Identifying interactions among factors related to death occurred at the scene of traffic accidents: Application of "logic regression" method.

Aim: Traffic accidents are caused by several interacting risk factors. This study aimed to investigate the interactions among risk factors associated with death at the accident scene (DATAS) as an indicator of the crash severity, for pedestrians, passengers, and drivers by adopting "Logic Regression" as a novel approach in the traffic field. Method: A case-control study was designed based on the police data from the Road Traffic Injury Registry in northwest of Iran during 2014-2016. For each of the pedestrians, passengers, and drivers' datasets, logic regression with "logit" link function was fitted and interactions were identified using Annealing algorithm. Model selection was performed using the cross-validation and the null model randomization procedure. Results: regarding pedestrians, "The occurrence of the accident outside a city in a situation where there was insufficient light" (OR = 6.87, P-value<0.001) and "the age over 65 years" (OR = 2.97, P-value<0.001) increased the chance of DATAS. "Accidents happening in residential inner-city areas with a light vehicle, and presence of the pedestrians in the safe zone or on the non-separate two-way road" combination lowered the chance of DATAS (OR = 0.14, P-value<0.001). For passengers, "Accidents happening in outside the city or overturn of the vehicle" combination (OR = 8.55, P-value<0.001), and "accidents happening on defective roads" (OR = 2.18, P-value<0.001) increased the odds of DATAS; When "driver was not injured or the vehicle was two-wheeled", chance of DATAS decreased for passengers (OR = 0.25, p-value<0.001). The odds of DATAS were higher for "drivers who had a head-on accident, or drove a two-wheeler vehicle, or overturned the vehicle" (OR = 4.03, P-value<0.001). "Accident on the roads other than runway or the absence of a multi-car accident or an accident in a non-residential area" (OR = 6.04, P-value<0.001), as well "the accident which occurred outside the city or on defective roads, and the drivers were male" had a higher risk of DATAS for drivers (OR = 5.40, P-value<0.001). Conclusion: By focusing on identifying interaction effects among risk factors associated with DATAS through logic regression, this study contributes to the understanding of the complex nature of traffic accidents and the potential for reducing their occurrence rate or severity. According to the results, the simultaneous presence of some risk factors such as the quality of roads, skill of drivers, physical ability of pedestrians, and compliance with traffic rules play an important role in the severity of the accident. The revealed interactions have practical significance and can play a significant role in the problem-solving process and facilitate breaking the chain of combinations among the risk factors. Therefore, practical suggestions of this study are to control at least one of the risk factors present in each of the identified combinations in order to break the combination to reduce the severity of accidents. This may have, in turn, help the policy-makers, road users, and healthcare professionals to promote road safety through prioritizing interventions focusing on effect size of simultaneous coexistence of crash severity determinants and not just the main effects of single risk factors or their simple two-way interactions.

Feeling unwell of passenger travel by small vehicles and associated risk factors in the North Shewa Zone, Oromiya, Ethiopia.

The current study investigated how and why sociocultural structures, situational conditions, and personal behavioural factors cause passengers to feel ill when travelling by minibuses, drawing on ideas from the social construction theory of illness. A significant objective was to investigate associated risk variables that influence passengers' feelings of illness related to the social environment, addressing their beliefs, meanings, practices, and behaviours. A survey method was used to obtain data from 384 passengers for the study. The results of logistic regression indicated that feeling ill when travelling by minibuses differed from passenger to passenger; then, they had their own set of practical and emotional challenges that had no known medical reason. Compared with male and older passengers, female and younger passengers were more likely to feel ill. Furthermore, stress and role-set effects increased passengers' experiences of feeling ill more than did passengers who had no stress prior to the trip and who had only one role. Additionally, passengers who travelled intermittently, utilized suppression techniques to lessen travel discomfort, and fastened seat belts were less likely to experience symptoms of illness. Passengers who travelled on unsafe roads and used alcohol before travel, on the other hand, were more likely to feel ill than those who travelled on safer roads and did not use alcohol before the trip. The findings suggest that passengers should be aware of predisposing conditions that result in illness, be able to rest before travelling, and use all suppressive methods to reduce or prevent illness while travelling by small buses.

