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学者姓名：赵晓华
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Abstract ：
To explore the influence of emergency evacuation signs on passengers' behavior during subway fires and to enhance evacuation efficiency sustainably, this study proposes a dynamic emergency evacuation sign scheme. Utilizing a building information modeling (BIM) and virtual reality (VR) technology simulation platform, two schemes-current static signage and a novel dynamic signage system-are developed and evaluated. The research focuses on four scenarios combining varying crowd conditions (2:8 and 5:5) with signage types. Through experiments, we compare the performance of the current signage and the new dynamic signage in terms of evacuation efficiency and wayfinding difficulty. The results indicate that the dynamic identification system significantly improves evacuation efficiency, reduces incorrect route choices, and minimizes passenger confusion. Particularly in a complex scenario with a 2:8 crowd state, the dynamic signage effectively helps passengers avoid the negative impacts of group decision errors. Additionally, individual characteristics such as age, gender, spatial ability, and evacuation training experience significantly influence evacuation performance. By reducing risks, enhancing urban resilience, and optimizing evacuation processes, this study contributes to sustainable urban infrastructure safety. The findings provide a theoretical basis for designing sustainable emergency signage systems that address the social, economic, and environmental aspects of resilience in urban transportation.
Keyword ：
dynamic emergency evacuation signage system dynamic emergency evacuation signage system fire fire evacuation behavior evacuation behavior generalized estimating equations generalized estimating equations sustainable development sustainable development virtual reality virtual reality
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| GB/T 7714 | Zhao, Xuena , Bian, Yang , Zhao, Xiaohua et al. Sustainable Development Through Dynamic Emergency Evacuation Signage: A BIM- and VR-Based Analysis of Passenger Behavior [J]. | SUSTAINABILITY , 2025 , 17 (6) . |
| MLA | Zhao, Xuena et al. "Sustainable Development Through Dynamic Emergency Evacuation Signage: A BIM- and VR-Based Analysis of Passenger Behavior" . | SUSTAINABILITY 17 . 6 (2025) . |
| APA | Zhao, Xuena , Bian, Yang , Zhao, Xiaohua , Zhang, Yu . Sustainable Development Through Dynamic Emergency Evacuation Signage: A BIM- and VR-Based Analysis of Passenger Behavior . | SUSTAINABILITY , 2025 , 17 (6) . |
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Abstract ：
Much research has been conducted on takeover behavior in automated driving, and integrating these studies into a knowledge system can help to gain a deeper understanding of the current research status and guide critical future research. The takeover focused in this study refers to the takeover related to human intervention (i.e. the transfer of control between the human driver and the auto drive system), rather than the context of overtaking another vehicle (e.g., lane changes and acceleration). The takeover behavior is a multi-stage process consisting of situation awareness, decision & reaction, and takeover performance stages. An in-depth review of takeover behavior characteristics from the three takeover stages is helpful to describe the takeover process and analyze takeover behavior characteristics systematically. Therefore, this paper aims to review driver's takeover performance from the three levels of driver, automated vehicle, and road environment based on the takeover behavior mode. First, we identified 1329 articles through a systematic literature search. 122 articles were included in this review. Second, we use the knowledge graph method for bibliometric analysis. Third, we systematically review the characteristics of takeover behavior in three stages (situation awareness, decision & reaction, takeover performance) from three dimensions: driver, vehicle, and road environment. At the same time, this study develops scoring rules that quantify each factor's contribution to takeover behavior. Fourth, based on the reviewed literature and scores, 18 suggestions were proposed to improve takeover behavior from three levels: drivers, vehicles, road environment. Finally, we have outlined the future fundamental research of takeover behavior. This review summarizes the research content of takeover behavior testing and forms a knowledge system, which provides researchers with a window to understand the research status and development context. This review can guide future research on takeover behavior.
