Analysis of Motor Vehicle Accidents: Comparison Between Before and During the COVID-19 Lockdown in Maharashtra, India.

To prevent the pandemic spread of human-to-human transmitted diseases such as COVID-19, governments commonly resort to countrywide or regional lockdown strategies. Such lockdowns, whenever and wherever implemented, curtail the movement of persons and vehicles, and drastically alter traffic conditions. This study focuses on the effect of drastic and sudden changes in the traffic conditions, during the COVID-19 lockdown in the State of Maharashtra in India, in March-June 2020, on the numbers of motor vehicle accidents (MVAs), and the resultant fatalities and injuries. Content analysis of police-reported first information reports (FIRs) of MVAs is performed, and these lockdown trends are compared with archival data from corresponding previous (normal) periods. The statistical analysis shows that, during the lockdown, while the total number of MVAs fall drastically, they are more severe and have a much higher fatality rate per MVA. Also, the pattern of vehicles involved in MVAs, and resultant pattern of fatalities, also changes during lockdowns. The paper explores the reasons for these changed patterns and provides suggestions to reduce these negative externalities of pandemic related lockdowns.

Assessing the Effect of COVID-19 on the Traffic Safety of Intercity and Major Intracity Roads in Saudi Arabia.

The coronavirus disease 2019 (COVID-19) pandemic led to rapid and unexpected changes across the world, particularly in road safety. Thus, this work assesses the impact of COVID-19 accompanied by government preventive policies on road safety in Saudi Arabia by investigating the crash frequency and crash rates. A 4-year crash dataset relating to 2018-2021 was collected, covering about 71,000 km in total road length. It covers all intercity roads and some of the major intercity roads in Saudi Arabia with over 40,000 data logs of involved crashes. We considered three different time phases to observe road safety. These time phases were identified by the duration of government curfew measures against COVID-19 (before, during, and after). The crash frequency analysis showed that the curfew during COVID-19 significantly impacted the crash reduction. At a national level, the crash frequency decreased during 2020 and reached a 33.2% reduction compared to 2019 (the previous year), and it surprisingly continued decreasing in 2021 (the consequent year) to another 37.7% reduction although the government measures were lifted. Moreover, considering the traffic volume and road geometry, we analyzed crash rates for 36 selected segments, and the results showed a significant reduction in the crash rate before and after the COVID-19 pandemic. Additionally, a random effect negative binomial model was developed to quantify the impact of the COVID-19 pandemic. The results showed that the reduction in crashes was significant during and after COVID-19. Also, single roads (two-lane, two-way) were found to be more dangerous than other types of roads.

Safe In and Out of the Car

Our cars make our everyday life much easier. With their help, in a day full of programs, we can get anywhere on time without carrying our packages on our own. In our rushing world, there is the probability that even if we have enough time to get there somewhere, we will hurry, which leads to inattention or worse case an accident. Car manufacturers have a huge amount of research projects to install driver-assistance safety electronics into our cars that, even if they are not driving, instead of the driver, alert to an accident and help to avoid a stutter or a life-threatening accident. According to the Hungarian Central Statistical Office (KSH), research on car manufacturers has brought significant results, as while in 1990 there were nearly 37,000 accidents involving personal injuries on the roads, in 2020 there were only 18,000 such accidents. However, in addition to these active and passive safety features, we need to be aware of and follow the written and unwritten rules of road safety. However, the number of passenger cars has increased so significantly in the last 20-25 years-but especially in the last two years due to the coronavirus epidemic-as roads are characterized by such a high degree of congestion that pedestrians and cyclists require much more attention from participants. This way it is important children receive proper education on the rules of walking or cycling at nursery school and preschool age. The aim of the study is to enumerate and present the platforms that help children to learn, know and deepen the rules of safe traffic.