Screening and early detection of communicable diseases on board cruise ships: An assessment of passengers' preferences on technical solutions.

BACKGROUND: Implementing technological solutions to screen for and detect early the most prevalent communicable diseases on cruise ships is contingent on, among others, willingness of passengers to accept use of such solutions. METHOD: We surveyed passenger preferences to record their willingness to accept technological solutions for screening and early detection of communicable diseases on cruise ships. Self-reported sociodemographic characteristics, use of technology and acceptance of solutions were recorded anonymously in paper format. Multiple logistic regression analyses investigated the association of demographic and other characteristics with willingness and barriers/concerns of passengers to endorse proposed solutions. RESULTS: Of a total of 1344 passengers on two successive cruises on board CELESTYAL OLYMPIA, 336 (1 every 4) participated in the survey. The vast majority of passengers (92.3 %, n = 310) agreed with at least one solution. Passengers showed lower levels of acceptance for more personalized solutions, such as use of wearable devices (45.5 %) and monitoring with cameras (64.0 %), whereas they were more receptive to less personally invasive solutions, such as integration of cabins with air purifiers (89.6 %) and air quality sensors (80.4 %). Age, self-employment status, educational level, and fear of contacting a communicable disease were significantly correlated with passengers' willingness to adopt proposed solutions. CONCLUSIONS: To successfully integrate screening and early detection technological solutions in cruise ships, it is imperative that targeted awareness and education interventions are implemented on passengers to strengthen understanding and acceptance of such solutions and assuage concerns around monitoring and handling of personal health data.

Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration.

Heating, Ventilation, and Air Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet they frequently fail to ensure provide adequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensors have opened up new possibilities for real-time detection of occupant thermal comfort status and timely feedback to the HVAC system. However, since occupant thermal comfort is subjective and cannot be directly measured, it is generally inferred from thermal environment parameters or physiological signals of occupants within the HST compartment. This paper presents a field test conducted to assess the thermal comfort of occupants within HST compartments. Leveraging physiological signals, including skin temperature, galvanic skin reaction, heart rate, and ambient temperature, we propose a Predicted Thermal Comfort (PTC) model for HST cabin occupants and establish an intelligent regulation model for the HVAC system. Nine input factors, comprising physiological signals, individual physiological characteristics, compartment seating, and ambient temperature, were formulated for the PTS model. In order to obtain an efficient and accurate PTC prediction model for HST cabin occupants, we compared the accuracy of different subsets of features trained by Machine Learning (ML) models of Random Forest, Decision Tree, Vector Machine and K-neighbourhood. We divided all the predicted feature values into four subsets, and did hyperparameter optimisation for each ML model. The HST compartment occupant PTC prediction model trained by Random Forest model obtained 90.4% Accuracy (F1 macro = 0.889). Subsequent sensitivity analyses of the best predictive models were then performed using SHapley Additive explanation (SHAP) and data-based sensitivity analysis (DSA) methods. The development of a more accurate and operationally efficient thermal comfort prediction model for HST occupants allows for precise and detailed feedback to the HVAC system. Consequently, the HVAC system can make the most appropriate and effective air supply adjustments, leading to improved satisfaction rates for HST occupant thermal comfort and the avoidance of energy wastage caused by inaccurate and untimely predictive feedback.

Injury Patterns in Vehicle Crashes: The Significance of Occupant Seating Position.

