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学者姓名：杨艳群
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As the primary setting for students' daily life and learning, university campuses are facing a growing concern about the impact of increased stress on students' emotional well-being. The sound environment plays a critical role in affecting students' mental health, learning efficiency, and overall well-being. However, research on the influence of campus soundscapes on students' emotions is limited, and the mechanisms behind these effects remain to be explored. This study, using the Qishan Campus of Fuzhou University as a case, investigates the impact of campus soundscapes on students' emotional perception and restorative effects. Four typical functional areas (academic zone (ACZ), residential zone (RDZ), recreational zone (RCZ), and administrative zone (ADZ)) were selected to analyze the effects of natural and artificial sounds on students' emotions and physiological states. Based on EEG, eye tracking, sound level measurements, and questionnaire surveys, a one-way repeated measures ANOVA was used to assess students' emotional arousal, valence, and physiological restoration under different soundscape conditions. The results showed that natural sounds, such as the sound of wind-blown leaves and flowing water, significantly improved students' emotions and restorative effects, while artificial noises like construction sounds and traffic noise had negative impacts. Additionally, subjective perceptions of soundscape restoration were positively correlated with arousal, valence, and acoustic comfort, and negatively correlated with gaze frequency and pupil size. The findings provide a theoretical foundation for optimizing campus soundscape design and highlight the importance of natural sounds in enhancing students' mental health and academic environment.
Keyword ：
campus landscape campus landscape emotional perception emotional perception perceptual measure perceptual measure restorative environment restorative environment soundscape soundscape
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| GB/T 7714 | Liang, Qing , Lin, Shucan , Wang, Linwei et al. The Impact of Campus Soundscape on Enhancing Student Emotional Well-Being: A Case Study of Fuzhou University [J]. | BUILDINGS , 2025 , 15 (1) . |
| MLA | Liang, Qing et al. "The Impact of Campus Soundscape on Enhancing Student Emotional Well-Being: A Case Study of Fuzhou University" . | BUILDINGS 15 . 1 (2025) . |
| APA | Liang, Qing , Lin, Shucan , Wang, Linwei , Yang, Fanghuan , Yang, Yanqun . The Impact of Campus Soundscape on Enhancing Student Emotional Well-Being: A Case Study of Fuzhou University . | BUILDINGS , 2025 , 15 (1) . |
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With the rapid increase in the number of two-wheeled electric vehicles, the number of accidents related to them has also greatly increased. However, despite facing a huge threat from accidents, the helmet, an efficient and legally required protection for riders, is not popular with Chinese two-wheeled electric vehicles riders. To study the factors affecting helmet use for these riders, this paper conducted an observational study to collect helmet use data for 16,207 two-wheeled electric vehicle riders in Fuzhou, China. With these data, this paper built a multivariate logistic regression model to study the main effects of various factors on helmet use, and analyze the interaction effects of these factors. Results showed that, on the one hand, area, weather, temperature, controller, separated non-motor-vehicle lanes, time, rider's age, and type of vehicle had significant effects on helmet use and the interaction between these factors is significant, especially the interaction between weather, temperature and other factors. On the other hand, level of service, gender and whether the riders are food delivery workers have no significant impact on helmet use, but show significant interaction effects with other factors.