Health Impacts of COVID-19 through the Changes in Mobility

Understanding the wider effects of the COVID-19 pandemic on public health is needed to respond sufficiently to the impacts and facilitate recovery. We studied the secondary health impacts of COVID-19 through the changes in transportation using a ripple effect mode. Three ripples are defined to reflect the impacts of COVID-19 on (1) transportation and the systems behind it, (2) transportation-related health risk factors, and (3) public health. COVID-19 impacts on transportation are synthesized through six areas: transportation demand, transportation mode, traffic safety, land use and built environment, transportation jobs, and transportation equity. These changes are further associated with decreased transportation-related air pollution, greenhouse gases, noise, heat, and stress. Higher rates of road casualties were observed in the area of COVID-19. Social exclusion and limitations in accessibility to healthcare and healthy food were identified as negative consequences of changes in transportation. There are uncertainties in the rate of active transportation (i.e., walking and cycling) and related crashes that require further investigation. The findings of this study uncover the complex and relatively unknown impacts of COVID-19 on public health through changes in transportation. © 2023 by the authors.

Near-term impact of COVID-19 pandemic on seniors' crash size and severity.

Recent research revealed that COVID-19 pandemic was associated with noticeable changes in travel demand, traffic volumes, and traffic safety measures. Despite the reduction of traffic volumes across the US, several recent studies indicated that crash rates increased across different states during COVID-19 pandemic. Although some recent studies have focused on examining the changes in traffic conditions and crash rates before and during the pandemic, not enough research has been conducted to identify risk factors to crash severity. Even the limited research addressing the contributing factors to crash severity were focused on the pool category of drivers and no insight is available regarding older drivers, one of the most vulnerable groups to traffic collision and coronavirus. Moreover, these studies investigated the early impact of the COVID-19 pandemic mostly using up to three months of data. However, near-term and long-term effects of the COVID-19 pandemic are still unknown on traffic collisions. Therefore, this study aims to contribute to the literature by studying the near-term impact of the COVID-19 pandemic on crash size and severity among older drivers. To this end, a relatively large sample of crash data with senior drivers at fault was obtained and analyzed. To identify the main contributing factors affecting crash outcomes, Exploratory Factor Analysis was conducted on a high-dimension data set to identify potential latent factors which were validated through Confirmatory Factor Analysis. After that, Structural Equation Modeling technique was performed to examine the associations among the identified independent latent factors and the dependent variable. Additionally, SEM model identified the impact of the COVID-19 pandemic on seniors' crash severity. The findings reveal that several latent variables were the significant predictors of crash severity of older drivers including "Driving maneuver & crash location", "Road features and traffic control devices", "Driver condition & behavior", "Road geometric characteristics", "Crash time and lighting", and "Road class" latent factors. The binary variable of "Pandemic" was found to be as highly significant as the last four latent factors mentioned above. This means not only were older drivers more likely to be involved in higher crash size with higher severity level during the pandemic period, but also "Pandemic" was a risk factor to seniors as much as "Driver condition & behavior", "Road geometric characteristics", "Crash time & lighting", and "Road class" factors. The results of this study provide useful insights that may improve road safety among senior drivers during pandemic periods like COVID-19.

Safe In and Out of the Car

Our cars make our everyday life much easier. With their help, in a day full of programs, we can get anywhere on time without carrying our packages on our own. In our rushing world, there is the probability that even if we have enough time to get there somewhere, we will hurry, which leads to inattention or worse case an accident. Car manufacturers have a huge amount of research projects to install driver-assistance safety electronics into our cars that, even if they are not driving, instead of the driver, alert to an accident and help to avoid a stutter or a life-threatening accident. According to the Hungarian Central Statistical Office (KSH), research on car manufacturers has brought significant results, as while in 1990 there were nearly 37,000 accidents involving personal injuries on the roads, in 2020 there were only 18,000 such accidents. However, in addition to these active and passive safety features, we need to be aware of and follow the written and unwritten rules of road safety. However, the number of passenger cars has increased so significantly in the last 20–25 years—but especially in the last two years due to the coronavirus epidemic—as roads are characterized by such a high degree of congestion that pedestrians and cyclists require much more attention from participants. This way it is important children receive proper education on the rules of walking or cycling at nursery school and preschool age. The aim of the study is to enumerate and present the platforms that help children to learn, know and deepen the rules of safe traffic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Impact of COVID-19 on traffic safety from the "Lockdown" to the "New Normal": A case study of Utah.