OBJECTIVES:  Investigating patterns among the outcomes of patients involved in motor vehicle accidents (MVAs) can provide information necessary to guide targeted interventions to improve road traffic safety. Our purpose is to identify any differences between passenger and driver injury severity and overall clinical course after MVAs. METHODS:  We performed a retrospective review and analysis of 3,693 patients involved in MVAs from 2016 to 2021. We divided the data into two groups, drivers and passengers, and compared the Injury Severity Score (ISS), Revised Trauma Score (RTS) on admission, days in the Intensive Care Unit (ICU), length of hospital stay (LOS), post Emergency Department (ED) disposition, discharge (DC) disposition, and signs of life on arrival (SOLA) to the ED. We compared mean ISS, New Injury Severity Score (NISS), RTS, length in ICU and LOS using a student's T-test and SOLA, post-ED and DC disposition using Chi-square analysis. RESULTS:  We did not find any statistically significant difference in ISS, RTS, days in ICU, LOS, or SOLA between the drivers and passengers. However, we did find a statistically significant difference in the post-ED (X2= 113.743, p=<0.0001) and DC disposition (X2=41.172, p=<0.0001) of drivers and passengers. After the ED and DC, more passengers were transferred to a higher level of care than expected, while the inverse was true for drivers. The number of drivers discharged to Skilled Nursing Facilities (SNFs) was also higher than expected, further contributing to the observed difference in DC disposition.  Conclusion: Our study found no statistically significant difference between driver and passenger injury severity, length of hospital stay, days in ICU, and SOLA after an MVA. The clinical courses of the two groups were found to be significantly different based on post-ED and DC disposition data. We identified limitations, such as a relatively small sample size and insufficient data on specific car seat locations for passengers, underscoring the need for a more nuanced exploration. Future research must broaden its scope to encompass diverse crash scenarios, vehicle design and safety technologies, seat belt dynamics, and age- and gender-specific vulnerabilities.

COVID-19 control measures unexpectedly increased the duration of stay at High Speed Rail stations during the first community outbreak in Taiwan.

During the COVID-19 pandemic, Taiwan has implemented strict border controls and community spread prevention measures. As part of these efforts, the government also implemented measures for public transportation. In Taiwan, there are two primary public transportation systems: Taiwan Railways (TR) is commonly utilized for local travel, while the Taiwan High-Speed Rail (THSR) is preferred for business trips and long-distance journeys due to its higher speed. In this study, we examined the impact of these disease prevention measures on the number of passengers and duration of stay in two major public transportation systems during the first community outbreak from April 29th to May 29th, 2021. Using data from a local telecommunications company, our study observed an expected decrease in the number of passengers after the cancellation of non-reserved seats at both TR and THSR stations across all 19 cities in the main island of Taiwan. Surprisingly, however, the duration of stay in some of the cities unexpectedly increased, especially at THSR stations. This unanticipated rise in the duration of stay has the potential to elevate contact probability among passengers and, consequently, the transmission rate. Our analysis shows that intervention policies may result in unforeseen outcomes, highlighting the crucial role of human mobility data as a real-time reference for policymakers. It enables them to monitor the impact of disease prevention measures and facilitates informed, data-driven decision-making.

Thermal sensation prediction model for high-speed train occupants based on skin temperatures and skin wettedness.

Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements.

U.S. network and low-cost carriers' performance in response to COVID-19: Strictness of government policies and passengers' panic.

Coronavirus outbreak has been highly disruptive for aviation sector. There is strong correlation between COVID-19 related news, volatility in transportation, low confidence in travel safety, and uncertainty in this era. In this research, we study and distinguish the COVID-19's impact on U.S. airlines' performance. The network and low-cost carriers responded differently to it in terms of capacity reduction, market share reduction, scheduled flights reduction, flight cancellations, and service quality in the year 2020. We illustrate low-cost carrier had higher efficiency compared to network ones during pandemic by applying Network Data Envelopment Analysis. Furthermore, the effects of two key factors that emerge from COVID-19, the government's stringency actions and passengers' panic, on U.S. airlines efficiency are studied. Our analysis demonstrate that the negative effect is more significant for passengers' panic than it is for governments' stringency measures. In addition, we show that passengers' panic has more impact on the efficiency of network carriers compared to low-cost carrier.

The prevalence of seat belt use among drivers and passengers: a systematic review and meta-analysis.