Keyword ：
helmet use helmet use multivariate logistic regression model multivariate logistic regression model observational study observational study two-wheeled electric vehicles riders two-wheeled electric vehicles riders
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| GB/T 7714 | Lin, Wenhan , Li, Congying , Zheng, Weibin et al. Riding Risk: Factors Shaping Helmet Use Among Two-Wheeled Electric Vehicle Riders in Fuzhou, China [J]. | SYSTEMS , 2025 , 13 (3) . |
| MLA | Lin, Wenhan et al. "Riding Risk: Factors Shaping Helmet Use Among Two-Wheeled Electric Vehicle Riders in Fuzhou, China" . | SYSTEMS 13 . 3 (2025) . |
| APA | Lin, Wenhan , Li, Congying , Zheng, Weibin , Wang, Linwei , Yang, Yanqun . Riding Risk: Factors Shaping Helmet Use Among Two-Wheeled Electric Vehicle Riders in Fuzhou, China . | SYSTEMS , 2025 , 13 (3) . |
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The entrance zones of highway tunnels present a visually complex environment, often requiring multiple traffic signs to ensure driving safety. However, excessive information or improperly positioned traffic signs may cause cognitive overload, hinder their ability to adapt to changing driving conditions and compromise traffic safety. This study aims to assess the effect of traffic signs information supply speed (TSISS), which considers factors such as traffic sign information (TSI), combined installation and spacing of traffic signs, and speed limits on the road, on driving performance and CL. The study collected four types of performance data: eye movement, electroencephalogram (EEG), driving behavior, and subjective cognitive load (SCL). A driving simulator experiment used six TSISSs at the highway tunnel entrance zone: 0.333, 0.400, 0.500, 0.600, 0.667, and 0.833 items/s. An "item" is an independent directive or command of traffic signs. The results showed that as the TSISS increased, pupil area, scan rate, theta wave absolute power, longitudinal acceleration, steering wheel angle, and SCL significantly increased. In contrast, blink frequency, alpha wave absolute power, and vehicle longitudinal speed decreased. When the TSISS did not exceed 0.600 items/s, the efficiency values calculated by the data envelopment analysis model were high (more than 0.950). However, when the TSISS exceeded 0.600 items/s, the efficiency significantly decreased (below 0.850). Based on these findings, 0.600 items/s is recommended as the optimal threshold for TSISS at highway tunnel entrances. These findings can help evaluate the rationality and effectiveness of traffic sign placement at tunnel entrances, providing essential theoretical bases and practical guidelines for optimizing the overall design of highway traffic signs.
Keyword ：
Cognitive Load Cognitive Load Data Envelopment Analysis Data Envelopment Analysis Driving Simulator Driving Simulator Traffic Signs Information Supply Speed Traffic Signs Information Supply Speed Tunnel Entrance Zone Tunnel Entrance Zone
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| GB/T 7714 | Yang, Yanqun , Wu, Xinli , Yin, Danni et al. Effect of Traffic Sign's Information Supply Speed on Driver Performance at Tunnel Entrances [J]. | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2025 , 111 : 217-237 . |
| MLA | Yang, Yanqun et al. "Effect of Traffic Sign's Information Supply Speed on Driver Performance at Tunnel Entrances" . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR 111 (2025) : 217-237 . |
| APA | Yang, Yanqun , Wu, Xinli , Yin, Danni , Easa, Said M. , Zheng, Xinyi . Effect of Traffic Sign's Information Supply Speed on Driver Performance at Tunnel Entrances . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2025 , 111 , 217-237 . |
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With the rapid development of intelligent transportation systems, voice assistants are increasingly integrated into driving environments, providing an effective means to mitigate the risks of fatigued driving. This study explored drivers' interaction preferences with voice assistants under different fatigue states and proposed a fatigue-state-based dialogue-awakening mechanism. Using Grounded Theory and the Stimulus-Organism-Response (SOR) framework, in-depth interviews were conducted with 25 drivers from diverse occupational backgrounds. To validate the qualitative findings, a driving simulation experiment was carried out to examine the effects of different voice interaction styles on driver fatigue arousal across various fatigue levels. Results indicated that heavily fatigued drivers preferred highly stimulating and interactive voice communication; mildly fatigued drivers tended toward gentle and socially supportive dialogue; while drivers in a non-fatigued state preferred minimal voice interference, activating voice assistance only when necessary. Significant occupational differences were also observed: long-haul truck drivers emphasized practicality and safety in voice assistants, taxi drivers favored voice interactions combining navigation and social content, and private car owners preferred personalized and emotional support. This study enriches the theoretical understanding of fatigue-sensitive voice interactions and provides practical guidance for the adaptive design of intelligent voice assistants, promoting their application in driving safety.