During the past several years, the COVID-19 pandemic has had pronounced impacts on traffic safety. Existing studies found that the crash frequency was reduced and the severity level was increased during the earlier "Lockdown" period. However, there is a lack of studies investigating its impacts on traffic safety during the later stage of the pandemic. To bridge such a gap, this study selects Salt Lake County, Utah as the study area and employs statistical methods to investigate whether the impact of COVID-19 on traffic safety differs among different stages. Negative binomial models and binary logit models were utilized to study the effects of the pandemic on the crash frequency and severity respectively while accounting for the exposure, environmental, and human factors. Welch's t-test and Pairwise t-test are employed to investigate the possible indirect effect of the pandemic by influencing other non-pandemic-related factors in the statistical models. The results show that the crash frequency is significantly less than that of the pre-pandemic during the whole course of the pandemic. However, it significantly increases during the later stage due to the relaxed restrictions. Crash severity levels were increased during the earlier pandemic due to the increased traffic speed, the prevalence of DUI, reduced use of seat belts, and increased presence of commercial vehicles. It reduced to a level comparable to the pre-pandemic later, owing to the reduction of speed and increased seat-belt-used to the pre-pandemic level. As for the incoming "New Normal" stage, stakeholders may need to take actions to deter DUI and reduce commercial-vehicle-related crashes to improve traffic safety.

Policy development of urban railway services sustainability in Indonesia: A multipol application

The daily traffic congestion faced by residents who live in the Greater Jakarta area has popularized the Jabodetabek Electric Train (KRL) as a mode of transportation for commuters to work and school. However, satisfactory service has not matched the increasing number of KRL users. Therefore, this study aims to develop a sustainability policy for urban rail services in Indonesia as an alternative strategy to overcome KRL service problems, such as overcapacity and inconvenience. The Multipol method is used to develop KRL service sustainability policies. Multipol is a multi-criteria decision-making method through the opinion of transportation experts. This study found that controlling the spread of COVID in the KRL is one of the priorities that must be implemented to ensure the continuity of the train. Then, the safety and security of the KRL are among the most critical policies determining the sustainability of urban railways in Indonesia. Therefore, safety and security can be improved by developing the competence of railway personnel through training, and protection, guaranteeing the rights of persons with disabilities and building safe and secure transfer spaces for onward journeys. The Ministry of Transportation and Indonesian commuter rail companies must improve supervision, assessment, and sanctions to meet service standards.

Analysis of Naturalistic Driving Events in Honolulu (Pre-COVID)

Dashboard cameras and sensors were installed in 233 taxi vans in Honolulu, Hawaii. They produced many hours of naturalistic driving data (NDD) between fall 2019 and spring 2020 in the form of 20 s recorded events. The study achieved its objectives to (1) collect data from naturalistic driving events where driving maneuvers caused acceleration or deceleration in any direction of 0.5g or higher, (2) develop a database suitable for statistical analysis, (3) derive basic statistics for all variables, and (4) investigate correlations between variables. The database included a total of 402 harsh events, of which were 398 near-crashes and 4 were crashes. Several variables such as road, environmental, driver, and vehicle characteristics were coded for each event. The installation of an NDD system by the taxi company proved to be a successful tool for coaching drivers, and for providing statistically significant insights into traffic safety factors relating to near-miss events, such as wider expressways come with a higher risk for near rear-end events;urban roads without parking lower the risk of near rear-end events;light traffic density significantly reduces the risk of rear-end events on freeways;and, mobile phone usage has a positive and significant coefficient that increases the risk of highway rear-end events. © ASCE.

