Schemes 3 and 4 were optimally assessed from aesthetic and cultural perspectives. This study is conducive to the optimization of the exterior design of subway trains, can be used to inform design iteration, and provides a reference for the optimal selection of design schemes for other urban rail trains.

HTA-based modeling study of the process of medical transport tasks in high-speed health trains.

BACKGROUND: High-speed health trains are important tools and guarantees in major accidents, epidemic pandemics, disasters, and warfare health care, and the health trains currently developed for common train platforms have more functional defects. OBJECTIVE: The purpose of this study is to analyze the relationship between the medical transfer system and the medical system, and to obtain a better medical transfer train formation through the established model. METHODS: Based on the case study of medical transport tools, this paper analyzes the components and interrelationships of the medical transport system and the medical system, and then analyzes the medical transport task process of the health train by using the hierarchical task analysis (HTA) method. Combined with the Chinese standard EMU, a medical transport task model of the high-speed health train is established. Through this model, the functional compartment unit of the high-speed health train and the marshaling scheme of the high-speed health train are obtained. RESULTS: The expert system is used to evaluate the scheme. The results show that the train formation scheme formulated by the model in this paper is superior to other train formation schemes in three indicators, meeting the requirements of large medical transfer tasks. CONCLUSION: The results of this study can improve the ability of on-site treatment of patients, and can provide a basis for the research and development of a high-speed health train, which has a certain practical application value.

Chinese handwriting while driving: Effects of handwritten box size on in-vehicle information systems usability and driver distraction.

OBJECTIVE: Handwritten box size (HBS) is an essential Chinese handwriting interface element when interacting with touchscreen-based in-vehicle information systems (IVISs) since it is compactly bound up with driver distraction besides usability issues. Miscellaneous HBSs are commercially available on IVISs, yet the details of how the drivers interact with them in an in-vehicle display situation remain sparsely examined. Therefore, this study set out to investigate the effects of HBS on IVISs usability (task completion time, number of errors, number of protruding strokes, and NASA-TLX, a subjective workload assessment tool) and driver distraction (mean speed, lane position variation, total glance time, number of glances, mean glance time, and number of glances exceeding 1.6 s). Ultimately, the appropriate HBS on IVISs is determined. METHODS: A simulated driving experiment involving thirty drivers was launched. The primary task was lane-keeping with speed ranging from 40 to 60 km/h, and the secondary task was entering a 5-character text by Chinese handwriting input under five different HBS conditions: 25 × 25 mm, 30 × 30 mm, 35 × 35 mm, 40 × 40 mm, and 45 × 45 mm. A battery of one-way repeated measure analyses of variance (r-ANOVA) was used to examine which HBS can maximize IVISs usability and minimize driver distraction with the smallest HBS. RESULTS: Generally, the issues of IVISs usability and driver distraction improved progressively as the HBS increased to a specific size (40 × 40 mm in this study), at which they got to the asymptotes. Specifically, HBS below 40 × 40 mm was associated with longer text input time, more errors and protruding strokes, extended eyes-off-road time, excessive off-road glances, and deteriorative lateral driving performance. Nevertheless, there were no significant differences in mean glance time and longitudinal driving performance. No improvement measures were observed for HBS above 40 × 40 mm, except for a higher perceived workload. CONCLUSIONS: Overall, the appropriate HBS of in-vehicle Chinese handwriting was found to be 40 × 40 mm. Considering that the in-vehicle human-machine interface (HMI) has limited display space and increasing visual complexity, these findings may help develop evidence-based design guidelines for driver-friendly IVISs and prevent distracted-related traffic injuries.

The impact of different AR-HUD virtual warning interfaces on the takeover performance and visual characteristics of autonomous vehicles.