Keyword ：
dialogue wake-up mechanism dialogue wake-up mechanism driving simulation experiment driving simulation experiment fatigued driving fatigued driving Grounded Theory Grounded Theory SOR theory SOR theory voice assistant voice assistant
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| GB/T 7714 | Zhou, Chenyi , Wang, Linwei , Yang, Yanqun . Dialogue at the Edge of Fatigue: Personalized Voice Assistant Strategies in Intelligent Driving Systems [J]. | APPLIED SCIENCES-BASEL , 2025 , 15 (12) . |
| MLA | Zhou, Chenyi et al. "Dialogue at the Edge of Fatigue: Personalized Voice Assistant Strategies in Intelligent Driving Systems" . | APPLIED SCIENCES-BASEL 15 . 12 (2025) . |
| APA | Zhou, Chenyi , Wang, Linwei , Yang, Yanqun . Dialogue at the Edge of Fatigue: Personalized Voice Assistant Strategies in Intelligent Driving Systems . | APPLIED SCIENCES-BASEL , 2025 , 15 (12) . |
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As aging urban expressways become more pronounced, maintenance and construction work on these roadways is increasingly necessary. Some lanes may need to be closed during maintenance and construction, decreasing driving safety and comfort in the work zone. This situation often leads to traffic congestion and a higher risk of traffic accidents. Notably, 80% of work zone traffic accidents occur in the warning and upstream transition areas (or simply warning and transition areas). Therefore, it is crucial to appropriately determine the lengths of these areas to enhance both safety and comfort for drivers. In this study, we examined three different warning lengths (1800 m, 2000 m, and 2200 m) and three transition lengths (120 m, 140 m, and 160 m) using the entropy weighting method to create nine simulation scenarios on a two-way, six-lane urban expressway. We selected various metrics for driving safety and comfort, including drivers’ eye movement, electroencephalogram, and driving behavior indicators. A total of 45 participants (mean age = 23.9 years, standard deviation = 1.8) were recruited for the driving simulation experiment, and each participant completed all 9 simulation scenarios. After eliminating 5 invalid datasets, we obtained valid data from 40 participants. We employed a combination of the analytic network process and entropy weighting method to calculate the comprehensive weights of the eight evaluation indicators. Additionally, we introduced the fuzzy theory, utilizing a trapezoidal membership function to evaluate the membership matrix values of the indicators and the comprehensive evaluation grade eigenvalues. The ranking of the experimental scenarios was determined using these eigenvalues. The results indicated that more extended warning lengths correlated with increased safety and comfort. Specifically, the best driver safety and comfort levels were observed in Scenario I, which featured a 2200 m warning length × 160 m transition length. However, the difference in safety and comfort across different transition lengths diminished as the warning length increased. Therefore, when road space is limited, a thoughtful combination of reasonable lengths can still provide high driving safety and comfort. © 2025 by the authors.
Keyword ：
Accident prevention Accident prevention Automobile drivers Automobile drivers Behavioral research Behavioral research Eigenvalues and eigenfunctions Eigenvalues and eigenfunctions Entropy Entropy Function evaluation Function evaluation Highway accidents Highway accidents Highway traffic control Highway traffic control Membership functions Membership functions Motor transportation Motor transportation Traffic congestion Traffic congestion
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| GB/T 7714 | Hu, Aixiu , Huang, Ruiyun , Yang, Yanqun et al. Length Requirements for Urban Expressway Work Zones’ Warning and Transition Areas Based on Driving Safety and Comfort [J]. | Systems , 2025 , 13 (7) . |
| MLA | Hu, Aixiu et al. "Length Requirements for Urban Expressway Work Zones’ Warning and Transition Areas Based on Driving Safety and Comfort" . | Systems 13 . 7 (2025) . |
| APA | Hu, Aixiu , Huang, Ruiyun , Yang, Yanqun , El-Dimeery, Ibrahim , Easa, Said M. . Length Requirements for Urban Expressway Work Zones’ Warning and Transition Areas Based on Driving Safety and Comfort . | Systems , 2025 , 13 (7) . |
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The tunnel construction environment is complex, and workers' cognitive load directly affects safety and efficiency, making a dynamic assessment urgently needed. This study aims to explore the cognitive load of tunnel construction workers under different working environments using EEG technology. In the experimental design, subjects adapted to the virtual reality (VR) environment and received instructions before wearing a wireless EEG system and VR equipment to begin the formal experiment. Each subject underwent four rounds of experiments, corresponding to four different scenarios: control, night shift, noise, and confined space. Each round included three tasks of low, medium, and high difficulty. Analysis of EEG data showed that tunnel construction tasks in different environments significantly affected cognitive load, especially during night shifts and in confined spaces, with cognitive load increasing significantly with task difficulty. The results provide a theoretical basis for optimizing the management of tunnel construction environments and task design.