Safe In and Out of the Car

Our cars make our everyday life much easier. With their help, in a day full of programs, we can get anywhere on time without carrying our packages on our own. In our rushing world, there is the probability that even if we have enough time to get there somewhere, we will hurry, which leads to inattention or worse case an accident. Car manufacturers have a huge amount of research projects to install driver-assistance safety electronics into our cars that, even if they are not driving, instead of the driver, alert to an accident and help to avoid a stutter or a life-threatening accident. According to the Hungarian Central Statistical Office (KSH), research on car manufacturers has brought significant results, as while in 1990 there were nearly 37,000 accidents involving personal injuries on the roads, in 2020 there were only 18,000 such accidents. However, in addition to these active and passive safety features, we need to be aware of and follow the written and unwritten rules of road safety. However, the number of passenger cars has increased so significantly in the last 20–25 years—but especially in the last two years due to the coronavirus epidemic—as roads are characterized by such a high degree of congestion that pedestrians and cyclists require much more attention from participants. This way it is important children receive proper education on the rules of walking or cycling at nursery school and preschool age. The aim of the study is to enumerate and present the platforms that help children to learn, know and deepen the rules of safe traffic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Safety Profile of Dupilumab Approved for Chronic Rhinosinusitis with Nasal Polyposis: Analysis from the European Spontaneous Adverse Event Reporting System: An International Journal of Medical Toxicology and Drug Experience

Introduction: Chronic rhinosinusitis with nasal polyposis (CRSwNP) is characterized by a type 2 pattern of inflammation resulting in the production of some cytokines such as interleukin (IL)-4, IL5, and IL13. Options for treatment-resistant CRSwNP include aspirin desensitization, recurrent topic and systemic corticosteroid use, and functional endoscopic sinus surgery (FESS). However, frequent relapses after medical and surgical treatment have been observed. Thus, dupilumab, a human recombinant monoclonal IgG4 antibody, changes radically the treatment of CRSwNP because of its binding effects on major drivers of human type 2 inflammatory processes [1-3]. Considering its recent approval, it may be useful to evaluate its safety profile. Objective: The aim of this study was to describe better adverse drug reactions (ADRs) related to dupilumab in the treatment of CRSwNP analyzing all individual case safety reports (ICSRs) collected into the European Spontaneous Reporting System (SRS) database. Methods: All ICSRs recorded starting from the drug approval up to 31 December 2021 with dupilumab reported as suspected and having the specific indication of CRSwNP were considered. A descriptive analysis was conducted to assess demographic characteristics and dupilumab-related variables. Results: Out of 10,400 ICSRs related to dupilumab, only 481 (4.6%) had CRSwNP indication, of which 68.2% were related to adults and 54.3% to females. The 68.4% were serious;however, ICSRs mainly led to a completely or partial recovering (25.4%) and 8 cases were fatal (1.7%). The time to onset (TTO) of ADRs was 25 (1-84.75) days while the time to resolution (TTR) was 5 (1.75-15.75) days. Analyzing ADRs by System Organ Classes (SOCs), the most reported were general and administration site conditions (36.4%) followed by injuries (21.6%), infections (21.2%), respiratory (19.1%), skin (16.6%), and nervous system disorders (16.4%). Looking at Preferred Terms (PTs), arthralgia (7.3%), eosinophilia (6.9%), COVID-19 (6.0%), pyrexia (5.8%), asthenia (5.6%), rash (5.4%), and dyspnoea (5.2%) were the most reported. The 7.5% of ICSRs described an aggravated condition with persistent nasal polyps: in 4 cases (0.8%) a nasal polypectomy was required. Considering fatal ICSRs, two cases were related to progression of COVID-19, one to road traffic accident, one to accidental death and the others were not fully specified. Conclusion: These results showed that dupilumab-related ICSRs are not commonly reported in CRSwNP. However, given the good treatment response and the minimal adverse effects observed, clinicians should consider treating CRSwNP with dupilumab. Moreover, additional analyses are necessary to better outline the safety profile of dupilumab in this particular setting.