OBJECTIVE: The objective of this study was to determine the different effects of the arrow-pointing augmented reality head-up display (AR-HUD) interface, virtual shadow AR-HUD interface, and non-AR-HUD interface on autonomous vehicle takeover efficiency and driver eye movement characteristics in different driving scenarios. METHODS: Thirty-six participants were selected to carry out a simulated driving experiment, and the eye movement index and takeover time were analyzed. RESULTS: The arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface could effectively reduce the driver's visual distraction, improve the efficiency of obtaining visual information, reduce the number of times the driver's eyes leave the road, and improve the efficiency of the takeover compared with the non-AR-HUD interface, but there was no significant difference in eye movement indexes between the arrow pointing AR-HUD interface and the more eye-catching virtual shadow AR-HUD interface. When specific scenarios were considered, it was found that in the scenario of emergency braking of the vehicle in front, the arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface had more advantages in takeover efficiency than the non-AR-HUD interface. However, in the scenarios of a rear vehicle overtaking the vehicle ahead and non-motor vehicles running red lights, there was no significant difference in takeover efficiency. For the non-motor vehicle invading the line, emergency U-turn of the vehicle in front, and pedestrian crossing scenarios, the virtual shadow AR-HUD interface had the highest takeover efficiency. CONCLUSIONS: These research results can help improve the active safety of autonomous vehicle AR-HUD interfaces.

Impact of experience on visual behavior and driving performance of high-speed train drivers.

This study investigated the impact of experience on the visual behavior and driving performance of high-speed train drivers, and explored the correlation between visual behavior and driving performance. Through a simulated driving task, eye movement data and operating data of novice drivers, trainee drivers, and experienced drivers in the traction stage, normal operation process stage, and braking stage were collected. Variance and linear regression were used to analyze the difference and correlation between indicators. The results show that experience could change the driver's information collection method from long fixation to multi-frequency. Experience also increased the consistency of group operations and reduced the likelihood of hazard occurrences. Therefore, driving performance can be improved by reducing the average fixation duration of information through interface optimization.

Address inputting while driving: a comparison of four alternative text input methods on in-vehicle navigation displays usability and driver distraction.

OBJECTIVE: Efficient and safe address entry is crucial to in-vehicle navigation systems. Although various text input methods (TIMs) are commercially available, to date, the details of the driver's interactions with these TIMs in the vehicle are poorly understood. Therefore, the effect of four alternative TIMs conditions on in-vehicle navigation displays usability and driver distraction were directly compared. For reference, the baseline driving task (distraction-free) was also investigated. METHODS: A city expressway simulator experiment including 25 young drivers was launched. Under each condition, the driving task was lane-keeping with speed ranging between 40 and 60 km/h, and the navigation task was to enter a 14-characters Chinese address name. In the meantime, usability (text entry time, number of errors, and preference) and driver distraction (NASA-TLX, average speed, the standard deviation of lane position, total glance duration, number of glances, average glance duration, and number of glances exceeding 1.6 s) metrics were measured as dependent variables. A sequence of one-way repeated measure analyses of variance (ANOVA) was performed to examine which type of TIMs can maximize in-vehicle navigation displays usability and minimize driver distraction. RESULTS: Generally, lateral driving performance deteriorated with the addition of the address inputting task, and the four alternative TIMs might fall into three levels: Speech is optimal, Qwerty followed, Shape-writing and Handwriting ranked last. Specifically, word-based speech remains performed best on all observed metrics for Chinese address names. There was an insignificant difference in text entry time and total glance duration among Qwerty, Shape-writing, and Handwriting. However, Shape-writing and Handwriting are not suitable for young drivers since the nature of uninterruptible causes excessive errors, more considerable lane position variation, longer average glance duration, and more glances exceeding 1.6 s. CONCLUSIONS: This study provides valuable insights into young drivers' interactions with four alternative TIMs. Importantly, it is beneficial to the automotive user interfaces design of in-vehicle navigation displays and other sub-functions of in-vehicle information systems (IVISs), such as music playback and text messaging, which positively mitigate driver distraction and prevent traffic injuries.

Dynamic is optimal: Effect of three alternative auto-complete on the usability of in-vehicle dialing displays and driver distraction.