BACKGROUND: Seat belts might save people's lives in car accidents by preventing severe collision damage and keeping passengers safe from critical injuries. This meta-analysis was performed to assess the prevalence of seat belt use among drivers and passengers. METHODS: The databases of PubMed, Web of Science (WOS), and Google Scholar were searched from the beginning of 2000 to late December 2020 to identify studies that investigated the prevalence of seat belt use among drivers and passengers. The pooled prevalence was calculated using a random-effects model. The STATA-v14 software was used to perform data analysis. RESULTS: Sixty-eight studies that met the inclusion criteria and were suitable for this meta-analysis were identified. The pooled prevalence of seat belt use was 43.94% (95% CI: 42.23-45.73) among drivers, 38.47% (95% CI: 34.89-42.42) among front-seat passengers, and 15.32% (95% CI: 12.33-19.03) among rear-seat passengers. The lowest seat belt use among drivers and passengers was observed in Asia, the Middle East, and Africa, while the highest use was reported in Europe and America. Moreover, the prevalence of seat belt use was higher among women drivers [51.47% (95% CI: 48.62-54.48)] than men drivers [38.27% (95% CI: 34.98-41.87)] (P < 0.001). Furthermore, the highest prevalence of seat belt use was seen among drivers (68.9%) and front-seat passengers (50.5%) of sports utility vehicles (SUVs); in contrast, the lowest prevalence was observed among drivers and passengers of public vehicles such as buses, minibuses, and taxis. CONCLUSIONS: In general, the prevalence of seat belt use was not high among drivers and was even lower among passengers. Moreover, drivers and passengers in Asia, the Middle East, and Africa had the lowest prevalence of seat belt usage. Additionally, drivers and passengers of public transportation (buses, minibuses, and taxis) had a lower rate of seat belt use, especially among men. Therefore, effective interventional programs to improve seat belt use should be designed and implemented, particularly among these at-risk populations in Asia, the Middle East, and Africa.

A close contact identification algorithm using kernel density estimation for the ship passenger health.

COVID-19 has been spread globally, with ships posing a significant challenge for virus containment due to their close-quartered environments. The most effective method for preventing the spread of the virus currently involves tracking and physically isolating close contacts. In this paper, we propose the Close Contact Identification Algorithm (CCIA). The probability density of user location points may be higher in a certain spatial range such as a cabin where there are more location points. The characteristics of CCIA include using Kernel Density Estimation (KDE) to calculate the probability density of each user location point and seeking the maximum Euclidean distance between location points in each cluster for merging clusters. CCIA is capable of calculating the probability density of each location point, a feature that other clustering algorithms, such as Kmeans, Hierarchical, and DBSCAN, cannot achieve. The contribution of CCIA is using the probability density of each location point to identify close contacts in ship environments. The performance of CCIA shows more accurate clustering compared to Kmeans, Hierarchical, and DBSCAN. CCIA can effectively identify close contacts and enhance the capabilities of user devices in mitigating the spread of COVID-19 within ship environments.

Bioprotection of Transportation and Facilities from SARS-CoV-2 (COVID-19).

The recent COVID-19 pandemic has led to a nearly world-wide shelter-in-place strategy. This raises several natural concerns about the safe relaxing of current restrictions. This article focuses on the design and operation of heating ventilation and air conditioning (HVAC) systems in the context of transportation. Do HVAC systems have a role in limiting viral spread? During shelter-in-place, can the HVAC system in a dwelling or a vehicle help limit spread of the virus? After the shelter-in-place strategy ends, can typical workplace and transportation HVAC systems limit spread of the virus? This article directly addresses these and other questions. In addition, it also summarizes simplifying assumptions needed to make meaningful predictions. This article derives new results using transform methods first given in Ginsberg and Bui. These new results describe viral spread through an HVAC system and estimate the aggregate dose of virus inhaled by an uninfected building or vehicle occupant when an infected occupant is present within the same building or vehicle. Central to these results is the derivation of a quantity called the "protection factor"-a term-of-art borrowed from the design of gas masks. Older results that rely on numerical approximations to these differential equations have long been lab validated. This article gives the exact solutions in fixed infrastructure for the first time. These solutions, therefore, retain the same lab validation of the older methods of approximation. Further, these exact solutions yield valuable insights into HVAC systems used in transportation.