Dimensioning of Cycle Lanes Based on the Assessment of Comfort for Cyclists

In a century where mobility is becoming more sustainable in terms of energy transition, emissions reduction, and a healthy quality of life, the use of bicycles is increasing and has many advantages over other modes of transport that have been underused. The bicycle is an excellent alternative for short distances of up to five kilometers. In combination with public transportation, it can also successfully compete with motorized transport for longer distances. For the adequate development of cycling, it is necessary to create the right conditions in terms of accessibility and road safety. This means planning appropriate cycling infrastructure where cyclists feel comfortable and safe, which can lead to additional increased use in bicycles for everyday trips. Comfort for cyclists is a concept supported by road safety, a pleasant environment, connectivity, and the attractiveness of cycling infrastructure. In other words, cyclists respond to the physical, psychological, and sociological aspects of the cycling experience that are also related to the cycling infrastructure and environment: where I am, what I see and perceive, and how I feel. This paper presents the concept of the level of service for cyclists (BLOS) as a unified method for defining the comfort of cyclists. This paper presents the method for determining the level of service or comfort for bicyclists as a function of road width, width of the cycling area, traffic volume, and the speed and structure of motorized traffic flow. The result of BLOS, the mathematical model used, is graphically presented and allows decision-makers and designers of cycling infrastructure to easily assess the suitability of cycling infrastructure. Different diagrams for different input data are presented in the paper.

Car careers: A socio-psychological evaluation of aspirational automobile ownership

There is a general consensus that private car ownership is a significant barrier to transport system change, specifically in regard to injuries, space, air pollutants, or greenhouse gas emissions. Observed changes in automobile characteristics also suggest that the system is becoming less sustainable, given trends towards larger cars with greater mass and horsepower. It is thus relevant to understand how the automobile system progresses. National statistics provide data on the technical side of car ownership, such as changes in vehicle specifics or national fleet size. This paper complements this view with a socio-psychological perspective on aspirational car owner-ship, i.e. the type of car people preferred to drive if given a free choice. Data is derived from an online panel (n = 1,211) representative of the German population, and also contains information on current car ownership, use, driving style, traffic behavior, attitudes towards traffic risks and safety measures, as well as political orientation. This allows for a discussion of driver segments in relation to the characteristics of cars, and hence to better understand the socio-psychological drivers of the development of the automobile system.

Driving Behavior and Its Correlation with COVID-19 Response Measures: A Neural Network Forecasting Analysis

The pandemic of COVID-19 has affected human patterns since December 2019. Since the very beginning, most countries imposed strict measures such as lockdowns and the suspension of all nonessential movements to reduce the spread of the pandemic. Therefore, mobility, road safety, and travel behavior were also significantly affected. At present, many studies tried to investigate travel or mobility behavior changes taking into account all possible transportation modes, but very few studies investigated driving behavior. This study aims to investigate driving behavior and its correlation with the strictness of COVID-19 response measures. Four neural network autoregression (NNAR) models with an external regressor were developed in order to forecast three different future stringency scenarios. NNAR models were employed as the forecasting performance was superior when comparing with statistical autoregressive integrated moving average (ARIMA) models. The NNAR models were developed using driving behavior-related variables (i.e., driving speed, speeding, speeding duration percentage, and mobile use percentage), derived from a smartphone application that has been developed by OSeven Telematics. The NNAR models were trained on 2020 data and three different scenarios were predicted for 2021 by providing three different constant stringency indices (i.e., 0, 55, 85). In particular, normal conditions without restrictions were simulated with zero stringency index, whereas moderate restrictions were simulated with 55 and finally, fully restrictions were simulated with 85. The NNAR modeling results showed that with higher stringency index, mobile use and driving speed tend to increase, whereas speeding duration demonstrates higher peaks. Interestingly, with stricter response measures, lower values were forecasted for speeding. Taking into account the modeling outcomes, there is a direct effect of the COVID-19 response measures on driving behavior. Nevertheless, a wider time frame for data collection as well as the use of more sophisticated techniques to control for the interrelationship between COVID-19 spread and driving behavior might be useful for future studies. [ FROM AUTHOR] Copyright of Journal of Transportation. Part A: Systems is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Design, Implementation and Experimental Investigation of a Pedestrian Street Crossing Assistance System Based on Visible Light Communications.