Keyword ：
cognitive load cognitive load EEG EEG tunnel construction tunnel construction VR VR
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| GB/T 7714 | Guo, Zongyong , Xia, Chengming , Tao, Huadi et al. Research on Cognitive Load of Tunnel Construction Workers in Different Environments Based on EEG [J]. | BUILDINGS , 2025 , 15 (16) . |
| MLA | Guo, Zongyong et al. "Research on Cognitive Load of Tunnel Construction Workers in Different Environments Based on EEG" . | BUILDINGS 15 . 16 (2025) . |
| APA | Guo, Zongyong , Xia, Chengming , Tao, Huadi , Huang, Shoujie , Yang, Yanqun . Research on Cognitive Load of Tunnel Construction Workers in Different Environments Based on EEG . | BUILDINGS , 2025 , 15 (16) . |
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为减少弯道段交通事故,对山区公路视线诱导设施综合效用进行研究.在弯道段单独或组合设置护栏、轮廓标、线形诱导标3类视线诱导设施,并基于驾驶模拟器、眼动仪和脑电仪获取眼动、脑电及驾驶行为数据,分析不同设置方案下驾驶人的行为特性.基于超效率BCC-DEA模型,构建山区公路弯道视线诱导设施有效性评价体系,对不同设置方案的综合效果进行评价.结果表明:视线诱导设施组合设置对驾驶行为的影响比单独设置效果更好,其中采用“线形诱导标+轮廓标”设置效果最优;视线诱导设施设置数量超过2个时会降低警示与诱导效果;指标敏感性分析表明,速度和横向位移指标分别是单独与组合设置时影响安全过弯的关键因素.
Keyword ：
山区公路弯道 山区公路弯道 数据包络分析 数据包络分析 视线诱导设施 视线诱导设施 超效率分析 超效率分析 驾驶模拟 驾驶模拟
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| GB/T 7714 | 杨艳群 , 黄永 , 姚羽珊 et al. 基于DEA模型的山区公路视线诱导设施综合效用评价 [J]. | 交通工程 , 2024 , 24 (03) : 1-9 . |
| MLA | 杨艳群 et al. "基于DEA模型的山区公路视线诱导设施综合效用评价" . | 交通工程 24 . 03 (2024) : 1-9 . |
| APA | 杨艳群 , 黄永 , 姚羽珊 , 郑新夷 . 基于DEA模型的山区公路视线诱导设施综合效用评价 . | 交通工程 , 2024 , 24 (03) , 1-9 . |
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With the rapid increase in electric bicycle (e-bikes) use, the rate of associated traffic accidents has also escalated. Prior studies have extensively examined e-bike riders’ injury risks, yet there is a limited understanding of how their behavior contributes to these accidents. This study aims to explore the relationship between e-bike riders’ risk-taking behaviors and the incidence of traffic accidents, and to propose targeted safety measures based on these insights. Utilizing a mixed-methods approach, this research integrates quantitative data from traffic accident reports and qualitative observations from naturalistic studies. The study employs a binary logistic regression model to analyze risk factors and uses observational data to substantiate the model findings. The analysis reveals that assertive driving behaviors among e-bike riders, such as running red lights and speeding, significantly contribute to the high rate of accidents. Moreover, the lack of protective gear and inadequate safety training are identified as critical factors increasing the risk of severe injuries. The study concludes that comprehensive policy interventions, including stricter enforcement of traffic laws and mandatory safety training for e-bike riders, are essential to mitigate the risks associated with e-bike use. The findings advocate for an integrated approach to urban traffic management that enhances the safety of all road users, particularly vulnerable e-bike riders. © 2024 by author(s).