Keyword ：
Statistical scores Statistical scores Test evaluation Test evaluation Improvement suggestion Improvement suggestion Takeover behavior Takeover behavior Reviews Reviews Automated vehicle Automated vehicle
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| GB/T 7714 | Chen, Haolin , Zhao, Xiaohua , Chen, Chen et al. A systematic review on test performance of the driver takeover process in automated driving [J]. | ACCIDENT ANALYSIS AND PREVENTION , 2025 , 215 . |
| MLA | Chen, Haolin et al. "A systematic review on test performance of the driver takeover process in automated driving" . | ACCIDENT ANALYSIS AND PREVENTION 215 (2025) . |
| APA | Chen, Haolin , Zhao, Xiaohua , Chen, Chen , Li, Zhenlong , Li, Haijian , Wang, Qiuhong . A systematic review on test performance of the driver takeover process in automated driving . | ACCIDENT ANALYSIS AND PREVENTION , 2025 , 215 . |
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Abstract ：
The emergency evacuation sign system is crucial for the safety and sustainable development of urban rail transit. Dynamic emergency evacuation signs, which offer real-time guidance during emergencies, are gaining prominence. There is an urgent need to develop a dynamic system that balances perceptual and cognitive visibility. Against this backdrop, this study built a simulation experiment platform based on BIM, Unity, and VR. Eight experimental scenarios were created using the platform: two emergency events (fire/fire accompanied by power outage) x four emergency evacuation signage systems (static emergency signage system/dynamic dissuasion emergency signage system/dynamic dissuasion emergency signage system with flashing/dynamic dissuasion emergency signage system with flashing and auxiliary information), and experimental testing was completed. The evacuation behavior parameters of 39 passengers were extracted and used to construct a multidimensional indicator system. Subsequently, generalized estimation equations were applied to investigate the impact mechanism of signage systems on passengers' evacuation behavior. Finally, the coupling coordination degree model was used to quantitatively evaluate the coupling coordination level of four emergency evacuation signage systems under different emergencies. Results indicate that compared to static signage system, the three sets of dynamic identification system schemes have a positive impact on passenger evacuation behavior and significantly reduce the number of decision-making errors. Particularly in high-risk scenarios involving fire accompanied by power outages, the dynamic dissuasion emergency signage system with flashing and auxiliary information outperforms others by achieving a better balance of reliability, efficiency, and safety. This study investigates the efficacy of various emergency evacuation signage systems across diverse emergency scenarios, offering insights for the enhanced design of such systems and thereby fostering the sustainable development of urban rail transit infrastructure.
Keyword ：
fire fire virtual reality virtual reality dynamic emergency evacuation signage system dynamic emergency evacuation signage system evacuation behavior evacuation behavior coupling coordination degree model coupling coordination degree model generalized estimating equations generalized estimating equations
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| GB/T 7714 | Zhang, Yu , Bian, Yang , Zhao, Xiaohua et al. Integrating Safety and Efficiency: Design and Evaluation of Dynamic Emergency Evacuation Sign System in Urban Rail Transit [J]. | SUSTAINABILITY , 2024 , 16 (24) . |
| MLA | Zhang, Yu et al. "Integrating Safety and Efficiency: Design and Evaluation of Dynamic Emergency Evacuation Sign System in Urban Rail Transit" . | SUSTAINABILITY 16 . 24 (2024) . |
| APA | Zhang, Yu , Bian, Yang , Zhao, Xiaohua , Zhao, Xuena . Integrating Safety and Efficiency: Design and Evaluation of Dynamic Emergency Evacuation Sign System in Urban Rail Transit . | SUSTAINABILITY , 2024 , 16 (24) . |
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Abstract ：
As electric bikes (e-bikes) rapidly develop in China, their traffic safety issues are becoming increasingly prominent. Accurately detecting risky riding behaviors and conducting mechanism analysis on the multiple risk factors are crucial in formulating and implementing precise management policies. The emergence of shared ebikes and the advancements in interpretable machine learning present new opportunities for accurately analyzing the determinants of risky riding behaviors. The primary objective of this study is to examine and analyze the risk factors related to speeding behavior to aid urban management agencies in crafting necessary management policies. This study utilizes a large-scale dataset of shared e-bike trajectory data to establish a framework for detecting speeding behavior. Subsequently, the extreme gradient boosting (XGBoost) model is employed to identify the level of speeding risk by leveraging its excellent identification ability. Moreover, based on measuring the degree of interaction among road, traffic, and weather characteristics, the investigation of the complex interactive effects of these risk factors on high-risk speeding is conducted using bivariate partial dependence plots (PDP) by its superior parsing ability. Feature importance analysis results indicate that the top five ranked variables that significantly affect the identified results of speed risk levels are land use density, rainfall, road level, curbside parking density, and bike lane width. The interaction analysis results indicate that higher levels of road and bike lane width correspond to an increased possibility of high-risk speeding among riders. Land use density, curbside parking density, and rainfall display a nonlinear effect on high-risk speeding. Introducing road level, bike lane width, and time interval could change the patterns of nonlinear effects in land use density, curbside parking density, and rainfall. Finally, several policy recommendations are proposed to improve e-bike traffic safety by utilizing the extracted feature values associated with a higher probability of high- risk speeding.
