Safety analysis of pedestrians distracted by mobile phones at street crossings: Field study in Nanjing.

The growing public concern over traffic safety hazards caused by pedestrians' distracted behavior, particularly related to mobile phone usage at pedestrian crossings. Through video recording of pedestrians' street-crossing behaviors on 12 sidewalks across 9 urban road intersections in Nanjing city, 1778 valid pedestrian samples were collected. The study categorizes mobile phone use during the crossing into five distinct types: no use, voice call, screen gaze, screen gaze with operation, and listening to music with headphones. Then, the effects of gender, age and companion conditions on the mobile phone during the crossing were examined by chi-square tests. Utilizing binomial logistic and Relogit regression models, the study analyzed the impact and safety risks of distraction on crossing behavior. Additionally, a random parameters (RP) logit model with heterogeneity in means was used to investigate the determinants affecting mobile phone usage. Notably, individuals aged 18 to 30 years were identified as the random parameter, while factors such as being under 18 years old, having a companion without interaction, having a companion with interaction, weekdays, sidewalk length, and the total number of other pedestrians were identified as fixed parameters. The study also presented significant variables affecting the probability of mobile phone usage through marginal effects, highlighting the potential safety risks associated with mobile phone usage during street crossing. These findings emphasize the need for heightened pedestrian safety awareness and a reduction in distracted behaviors to enhance overall traffic safety.

Geographically weighted machine learning for modeling spatial heterogeneity in traffic crash frequency and determinants in US.

Spatial analyses of traffic crashes have drawn much interest due to the nature of the spatial dependence and spatial heterogeneity in the crash data. This study makes the best of Geographically Weighted Random Forest (GW-RF) model to explore the local associations between crash frequency and various influencing factors in the US, including road network attributes, socio-economic characteristics, and land use factors collected from multiple data sources. Special emphasis is put on modeling the spatial heterogeneity in the effects of a factor on crash frequency in different geographical areas in a data-driven way. The GW-RF model outperforms global models (e.g. Random Forest) and conventional geographically weighted regression, demonstrating superior predictive accuracy and elucidating spatial variations. The GW-RF model reveals spatial distinctions in the effects of certain factors on crash frequency. For example, the importance of intersection density varies significantly across regions, with high significance in the southern and northeastern areas. Low-grade road density emerges as influential in specific cities. The findings highlight the significance of different factors in influencing crash frequency across zones. Road network factors, particularly intersection density, exhibit high importance universally, while socioeconomic variables demonstrate moderate effects. Interestingly, land use variables show relatively lower importance. The outcomes could help to allocate resources and implement tailored interventions to reduce the likelihood of crashes.

Effect of distance information and number of warning signs on driving safety of young adults near road work zones in China.

The continuous growth of automobile ownership and road mileage in China has brought a lot of road maintenance work. The work zone shall be set for road maintenance work. Due to the road characteristics near the work zone, more accidents and a higher accident risk exist. Traffic signs are one of the essential means to ensure traffic safety. The location and number of road work signs (sign level) play a crucial role in driver safety near the work zone. The repeated road work signs can form a warning system to regulate driver behavior. This paper evaluates the effect of the number of warning signs with and without distance information on driver behavior (psychological load and physiological characteristics) near the work zone. The matter-element extension model is used for comprehensive evaluation. The study resulted in several findings. First, adding distance information improves the difficulty and time of visual recognition and enhances driver alertness. On the other hand, too many road signs are not conducive to maintaining driver alertness. Second, distance information on the work signs and the repeated setting of road warning signs add extra burden on the driver and increase driver fatigue. Third, driver's response to the repeated road work signs will gradually become stable; The speed transition under the warning signs Levels 2 and 3 are more stable than that under the warning sign Levels 1 and 4. Finally, the warning sign level shall not be more than 3. If the advanced warning area is short, it is recommended to select a warning sign Level 1. If the advanced warning area is relatively long, it is recommended to choose a warning sign Level 2. Finally, adding distance information will improve the overall effect of the warning scheme. These findings can provide a valuable reference for setting the road work signs near the work zone in practice in China.

Nomophobia, attitude and mobile phone use while riding an E-bike: Testing a dual-process model of self-control.