Station-Level Effects of the COVID-19 Pandemic on Subway Ridership in the Seoul Metropolitan Area.

This paper investigates the station-level impacts of the coronavirus disease (COVID-19) pandemic on subway ridership in the Seoul Metropolitan Area. Spatial econometric models are constructed to examine the association between ridership reduction caused by the pandemic and station-level characteristics during the pandemic years 2020 and 2021. The results reveal unequal effects on station-level ridership, based on the pandemic waves, the demographics, and the economic features of pedestrian catchment areas. First, the subway system was severely disrupted by the pandemic, with significant decreases in ridership-by about 27% for each of the pandemic years-compared with the pre-pandemic year (2019). Second, the ridership reduction was sensitive to the three waves in 2020 and responded accordingly; however, it became less sensitive to the waves in 2021, indicating that subway usage was less responsive to pandemic waves during the second year of the pandemic. Third, pedestrian catchment areas with higher numbers of younger residents (in their 20s) and older residents (65 years and older), those with more businesses requiring face-to-face interactions with consumers, and stations located in the employment centers were hit the hardest in ridership reduction caused by the pandemic.

Has passenger satisfaction at airports changed with the onset of COVID-19? The case of Seville Airport (Spain).

The changes that have come about at airports in recent decades in the areas of security, deregulation, and technological advances have affected both airport management and the passenger experience at airport facilities. In addition, all around the world, the airport sector has been struck by the COVID-19 pandemic during 2020 and 2021. Using a broad sample of data taken from Airport Service Quality (ASQ) surveys and robust econometric methodology, specifically, an Ordered Logit model with Principal Component Analysis, this paper seeks to cover the gap in the academic literature regarding the effect of a worldwide pandemic on passenger satisfaction at airports during the 2015-2021 period, while taking into consideration the passenger profile and journey and airport attributes. It takes as its reference a Spanish regional airport, which had been experiencing a strong expansion process prior to the pandemic. With respect to the variables linked to the passenger profile, a differential behavior is observed in satisfaction depending on nationality, motive for travel, and destination. In addition, the four facility- and airport process-related dimensions are significant, with cleanliness and comfort standing out above all others. These are even more important in a health emergency scenario such as is currently being experienced. Lastly, 2021 is shown to cause a downturn in the positive passenger satisfaction with the airport that had been observed during the first year of the pandemic. Therefore, more long-term management is required alongside the initial rapid and efficient action taken by airports, with up-to-date information for passengers to internalize the inconveniences associated with this long-drawn-out period of uncertainty.

Bus passenger injury prevention: Learning from onboard incidents.

OBJECTIVE: Bus travel is relatively safe: however there remains a lack of understanding of passenger injury incidents onboard buses. The objective of this study was to understand more about onboard passenger incidents to help inform injury mitigation. METHODS: The UK national STATS19 data and Transport for London bus incident data (IRIS) were used to determine the size of the problem in Greater London. Other data including onboard incident reports from two bus operators and CCTV footage of 70 incidents were used to understand passenger injury in more depth and identify common themes and challenges. RESULTS: The STATS19 and IRIS analysis showed that there was a difference between nationally reported bus incidents compared to locally reported bus incidents. Non-collision incidents are prevalent in the data suggesting there is a large problem to tackle. The CCTV and bus incident data identified braking to be the single largest problem in onboard bus passenger injury incidents. Inconsistent reporting of passenger incidents and injury descriptions make it difficult to identify injury patterns and trends. Areas on the bus appear to contribute to higher injury incidents namely those seats facing and closest to the wheelchair area. Other challenges relating to expected passenger and driver behaviors were noted where blame for the incident and outcome can be attributed to both parties. CONCLUSIONS: This combined analysis of incident reports and CCTV footage has enabled a better understanding of the events leading to on-board passenger injury incidents. Preventing harsh braking would appear to be the most effective way of reducing passenger injuries. Additionally improved data collection would assist both transport authorities and bus operators to identify and monitor the effect of bus safety improvements.