Keyword ：
Risk factors Risk factors Speeding behavior Speeding behavior Policy recommendations Policy recommendations Shared e -bike Shared e -bike Interpretable machine learning Interpretable machine learning
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| GB/T 7714 | Zhang, Xiaolong , Zhao, Xiaohua , Bian, Yang et al. Interactive effects analysis of road, traffic, and weather characteristics on shared e-bike speeding risk: A data-driven approach [J]. | ACCIDENT ANALYSIS AND PREVENTION , 2024 , 207 . |
| MLA | Zhang, Xiaolong et al. "Interactive effects analysis of road, traffic, and weather characteristics on shared e-bike speeding risk: A data-driven approach" . | ACCIDENT ANALYSIS AND PREVENTION 207 (2024) . |
| APA | Zhang, Xiaolong , Zhao, Xiaohua , Bian, Yang , Huang, Jianling , Yin, Luyao . Interactive effects analysis of road, traffic, and weather characteristics on shared e-bike speeding risk: A data-driven approach . | ACCIDENT ANALYSIS AND PREVENTION , 2024 , 207 . |
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Abstract ：
Nowadays, navigation systems are widely used in public travel because they can instantly offer GPS-based route directions. Following the navigation prompt messages while driving is considered a secondary driving task, while vehicle control is regarded as a primary driving task. Navigation prompt messages with more information can deliver more cues to drivers, but they require a higher cognitive demand and vice versa. To systematically explore the effects of the amount of information from navigation voice prompts and further quantify the utility of voice prompts, four types of prompt messages with increasing amounts of information, denoted as a Single Message, Double Message, Triple Message, and Quadruple Message, were designed. A driving simulation experiment was conducted to obtain driving behavior data under different prompt messages. The one-way analysis of variance (ANOVA) and Kruskal-Wallis (KW) test were used to examine the differences in driving performance under the guidance of different prompt messages from multiple perspectives. Then, eight indicators were selected based on the functions of the navigation system and the driver's response, and the grey near-optimal method was used to determine the utility of the four types of prompt messages. This study found that the four types of navigation prompt messages all began to take effect at about 200 m upstream of the stop bar. The differences between the four types of prompt messages were more significant in the zone from 100 m upstream and ended at 100 m downstream of the stop bar of the intersection. Drivers using Single and Double Messages exhibited more powerful deceleration than those using Triple and Quadruple Messages. The utility values of the four types of prompt messages increased with the increase in the amount of information. This study provides theoretical support for optimizing navigation information and lays a foundation for establishing navigation broadcast guidelines.
Keyword ：
navigation system navigation system driving behavior and performance driving behavior and performance grey near-optimal method grey near-optimal method driving simulation technology driving simulation technology the amount of information from navigation voice the amount of information from navigation voice
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| GB/T 7714 | Yang, Liping , Zhao, Xiaohua , Bian, Yang et al. Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance [J]. | SUSTAINABILITY , 2024 , 16 (14) . |
| MLA | Yang, Liping et al. "Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance" . | SUSTAINABILITY 16 . 14 (2024) . |
| APA | Yang, Liping , Zhao, Xiaohua , Bian, Yang , Zhang, Mengmeng , Guo, Yajuan . Effects of the Amount of Information from Navigation Voice Guidance on Driving Performance . | SUSTAINABILITY , 2024 , 16 (14) . |
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Abstract ：
A comprehensive understanding of the traffic situation in the Monitoring Blind Areas (MBA) of highway is very important for traffic management. However, the complete absence of historical data renders conventional traffic data imputation methods, including tensor decomposition and deep learning algorithms, ineffective. In this paper, a Spatio-temporal Copula (ST-Copula) method is proposed based on the theory of spatial statistics to interpolate traffic data in MBA. Firstly, based on the data series of observation points, the corresponding marginal distribution functions are obtained by data fitting. These marginal functions then be aggregated into a joint function using Copula theory. Secondly, a spatiotemporal correlation matrix is constructed with the spatial variation function to describe the dependent structure of the traffic data, and the maximum likelihood method is adopted to estimate the parameters. Finally, conditional probability density function is constructed according to the spatial location, and Monte-Carlo sampling is applied to deduce the traffic data of the MBA. Based on the above methodology, speed data from a freeway in Zhejiang Province are collected to evaluate the effectiveness of the ST-Copula model. The results showed that compared to Kriging and Copula-based methods, the ST-Copula achieves reductions of 36.4 % and 34.8 % in MAPE and RMSE values, respectively, across various conditions. ST-Copula reduces the limitations of inherent Gaussian assumptions in traditional spatial statistical methods, demonstrating robustness in handling high spatiotemporal variability. The proposed method demonstrates the feasibility of inferring global traffic conditions from limited observations, effectively allowing the monitoring of entire road networks using fewer detectors, thereby reducing road construction costs and rapid response to emergencies.