In urban areas, pedestrians are the road users category that is the most exposed to road accident fatalities. In this context, the present article proposes a totally new architecture, which aims to increase the safety of pedestrians on the crosswalk. The first component of the design is a pedestrian detection system, which identifies the user's presence in the region of the crosswalk and determines the future street crossing action possibility or the presence of a pedestrian engaged in street crossing. The second component of the system is the visible light communications part, which is used to transmit this information toward the approaching vehicles. The proposed architecture has been implemented at a regular scale and experimentally evaluated in outdoor conditions. The experimental results showed a 100% overall pedestrian detection rate. On the other hand, the VLC system showed a communication distance between 5 and 40 m when using a standard LED light crosswalk sign as a VLC emitter, while maintaining a bit error ratio between 10-7 and 10-5. These results demonstrate the fact that the VLC technology is now able to be used in real applications, making the transition from a high potential technology to a confirmed technology. As far as we know, this is the first article presenting such a pedestrian street crossing assistance system.

Road Safety Evaluation Framework for Accessing Park Green Space Using Active Travel

The COVID-19 pandemic has led to a burgeoning demand for active travel (walking or cycling), which is a healthy, pollution-free, and affordable daily transportation mode. Park green space (PGS), as an open natural landscape, have become a popular destination for active travel trips in metropolitan areas. Pedestrians and cyclists are often at high crash risk when exposed to complicated traffic environments in urban areas. Therefore, this study aims to propose a safety assessment framework for evaluating active travel traffic safety (ATTS) near PGS from the perspective of urban planning and exploring the effect of the point-of-interest (POI) aggregation phenomenon on ATTS. First, links between ATTS and the environment variables were investigated and integrated into the framework using the catastrophe model. Second, the relationship between the POI density and ATTS was investigated using three spatial regression models. Results in the Wuhan Metropolitan Area as a case study have shown that (1) the population density, road density, nighttime brightness, and vegetation situation near PGS have pronounced effects on ATTS;(2) pedestrians near PGS enjoy safer road facilities than cyclists. Active travel traffic near PGS requires more attention than non-park neighborhoods;(3) among four park categories, using active travel to access theme parks is the safest;and (4) SEM has the best fit for POI cluster research. Increases in leisure facility density and residence density may lead to deterioration and improvement in ATTS safety levels near PGSs, respectively. The safety framework can be applied in other regions because the selected environment indicators are common and accessible. The findings offer appropriate traffic planning strategies to improve the safety of active travel users when accessing PGS. Copyright © 2022 Luo, Liu, Xing, Wang and Rao.

Safety analytics at a granular level using a Gaussian process modulated renewal model: A case study of the COVID-19 pandemic.

With the advance of intelligent transportation system technologies, contributing factors to crashes can be obtained in real time. Analyzing these factors can be critical in improving traffic safety. Despite many crash models having been successfully developed for safety analytics, most models associate crash observations and contributing factors at the aggregate level, resulting in potential information loss. This study proposes an efficient Gaussian process modulated renewal process model for safety analytics that does not suffer from information loss due to data aggregations. The proposed model can infer crash intensities in the continuous-time dimension so that they can be better associated with contributing factors that change over time. Moreover, the model can infer non-homogeneous intensities by relaxing the independent and identically distributed (i.i.d.) exponential assumption of the crash intervals. To demonstrate the validity and advantages of this proposed model, an empirical study examining the impacts of the COVID-19 pandemic on traffic safety at six interstate highway sections is performed. The accuracy of our proposed renewal model is verified by comparing the areas under the curve (AUC) of the inferred crash intensity function with the actual crash counts. Residual box plot shows that our proposed models have lower biases and variances compared with Poisson and Negative binomial models. Counterfactual crash intensities are then predicted conditioned on exogenous variables at the crash time. Time-varying safety impacts such as bimodal, unimodal, and parabolic patterns are observed at the selected highways. The case study shows the proposed model enables safety analytics at a granular level and provides a more detailed insight into the time-varying safety risk in a changing environment.