Using a mobile phone while participating in traffic is a growing safety concern all over the world. However, mobile phone use (MPU) while riding an e-bike has not yet been given enough attention by researchers and practitioners. To fill this gap, this study conducted a preliminary online interview and a questionnaire-based survey in China to study what kinds of MPU behaviors e-bikers commonly engaged in and the prevalence of these behaviors. A conceptual dual-process framework consisting of e-bikers' demographics, e-bike usage pattern, nomophobia, attitude and self-control was also proposed to analyze the psychological mechanism underlying this phenomenon. The preliminary online interview revealed 7 typical types of MPU behaviors performed by e-bikers on the road. Results of the questionnaire survey showed that though the overall frequencies of MPU behaviors were low, nearly 60% of the respondents reported a history of mobile phone use during riding in the last three months. E-bikers' MPU frequencies were significantly impacted by e-bikers' gender, attitude, self-control and information-related nomophobia. Besides, self-control also significantly moderated the predictive effects of information-related nomophobia and attitude on MPU frequencies while ring an e-bike. Fears of being unable to access information on the mobile phone only contributed to MPU at low levels of self-control. In contrast, the protective effect of unfavorable attitude against engagement in the behavior became stronger at high self-control levels. The results not only offer deeper insights into the current situation of MPU among e-bikers in China, but also could facilitate the development of intervention and safety promotion strategies targeting this specific road user group.

Risk factors influencing tunnel construction safety: Structural equation model approach.

At present, the global tunnel construction industry is developing rapidly, but construction accidents are also common. A large number of casualties and property losses are alarming people. It is urgent to pay attention to the causes of tunnel construction accidents, ensure the safety of construction sites, and reduce tunnel construction accidents. Through literature and case analysis, we have sorted out 35 typical tunnel causative factors for research and analysis, which are divided into 7 types. Based on the variable system, we prepared a measurement questionnaire, and 536 valid questionnaires were collected. The structural equation model (SEM) was used to study the relationship between these variables. The influence mechanism and interaction relationship between the variables are analyzed in depth in terms of influence intensity and path coefficient. The results showed that the following six latent variables significantly influence tunnel construction accidents: human factors, material factors, geological exploration design, technical management, safety management, and natural conditions. Natural conditions have the most significant impact, followed by human factors and safety management. Particular attention should be paid to education, training, and safety management in construction risk control. The structural model and research results are helpful to establish the cause theory of tunnel construction accidents, and guide the formulation of safety management policies for tunnel construction projects, reduce tunnel accidents and ensure construction safety.

Mechanical, Electrical, and Tensile Self-Sensing Properties of Ultra-High-Performance Concrete Enhanced with Sugarcane Bagasse Ash.

Although sugarcane bagasse ash (SCBA) possesses favorable cementitious properties, previous research has primarily focused on improving the mechanical performance of conventional concrete- or cement-based composites. Limited attention has been given to ultra-high-performance concrete (UHPC) with SCBA, especially regarding its tensile -sensing properties. This study aimed to comprehensively evaluate the effect of SCBA on the mechanical, electrical, and tensile self-sensing properties of UHPC. The results demonstrated that incorporating SCBA below the critical concentration of 3.0 wt% enhanced the mechanical properties of UHPC. Notably, adding 3.0 wt% SCBA remarkably improved the compressive, flexural, and tensile strengths of UHPC, resulting in increases of 13.1%, 17.4%, and 20.6%, respectively. However, excessive incorporation of SCBA adversely affected the mechanical properties due to reduced workability of UHPC, increased generation of harmful voids, and a lower degree of hydration caused by the excess SCBA. Furthermore, the inclusion of SCBA influenced the electrical resistivity of UHPC, and specifically, an SCBA content of 0.3 wt% yielded the maximum electrical resistivity. Moreover, incorporating SCBA in UHPC enhanced its tensile stress-sensing performance compared to SCBA-free UHPC. Among the various SCBA contents tested, UHPC with 0.3 wt% SCBA presented the best linearity, with values of 8.8% for loading and 17.0% for unloading, respectively, which were significantly lower than those for SCBA-free UHPC, which were 14.0% and 60.0%, respectively. Additionally, UHPC with 0.9 wt% SCBA gained the lowest hysteresis and repeatability, with values of 13.3% and 5.3%, respectively, which were much lower than those for SCBA-free UHPC, which were 50% and 51.6%, respectively. The tensile stress-sensing performance of UHPC is influenced by three key aspects: the gap between adjacent conductive fillers, contact resistance, and the connectivity of the electrical network, which are subject to change due to varying stress states and SCBA concentrations. This study should aid SCBA use and promote UHPC's practical applications.