Keyword ：
Traffic data interpolation Traffic data interpolation Monitoring blind area Monitoring blind area ST-Copula ST-Copula Spatiotemporal autocorrelation Spatiotemporal autocorrelation
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| GB/T 7714 | Yang, Haiyi , Zhao, Xiaohua , Luan, Sen et al. A ST-Copula method for highway traffic data interpolation in monitoring blind areas [J]. | MEASUREMENT , 2024 , 242 . |
| MLA | Yang, Haiyi et al. "A ST-Copula method for highway traffic data interpolation in monitoring blind areas" . | MEASUREMENT 242 (2024) . |
| APA | Yang, Haiyi , Zhao, Xiaohua , Luan, Sen , Qi, Jianyu . A ST-Copula method for highway traffic data interpolation in monitoring blind areas . | MEASUREMENT , 2024 , 242 . |
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Abstract ：
In this paper, the potential of using a head-up display (HUD) in the connected environment to improve a vehicle's running comfort and pedestrian safety is tested, by providing warning information to drivers in advance. To achieve this objective, driving simulation technology is used to construct the connected environment and develop the HUD, and the effectiveness of the system is then tested. Specifically, thirty-four participants were recruited to conduct driving simulation experiments in six scenarios: three warning display types (Baseline/Head-down display/Head-up display) combined with two weather conditions (clear weather/foggy weather). The effects of the three different warning display types on braking risk-avoidance strategy were studied by comparing the drivers' performance during the perception and decision stage (position of accelerator-pedal release, position of first braking), the risk-avoidance manipulation stage (maximum deceleration, braking distance) and the risk-avoidance result stage (minimum collision distance, position of minimum speed). The influences of weather conditions and driver attributes were also considered. When the HUD warnings were activated, drivers started to decelerate further away from pedestrians, with a more stable and moderate deceleration process and a greater safety margin between the vehicle and the pedestrians. Using HUD warnings in foggy conditions improved drivers' perception and decision abilities, this study confirmed the great benefits that HUD warnings in the connected environment can bring to traffic safety, especially under risky situations and inclement weathers. The research results provide a reference for the more humanized and rationalized optimization design of these warning systems.
Keyword ：
pedestrian safety pedestrian safety risk avoidance strategy risk avoidance strategy Connected environment Connected environment head-up display warning head-up display warning generalized linear mixed model generalized linear mixed model
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| GB/T 7714 | Zhang, Yu , Bian, Yang , Zhao, Xiaohua et al. Improving Pedestrian Safety with Head-Up Display Warning in a Connected Environment [J]. | INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION , 2024 , 41 (6) : 3724-3744 . |
| MLA | Zhang, Yu et al. "Improving Pedestrian Safety with Head-Up Display Warning in a Connected Environment" . | INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION 41 . 6 (2024) : 3724-3744 . |
| APA | Zhang, Yu , Bian, Yang , Zhao, Xiaohua , Li, Xuewei , Zhang, Jianhua . Improving Pedestrian Safety with Head-Up Display Warning in a Connected Environment . | INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION , 2024 , 41 (6) , 3724-3744 . |
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Abstract ：
Wrong-way riding (WWR) behavior of electric bikes (e-bikes) is a hazardous practice that frequently threatens traffic safety. It is imperative to accurately detect instances of WWR and analyze the various factors contributing to this behavior to develop and implement effective management policies. The emergence of shared e-bikes and advancements in machine learning have opened up new avenues for accurately examining the determinants of WWR behavior. Therefore, this study utilizes a large-scale dataset of shared e-bike trajectory data to establish a framework for detecting WWR behavior. Subsequently, association rule mining investigates the correlation among road, traffic, environmental factors, and the likelihood of higher and lower WWR behavior. The results indicate that: (1) In the association rules for higher WWR frequency, the absence of central separation facilities and bike lane separation facilities on the tertiary road, as well as lower land use density and the lack of public transportation facilities, enhanced the likelihood of WWR occurrence; (2) In the association rules for lower WWR frequency, longer crossing facility distance, physical bike lane separation, along with higher land use mixing and the presence of public transportation facilities, reduce the probability of WWR occurrence; (3) Time conditions display spatial heterogeneity, and different land use and road condition modulate the impact of time factors on rider' intention for WWR. Finally, based on the study findings, adequate policy recommendations are proposed for urban management agencies to reduce WWR behavior and enhance the safety of the e-bike traffic system.