Application of Logistic Regression Model to Assess the Impact of Smartwatch on Improving Road Traffic Safety: A Driving Simulator Study

Speeding is one of the most relevant risk behaviours for serious and fatal road traffic accidents, particularly among young drivers, being the cause of approximately every third road traffic accident. Due to this background, many road traffic safety campaigns are aimed at reducing speeding among young drivers. However, the effects of campaigns aimed at complying with speed limits for young drivers have significantly fewer effects than other campaigns. For these reasons, an experimental study was conducted to examine how young drivers react to the speeding campaign, which was shown to them on a smartwatch while driving in a driving simulator. Speeding results were compared for three scenarios: no campaign, a billboard campaign and a smartwatch campaign. The experiment involved 102 participants with an average age of 21 years. The results showed that participants were six times more likely to comply with the speed limit if a campaign was shown on a smartwatch than when shown on billboards.

Bus Predictive-Control Method considering the Impact of Traffic Lights

Amid the COVID-19 pandemic, many travelers have switched from public transit to other modes. How to maintain the stability and service quality of the bus system under regular pandemic prevention and control, so as to maintain the attractiveness of the bus, is an important research direction. Predicting operation states and adopting appropriate control measures for running buses are effective means of improving the bus system's schedule reliability and service quality. Focusing on the impacts of intersection traffic lights on the link's travel time durations, we establish a probabilistic prediction model for bus headways, classifying the bus headways into three states: bunching, stable, and big gap states. Based on the prediction of bus headways, the most suitable control strategy is selected by the proposed method from the plan set, such as holding control, speed-adjusting control, and stop-skipping control to minimize the bus headway deviation. Simulation experiments were employed to verify the effectiveness of the proposed method. Compared with the no-control situation, the expected headway variation, average passenger waiting time, and bus bunching frequency for 100 simulations by the proposed method are reduced by 77.73%, 41.66%, and 87.11%, respectively. Compared with some control methods without prediction, the proposed method is more robust, maintains good control performance, and reduces bus bunching despite significant variations in environmental parameters. In addition, the model still performs well when considering the execution errors of bus drivers. [ FROM AUTHOR] Copyright of Journal of Advanced Transportation is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Attention profile of physically recovered COVID-19 inpatients on the day of discharge.

Few studies have reported specific attention deficits in post-COVID-19 patients. Attention consists of different subdomains. Disruptions to specific attention subdomains might impair a wide range of everyday tasks, including road safety. As there are millions of COVID-19 patients with different socio-economic backgrounds, screening of attentional performance less dependent on education is needed. Here, we verified if physically recovered COVID-19 inpatients showed specific attention decrements at discharge. The Continuous Visual Attention Test (CVAT) is a Go/No-go task which is independent of participants' schooling. It detects visuomotor reaction time (RT = intrinsic alertness), variability of reaction time (VRT = sustained attention), omission (focused-attention), and commission errors (response-inhibition). Thirty physically functional COVID-19 inpatients at discharge and 30 non-infected controls underwent the CVAT. A MANCOVA was performed to examine differences between controls and patients, followed by post-hoc ANCOVAs. Then, we identified the percentile score for each patient within the distribution of the CVAT performance of 211 subjects mentally capable of driving (reference group). COVID-19 patients at discharge showed greater RT and VRT, and more omission errors than controls. Twenty-two patients (73%) had performance below the 5th percentile of the reference group in one or more subdomains. As slow visuomotor RT, deficits in focusing and difficulties in keeping visual attention are associated with traffic accidents, we concluded that most COVID-19 patients at discharge had deficits that may increase the risk of road injuries. As these deficits will probably affect other daily activities, a routine assessment with the CVAT could provide useful information on whom to send to post-COVID centers.