Factors Affecting Road Tunnel Construction Accidents in China Based on Grounded Theory and DEMATEL.

Despite the continuous progress of tunnel construction technology and safety management technology, road tunnel construction safety still faces many challenges in China, such as how to ensure the effective management and safety control of people and materials, how to ensure the implementation of technology and program implementation, risk assessment of construction site environmental information, etc. Exploring the causes of tunnel construction accidents and understanding the properties of the factors and their interrelationships can effectively control the sources of risk and contribute to the safety control of tunnel construction. Therefore, we have collected 30 formal accident investigation reports from the government safety supervision and management department from 2005 to 2021, including detailed investigation and accident analysis. Based on grounded theory, a qualitative research method to generalize experience through direct observation, abstraction, and analysis of data, we use Nvivo11 software to analyze reports and obtain 6 selective codes, 16 spindle codes, and 43 open codes. In addition, we construct a theoretical model of tunnel construction accident influencing factors, which passed the saturation test. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is used to analyze the influencing mechanism and interaction relationships of these factors. The two dimensions of influence degree and centrality are used to determine the critical influencing factors of tunnel construction accidents in mountainous areas. They are security awareness and professionalism. According to the cause degree, the influencing factors are divided into cause and result factors. Finally, the basis and suggestions for reducing construction accidents are presented.

Analysis of students' anger during riding electric bicycles on campus.

This paper presents a study of the causes of anger of students who ride electric bicycles on a university campus. A questionnaire survey of 370 students in university was conducted using a electric bicycle rider anger scale. Structural equation model is used to analyze the interaction between pedestrians, traffic management, other riders and environment and riders themselves. The results show that the overall level of students' riding anger on the campus was not high, and the interaction with the surrounding environment mainly reflected the riding anger of college students. The interaction of students' anger with campus traffic management requirements was relatively low. Based on the study results, several campus traffic management and safety education recommendations are made.

Analysis of Electric Bicycle Riders' Use of Mobile Phones While Riding on Campus.

Based on the theory of rational action (TRA), overconfidence theory (OT), and deterrence theory (DT), this study explores the reasons for mobile phone use by Chinese students riding electronic bicycles (e-bikes) in Fuzhou City. We tested the reliability and validity of an extended TPB, OT and DT questionnaire (with 531 eligible responses) and constructed a structural equation model of mobile phone use behavior while riding e-bikes, based on the improved model. The structural equation model (SEM) is used to evaluate the relationship between the internal factors of mobile phone riding behavior. The results show that the correlation among mobile phone dependence, punishment mechanism, attitude, and controllable operation impacts e-bike riders' behavior when using mobile phones while riding.

Data Loss Reconstruction Method for a Bridge Weigh-in-Motion System Using Generative Adversarial Networks.

In the application of a bridge weigh-in-motion (WIM) system, the collected data may be temporarily or permanently lost due to sensor failure or system transmission failure. The high data loss rate weakens the distribution characteristics of the collected data and the ability of the monitoring system to conduct assessments on bridge condition. A deep learning-based model, or generative adversarial network (GAN), is proposed to reconstruct the missing data in the bridge WIM systems. The proposed GAN in this study can model the collected dataset and predict the missing data. Firstly, the data from stable measurements before the data loss are provided, and then the generator is trained to extract the retained features from the dataset and the data lost in the process are collected by using only the responses of the remaining functional sensors. The discriminator feeds back the recognition results to the generator in order to improve its reconstruction accuracy. In the model training, two loss functions, generation loss and confrontation loss, are used, and the general outline and potential distribution characteristics of the signal are well processed by the model. Finally, by applying the engineering data of the Hangzhou Jiangdong Bridge to the GAN model, this paper verifies the effectiveness of the proposed method. The results show that the final reconstructed dataset is in good agreement with the actual dataset in terms of total vehicle weight and axle weight. Furthermore, the approximate contour and potential distribution characteristics of the original dataset are reproduced. It is suggested that the proposed method can be used in real-life applications. This research can provide a promising method for the data reconstruction of bridge monitoring systems.

Evaluation of Mental Load of Drivers in Long Highway Tunnel Based on Electroencephalograph.