Keyword ：
e-bikes e-bikes epidemiological studies epidemiological studies logit model logit model natural observation natural observation riding safety riding safety risk-taking behavior risk-taking behavior
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| GB/T 7714 | Yang, Y. , Tian, H. , Feng, Y. et al. Risk-taking behavior of electric cyclists and policy recommendations: A case study [J]. | Journal of Infrastructure, Policy and Development , 2024 , 8 (11) . |
| MLA | Yang, Y. et al. "Risk-taking behavior of electric cyclists and policy recommendations: A case study" . | Journal of Infrastructure, Policy and Development 8 . 11 (2024) . |
| APA | Yang, Y. , Tian, H. , Feng, Y. , Easa, S.M. , Zheng, X. . Risk-taking behavior of electric cyclists and policy recommendations: A case study . | Journal of Infrastructure, Policy and Development , 2024 , 8 (11) . |
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Expressway exit areas experience traffic diversion and complex road conditions, making them accident-prone areas. In this study, transverse and fishbone visual illusion deceleration markings were selected to optimize the induction facilities at expressway exits. The research aims to investigate the impact of these markings on the driving behavior, cognitive load, and physiological characteristics of drivers in various distracted scenarios at expressway exit areas. Furthermore, a comprehensive evaluation of each experimental scheme is conducted using the Matter-Element Extension Model. The study found that the implementation of deceleration markings can effectively enhance driver alertness and lane change awareness, enabling drivers to reduce their speed to near the speed limit in exit areas without compromising driving comfort. Compared to the situation without markings, drivers begin to decelerate approximately 600 m earlier and exit the ramp when markings are present. Fishbone deceleration markings, in contrast to transverse markings, result in lower vehicle speeds, smoother deceleration, and more effectively stimulate drivers' intention to change lanes, guiding them to make the final lane change earlier. Based on the comprehensive evaluation results, it is recommended that transverse or fishbone deceleration markings be considered in engineering practice. These markings have not produced significant effects on driver visual fatigue and driving load, with fishbone markings demonstrating superior comprehensive evaluation outcomes. These research findings can provide valuable insights for future expressway exit area marking design schemes, further enhancing driver safety.
Keyword ：
Deceleration marking Deceleration marking Distracted driver Distracted driver Driving simulation Driving simulation Electroencephalogram data Electroencephalogram data Expressway exit Expressway exit Eye movement Eye movement
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| GB/T 7714 | Yang, Yanqun , Li, Mingtao , Easa, Said M. et al. Effect of expressway exit deceleration markings on distracted drivers in China [J]. | HELIYON , 2024 , 10 (17) . |
| MLA | Yang, Yanqun et al. "Effect of expressway exit deceleration markings on distracted drivers in China" . | HELIYON 10 . 17 (2024) . |
| APA | Yang, Yanqun , Li, Mingtao , Easa, Said M. , Lin, Jie , Zheng, Xinyi . Effect of expressway exit deceleration markings on distracted drivers in China . | HELIYON , 2024 , 10 (17) . |
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Based on combining the relevant studies on situation awareness (SA), this paper integrated multiple indicators, including eye movement, electroencephalogram (EEG), and driving behavior, to evaluate SA. SA is typically divided into three stages: perception, understanding and prediction. This paper used eye movement indicators to represent perception, EEG indicators to represent understanding, and driving behavior indicators to represent prediction. After identifying indicators for evaluating SA, a driving simulation experiment was designed to collect data on the indicators. 41 subjects were recruited to participate in the investigation, and the experimenter collected data from each subject in a total of 9 groups. After removing 4 groups of invalid data, 365 groups of valid data were finally obtained. The grey correlation analysis was used to optimize the SA indicators, and 10 SA evaluation indicators were finally determined. There were the average fixation duration, the nearest neighbor index, pupil area, the percentage power spectral density values of the 3 rhythmic waves (0 , alpha , beta), rhythmic wave energy combination parameters ( alpha / 0), mean speed, SD of speed and acceleration. Taking the optimized 10 indicators as input and the SA scores as output, a backpropagation neural network model with a topological structure of 10-8-1 was constructed. 75% of the data were randomly selected for model training, and the final network training 's mean square error was 0.0025. Using the remaining 25% of data for verification, the average absolute error and average relative error of the predicted results are 0.248 and 0.046, respectively. This showed that the model was effective, and it was feasible to evaluate the SA by using the data of eye movement, EEG and driving behavior parameters.
Keyword ：
Backpropagation neural network Backpropagation neural network Electroencephalogram Electroencephalogram Eye movement Eye movement Situation awareness Situation awareness
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| GB/T 7714 | Yang, Yanqun , Chen, Yue , Easa, Said M. et al. Evaluation of driver's situation awareness in freeway exit using backpropagation neural network [J]. | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2024 , 105 : 42-57 . |
| MLA | Yang, Yanqun et al. "Evaluation of driver's situation awareness in freeway exit using backpropagation neural network" . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR 105 (2024) : 42-57 . |
| APA | Yang, Yanqun , Chen, Yue , Easa, Said M. , Lin, Jie , Chen, Meifeng , Zheng, Xinyi . Evaluation of driver's situation awareness in freeway exit using backpropagation neural network . | TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR , 2024 , 105 , 42-57 . |
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