OBJECTIVE: Auto-complete (AC) has become ubiquitous on domain-specific systems and is mainly divided into two types (static-AC and dynamic-AC). Specifically, static-AC only presents the possible completions not changing with user input in the suggestion list for users to select. Dynamic-AC constantly filters out inconsistent content with user input and shows the possible completions at the top of the suggestion list. However, the details of the driver's interactions with AC in the vehicle are poorly understood. Therefore, we investigated the effect of three alternative AC (non-AC, static-AC, and dynamic-AC) on the usability of in-vehicle dialing displays and driver distraction. As a reference, the baseline task (only driving) was also surveyed in each AC condition. METHODS: A simulated driving experiment consisting of 24 participants was conducted. The primary task was a lane-keeping task with speed ranging between 60 and 120 km/h over the stretch. The secondary task was dialing an 11-digit phone number. Usability metrics (task completion time and number of errors) and driver distraction metrics (NASA-reduced task load index (NASA-RTLX), mean speed, lateral position variation, total glance time, number of glances, mean glance time, and number of glances over 1.6 s) in each condition were measured. A series of one-way repeated measure analyses of variance was used to examine whether and which type of AC can maximize the usability of in-vehicle dialing displays and minimize driver distraction. RESULTS: Generally, the AC-based in-vehicle dialing display gains a more positive effect. Specifically, we observed that among the three alternative AC conditions, dynamic-AC performed optimally on usability metrics similar to previous studies and various driver distraction metrics, notwithstanding it is still not up to the level of the baseline condition. However, static-AC did not exhibit the advantages described in previous studies except for fewer errors and NASA-RTLX owing to the possibility of position bias and boundary effect. CONCLUSIONS: This study provides valuable insights into drivers' interactions with AC-based in-vehicle dialing displays and broadened its applications in safety-critical situations. More importantly, it informs the design of a more effective in-vehicle system, which positively contributes to mitigating driver distraction and preventing traffic accidents.

Influence of Multi-Modal Warning Interface on Takeover Efficiency of Autonomous High-Speed Train.

As a large-scale public transport mode, the driving safety of high-speed rail has a profound impact on public health. In this study, we determined the most efficient multi-modal warning interface for automatic driving of a high-speed train and put forward suggestions for optimization and improvement. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal-Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic-text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory-visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public.

A method identifying key optimisation points for aircraft seat comfort.

Seating is the overriding factor influencing aircraft cabin comfort. To efficiently enhance seat comfort, this paper proposes a method to identify key optimisation points for seat comfort. Seat discomfort indicators are recognised based on a comparison of perceived performance with expectation. Confirmatory factor analysis is used to explore the latent variables of discomfort indicators, and a structural model was used to analyse correlations between latent variables. Finally, the most important latent variable influencing seat comfort was clarified. Analysis results of survey data from narrow-body aircraft show that seat discomfort indicators centre on the physical performance of the seat and include four latent variables: support performance, personal space, contact surface features, and safety and stability. Support performance determines body posture while travelling and is the overriding latent variable influencing seat comfort. This research establishes aircraft seat discomfort indicators, latent variables formed through the mutual linkage of discomfort indicators, and the structural relations between latent variables. The results can assist in the formulation of comfort optimisation procedures for aircraft seats. Practitioner summary: A method identifying the key points of aircraft seat comfort optimisation was proposed, which includes three steps: recognising discomfort indicators, exploring the relationship between discomfort indicators, and confirming the most important variable influencing seat comfort. Results provide guidance for aircraft seat optimisation. Abbreviations: SEM: structural equation modelling; EFA: exploratory factor analysis; CFA: confirmatory factor analysis; PA-OV: path analysis with observed variables; CR: construct reliability; AVE: average variance extracted; CMIN: likelihood-ratio chi-square; DF: degrees of freedom; GFI: goodness-of -fit index; AGFI: adjusted goodness-of -fit index; RMSEA: root mean square error of approximation; NNFI: non-normed fit index; RFI: relative fit index; CFI: comparative fit index; CN: critical N.