Keyword ：
Wrong-way riding behavior Wrong-way riding behavior Influencing mechanism Influencing mechanism Shared e -bike Shared e -bike Improvement measures Improvement measures Association rule mining Association rule mining
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| GB/T 7714 | Zhang, Xiaolong , Bian, Yang , Zhao, Xiaohua et al. The association of road, traffic, and environmental factors with wrong-way riding behavior on shared e-bikes [J]. | JOURNAL OF CLEANER PRODUCTION , 2024 , 470 . |
| MLA | Zhang, Xiaolong et al. "The association of road, traffic, and environmental factors with wrong-way riding behavior on shared e-bikes" . | JOURNAL OF CLEANER PRODUCTION 470 (2024) . |
| APA | Zhang, Xiaolong , Bian, Yang , Zhao, Xiaohua , Huang, Jianling , Liu, Zhongyin . The association of road, traffic, and environmental factors with wrong-way riding behavior on shared e-bikes . | JOURNAL OF CLEANER PRODUCTION , 2024 , 470 . |
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Abstract ：
To address dynamic and accurate evaluation of driving style in taxi driver safety management, this paper establishes a dynamic recognition model of driving style using a combination of unsupervised clustering and supervised classification. Based on the natural driving data of 124 taxis in Beijing for one month, the concept of vehicle operation information entropy is proposed. The driver's safety style is clustered by the K-means++ clustering algorithm to obtain three driving styles: "cautious," "aggressive," and "normal." The dynamic recognition model of driving style is established using Gradient Boosting Decision Tree (GBDT), support vector machine (SVM), and logistic regression (LR), and the effects of models are evaluated and compared. Results show that the GBDT algorithm has a better classification effect and stronger applicability to low-dimensional data. This model accurately identifies aggressive drivers. The research results provide support for drivers' safety management and targeted intervention in the taxi industry.
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| GB/T 7714 | Yan, Pengwei , Zhao, Xiaohua , Yao, Ying et al. Driving Style Recognition of Taxi Drivers Based on Naturalistic Driving Data [J]. | CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION , 2023 : 1225-1234 . |
| MLA | Yan, Pengwei et al. "Driving Style Recognition of Taxi Drivers Based on Naturalistic Driving Data" . | CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION (2023) : 1225-1234 . |
| APA | Yan, Pengwei , Zhao, Xiaohua , Yao, Ying , Ma, Xiaogang . Driving Style Recognition of Taxi Drivers Based on Naturalistic Driving Data . | CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION , 2023 , 1225-1234 . |
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Abstract ：
The change of space environment at the tunnel entrance which the light changes from bright to dark will lead to frequent traffic accidents. To explore whether the connected vehicle environment will improve the driving performance and traffic safety at the tunnel entrance, this paper first of all designed a driving simulation experiment and provided driving aids through the Human-Machine Interface (HMI). Then 35 drivers were invited to take a driving simulation under two different driving conditions: traditional driving environment (HMI-OFF) and connected vehicle environment (HMI-ON). Finally, the effectiveness and safety of HMI can be evaluated from two aspects of driver response efficiency and deceleration process, and further explore the causes of driving behavior changes by Cox model. The results show that the driver's response efficiency and deceleration behavior are both improved in the connected vehicle environment. The warning information provided by in-vehicle HMI enables the driver to know the road conditions ahead earlier and adjust the speed through more gentle acceleration so that the vehicle can enter the tunnel at a more stable speed. At the same time, there are significant differences in the brake-movement time of different driving ages, which the brake-movement time increases with the driving age. This indicates that experienced drivers usually adopt a soft way to adjust the speed, so that the vehicle speed change process is more stable on the premise of ensuring driving safety, so as to avoid the potential danger brought by drastic speed change. In this paper, a validity evaluation method based on survival analysis is proposed for tunnel entrance scenarios, which provides a reference for the realization of connected vehicle evaluation.
Keyword ：
transport transport survival analysis survival analysis human-machine interface human-machine interface Connected vehicle environment Connected vehicle environment
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| GB/T 7714 | Zhang, Jianhua , Zhao, Xiaohua , Li, Haijian et al. Evaluation of the Connected Vehicle Environment Effectiveness at Tunnel Entrance [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2023 , 24 (11) : 11699-11709 . |
| MLA | Zhang, Jianhua et al. "Evaluation of the Connected Vehicle Environment Effectiveness at Tunnel Entrance" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 24 . 11 (2023) : 11699-11709 . |
| APA | Zhang, Jianhua , Zhao, Xiaohua , Li, Haijian , Qi, Jianyu , Xing, Guanyang . Evaluation of the Connected Vehicle Environment Effectiveness at Tunnel Entrance . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2023 , 24 (11) , 11699-11709 . |
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