In recent years, the mileage of the tunnels has substantially increased with the rapid highway construction that led to increasing highway tunnels. Most studies on tunnel accidents have mainly focused on the external environments, such as tunnel structure, traffic volume, and lighting. In addition, although many studies on mental load of drivers have been conducted for public roads, such studies for highway tunnels have been limited. In this study, three scenarios with different front vehicle speeds (60, 45, and 30 km/h) in a two-lane long tunnel (one lane in each travel direction) were evaluated using a driving simulator. The experiment involved 24 participants (14 men and 10 women) with an average age of 25.8 years and an average experience of 3.2 years. The electroencephalogram (EEG) technology was used to collect the leading EEG indicators during the driving simulation of the scenarios: α, ß, and θ waves and the wave ratio, (α + θ)/ß. According to the ß-wave energy measurements, the alertness of drivers was the lowest at 45 km/h after adapting to the tunnel environment, indicating that the drivers were more comfortable at this speed. This preliminary finding should help in determining the speed limit in this type of tunnel.

Sound Effects on Physiological State and Behavior of Drivers in a Highway Tunnel.

Driving behavior in a highway tunnel could be affected by external environmental factors like light, traffic flow, and acoustic environments, significantly when these factors suddenly change at the moment before and after entering a tunnel. It will cause tremendous physiological pressure on drivers because of the reduction of information and the narrow environment. The risks in driving behavior will increase, making drivers more vulnerable than driving on the regular highways. This research focuses on the usually neglected acoustic environment and its effect on drivers' physiological state and driving behavior. Based on the SIMLAB driving simulation platform of a highway tunnel, 45 drivers participated in the experiment. Five different sound scenarios were tested: original highway tunnel sound and a mix of it with four other sounds (slow music, fast music, voice prompt, and siren, respectively). The subjects' physiological state and driving behavior data were collected through heart rate variability (HRV) and electroencephalography (EEG). Also, vehicle operational data, including vehicle speed, steering wheel angle, brake pedal depth, and accelerator pedal depth, were collected. The results indicated that different sound scenarios in the highway tunnel showed significant differences in vehicle speed (p = 0.000, η2 = 0.167) and steering wheel angle (p = 0.007, η2 = 0.126). At the same time, they had no significant difference in HRV and EEG indicators. According to the results, slow music was the best kind of sound related to driving comfort, while the siren sound produced the strongest driver reaction in terms of mental alertness and stress level. The voice-prompt sound most likely caused driver fatigue and overload, but it was the most effective sound affecting safety. The subjective opinion of the drivers indicated that the best sound scenario for the overall experience was slow music (63%), followed by fast music (21%), original highway tunnel sound environment (13%), and voice-prompt sound (3%). The findings of this study will be valuable in improving acoustic environment quality and driving safety in highway tunnels.

Effectiveness of yellow color guardrail belt at freeway exits.

If the information on freeway exits is not effective or driver vigilance is not adequate, the driver may not be able to obtain the information in time, resulting in missing the exit or making a forcible lane-change that could cause an accident. To allow the driver to obtain sufficient exit information in time and get off the freeway safely, this study proposes the creation of a guardrail painted with a yellow color and located prior to the exit. The yellow color guardrail belt (YCB) aims at informing the drivers that there is an exit ahead and to pay attention to the exit information, reminding them to adjust vehicle state and driving behavior in time. A driving simulator experiment with two different scenarios (YCB scenario and baseline scenario with no YCB) were used to explore the effectiveness of the YCB. Data on eye movement, electroencephalograph, and driving behavior of the participants were obtained. The results showed that compared with the baseline scenario, in the YCB scenario, the fixation points were mainly distributed in front of the road and the fixation duration on the guide signs was relatively longer; the EEG ratio (θ + α) / ß was smaller; the driver decelerated more smoothly; and the steering wheel angle was smaller. In addition, the statistical analysis showed that there were significant differences in the fixation duration, the EEG ratio (θ + α) / ß, and steering wheel angle between the two scenarios. This indicated that participants' vigilance in the YCB scenario was significantly improved, where the participants paid more attention to the guide signs and had better control of the vehicle. This study recommends a new device for reminding drivers to pay attention to freeway exits, which would greatly stimulate driver's sense of space on the exit and improve traffic safety on freeways.

Structural Equation Modeling of Drivers' Situation Awareness Considering Road and Driver Factors.