All-terrain vehicle exposure and the association of certified training on adolescent safety behaviors and crash experiences.

BACKGROUND: Certified training courses in all-terrain vehicle (ATV) operation are recommended, but little has been published regarding how they affect riding behaviors. Our objectives were to determine adolescents' ATV riding exposures, crashes and injuries, and the association of completing certified ATV training on riding behaviors. METHODS: Respondents completed an anonymous paper survey at 30 school districts approximately one year after participating in the Safety Tips for ATV Riders (STARs) program. Survey data were compiled using Qualtrics™. Frequency, chi-square, Fisher's exact test, and logistic regression analyses were performed using SAS, V.9.4. RESULTS: 4,891 students completed the survey from Fall 2012-Fall 2019. Respondents were 10-18 years old, and similar numbers of participants were male and female. Fifty-nine percent lived in town, 18% on a farm, and 22% in the country but not on farm. Forty-two percent reported their families owned an ATV. Seventy-seven percent had ridden an ATV, 40% of whom reported riding at least weekly. The vast majority (94%) used ATVs for recreation and 49% used them for work purposes. In the previous year, 22% of riders reported having been in a crash, with 7% of crash victims requiring medical attention for injuries. Greater crash likelihood was seen in males, recreational riders, more frequent riders, competitive racers and those who had ridden with passengers or on roads. Only 8% of riders had completed certified ATV safety training (note, STARs is not a certification program). Those whose families owned ATVs, more frequent riders, and public park users had greater likelihoods of course completion. Relative to their peers, respondents who completed a certification course had higher proportions that always/almost always wore helmets (39% vs. 20%, p < 0.0001) and lower proportions that never/almost never wore helmets (29% vs 58%, p < 0.0001), had ridden with passengers (63% vs. 96%, p < 0.0001), and had driven on public roads (41% vs 50%, p = 0.0065). CONCLUSIONS: ATV safety training certification among Iowa adolescents in the study was infrequent but those that received training reported higher helmet use, less riding with passengers, and less driving on public roads. These data suggest completing safety training certification may promote safer riding behaviors among youth.

Analysis of the Face Mask Use by Public Transport Passengers and Workers during the COVID-19 Pandemic.

(1) Background: The use of face masks and gloves in public places directly shows the commitment of the population to the established regulations. Public transport is one of the most-at-risk places of contamination. The aim of the study was to analyze the face mask use by public transport passengers and workers during the COVID-19 pandemic. (2) Methods: Public transport passengers and workers were surveyed. Periodic intermittent selective observation was used to gauge the level of adherence to the established regulations among public transport passengers. Factor analysis was used to identify factors determining the face-mask-wearing comfort. (3) Results: The majority of passengers (87.5%) and all transport workers (100%) used face masks and gloves. Most of the users wore only face masks. Only 41.6% of passengers and 74.7% of transport workers wore face masks correctly. Motivational attitudes at the implementation of preventive measures were determined: established regulations in the public place (55.8%) and the protection of one's own health and the health of family members (44.2%). Only 22.5% of those wearing face masks believed that doing so will have any effect on the spread of an infectious disease, and 10.8% wore masks to maintain the health of people around themselves. A low level of social responsibility was demonstrated. For 53.4% of workers, face mask wearing was uncomfortable. The majority of workers had adverse reactions to mask wearing: feeling short of breath (52.8%), hyperemia of face skin (33.8%), and facial hyperhidrosis (67.4%). (4) Conclusions: The comfort of wearing a mask is determined by adverse reactions occurrence, the properties of the mask, working conditions, and the duration of wearing the face mask. It is necessary to develop recommendations to reduce wearing discomfort. These recommendations, along with methods of raising the social responsibility of the population, can contribute to a greater commitment of the population to non-specific prevention measures.

Use of modern technologies by public transport passengers during the COVID-19 pandemic.

This paper presents the results of primary research involving a survey of Polish passengers during the COVID-19 pandemic. The survey was conducted in January 2022 using the CAWI method on a representative sample of N = 1,129 Polish adults aged 18 to 60. First, means of transport were classified by distance covered into urban, regional and interregional transport. Survey participants were asked a series of questions regarding the use of modern technologies in public transportation. Before that, however, the frequency of urban (agglomeration), regional, interregional (transregional) and private transport use during the COVID-19 pandemic was examined. More than half of respondents said they used modern technology across all modes of public transportation, and about a quarter said that while they had not yet used these technologies, they intended to do so. Only about 15% of respondents replied they did not use and did not intend to use modern technologies, regardless of the mode of transport. The aim of the paper is to examine the use of modern technologies by passengers in the era of the COVID-19 pandemic. Research results may help to influence passengers' purchasing decisions and to improve services offered by carriers in accordance with the objectives of long-term transport policy of both the European Union and Poland related to sustainable transport development.

Face detection for rail transit passengers based on single shot detector and active learning.

COVID-19 spreads rapidly among people, so that more and more people are wearing masks in rail transit stations. However, the current face detection algorithms cannot distinguish between a face wearing a mask and a face not wearing a mask. This paper proposes a face detection algorithm based on single shot detector and active learning in rail transit surveillance, effectively detecting faces and faces wearing masks. Firstly, we propose a real-time face detection algorithm based on single shot detector, which improves the accuracy by optimizing backbone network, feature pyramid network, spatial attention module, and loss function. Subsequently, this paper proposes a semi-supervised active learning method to select valuable samples from video surveillance of rail transit to retrain the face detection algorithm, which improves the generalization of the algorithm in rail transit and reduces the time to label samples. Extensive experimental results demonstrate that the proposed method achieves significant performance over the state-of-the-art algorithms on rail transit dataset. The proposed algorithm has a wide range of applications in rail transit stations, including passenger flow statistics, epidemiological analysis, and reminders of passenger who do not wear masks. Simultaneously, our algorithm does not collect and store face information of passengers, which effectively protects the privacy of passengers.

Road users' engagement in prosocial and altruistic behaviors: A systematic review.

INTRODUCTION: Engagement in prosocial and altruistic on-road behaviors is a new area of research with potential safety benefits for road users. This paper systematically reviewed studies on road users' engagement in prosocial and altruistic behaviors to provide guidance regarding the next steps in this area of research, particularly to inform targeted interventions. The objective was to identify the types of on-road prosocial and altruistic behaviors that have been studied, and the factors associated with these behaviors. Road users were defined as drivers, passengers, or vulnerable road users (e.g., pedestrian, motorcyclists, and bicyclists). METHOD: The database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRIMSA) guidelines and was conducted in June 2021. A total of 23,090 articles were identified in four databases including APA PsycINFO, Embase, Web of Science, and the Transportation Research Information Database. Eleven articles (13 studies) published between 2004 and 2021 met the inclusion criteria and were included in the review. RESULTS: Six studies focused on intervening behaviors, specifically relating to passengers' willingness or intentions to speak up to a driver engaging in unsafe driving behaviors, four studies focused on drivers' yielding behaviors at crosswalks, and one study each focused on altruistic driving behaviors, prosocial driving behavior at long-wait stops, and prosocial behavior towards cyclists. Studies typically examined characteristics of the prosocial road user, including self-esteem, efficacy, and subjective norms, as well as contextual factors, such as other road users' behaviors and on-road messaging. CONCLUSIONS: This review highlights specific factors that may predict road users' engagement in prosocial and altruistic on-road behaviors. PRACTICAL APPLICATIONS: The outcomes from this review may be used to guide the development of future road safety public education messages designed to encourage greater participation in prosocial and altruistic on-road behaviors that act to benefit all road users.