Driver's situation awareness (SA) is one of the key elements that affect driving decision-making and driving behavior. SA is influenced by many factors, and previous studies have focused only on individual factors. This study presents a comprehensive study to explore the path relationships and influence mechanism between SA and all influential factors, including road characteristics, driver characteristics and states, distracting elements, and cognitive ability. A structural equation model that relates SA to its influential factors is developed. A total of 324 valid questionnaires were collected to analyze and identify the relationships between the factors. The results show that the preceding influential factors have significant effects on SA, which is consistent with previous research. Based on path coefficients, positive effects were: cognitive abilities (0.500), driver state (0.360), age (0.277), driving experience (0.198), and gender (0.156). Negative effects were: distracting elements (-0.253) and road characteristics (-0.213). The results of this comprehensive study provide a valuable reference for the development of driver training programs and driving regulations.

Effect of highway directional signs on driver mental workload and behavior using eye movement and brain wave.

The rapid development of expressways has led to an increasing number of place names that must be displayed on road guide signs. As a result, multi-board guide signs have been increasingly set up on expressways. The main aim of this study was to analyze the effect of the directional road sign displayed on multi and single-board signs on driver mental workload and behavior. 32 participants including 16 females (mean age = 24.7 years, standard deviation = 1.9 years) participated in the experiment and completed 3 driving simulation scenes. The setting of each scene-sign board was different: 1 board, 2 boards, and 3 boards. The driver needed to reach the designated destination according to the guidance of the road signs. Eye tracker was used to measure the fixation, saccade and electroencephalogram (EEG) was used to measure the alpha (8-13 hz) band absolute power in different signage scenarios. There are two major findings of the study. First, when the number of place names is less than or equal to 7, the multi-board sign generates more mental workload than the single-board sign does. The alpha band power of the driver's frontal area under the multiple boards is lower and affects driving performance (the deceleration is greater). Second, when the number of place names is more than 7, there is no significant difference in the effect on mental workload whether multi or single-board sign is used. However, compared to the single-board sign, drivers in the case of multi-board sign are likely to reduce the fixation duration and increase the number of saccades. The results suggest that it is not necessary to use multi-board signs when the number of place names is less than 7. These findings provide more safety considerations for the setting of multi-board guide signs in the future.

New solution to build constructed wetland in cold climatic region.

Constructed wetland is an efficient and convenient wastewater treatment technology that has been widely used in China and elsewhere. However, seasonal frozen soil is easily formed in the cold regions of northern China. The local wetlands are in the frozen soil layer, causing the pollutants from wastewater not to be removed well. Therefore, a new constructed wetland structure that uses shallow geothermal energy to keep the wetland not frozen in the winter is proposed in this paper. The results of the experiment show that the average removal rates of total nitrogen, ammonium ion, and total phosphorus in the multistage constructed wetland system are 54.8%, 44.5%, and 77.7%, respectively. This performance is substantially better than that of conventional wetlands in winter. The proposed wetland structure can be applied to conventional wetlands and avoid the conventional wetlands being idle during cold seasons, which is conducive to the popularization of constructed wetlands (CWs) in cold regions.

Evaluation effects of two types of freeway deceleration markings in China.

This paper presents an evaluation of the effectiveness of two types of deceleration markings on freeways in China: fishbone-shaped (FS) markings and edge-rate (ER) markings. An actual 4-lane, 6-km long freeway in Province Hebei was created in a driving simulator and used for the experiments. Three scenarios of deceleration markings were adopted: one without markings, one with FS markings, and the third with ER markings. For each scenario, three traffic flow levels were adopted (low, medium, and heavy). The appropriate dimensions of deceleration markings were first established using relevant design guidelines and then used to develop the simulation scenarios using Multigen Creator software. Sixty drivers carried out the simulation experiments with eye tracker equipment. The adequacy of deceleration markings was analyzed with respect to speed, perceived distance, pupil diameter, and geometric parameters. The results showed that both types of deceleration markings made a certain effect on vehicle speed, drivers'visual behavior, and mental characteristics. However, the effect of the FS markings was more pronounced than that of the ER marking. Specifically, the FS markings showed a speed reduction of 12.3 km/h to 15.2 km/h and a perceived distance of 70 m to 90 m, compared with 6.7 km/h to 9.9 km/h and 40 m to 60 m, respectively, for the ER markings. Application comments of the results are provided in the conclusion.