This study presents an empirical investigation of the impacts of real-time weather conditions on the freeway crash severity. A Bayesian spatial generalized ordered logit model was developed for modeling the crash severity using the hourly wind speed, air temperature, precipitation, visibility, and humidity, as well as other observed factors. A total of 1424 crash records from Kaiyang Freeway, China in 2014 and 2015 were collected for the investigation. The proposed model can simultaneously accommodate the ordered nature in severity levels and spatial correlation across adjacent crashes. Its strength is demonstrated by the existence of significant spatial correlation and its better model fit and more reasonable estimation results than the counterparts of a generalized ordered logit model. The estimation results show that an increase in the precipitation is associated with decreases in the probabilities of light and severe crashes, and an increase in the probability of medium crashes. Additionally, driver type, vehicle type, vehicle registered province, crash time, crash type, response time of emergency medical service, and horizontal curvature and vertical grade of the crash location, were also found to have significant effects on the crash severity. To alleviate the severity levels of crashes on rainy days, some engineering countermeasures are suggested, in addition to the implemented strategies.

https://www.mdpi.com/1660-4601/17/8/2768/pdf

Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis.

Investigation of clusters and injuries in pedestrian crashes using GIS in Changsha, China

This study aims to investigate the relationships between COVID-19-related psychological distress, social media addiction, COVID-19-related burnout, and depression. The research, which was designed according to the relational survey model, was conducted with the participation of 332 school principals and teachers who received graduate education in the field of educational administration. Research data were collected through online surveys and then structural equation modeling (SEM) was used to test and analyze the proposed hypotheses. The study’s findings revealed that COVID-19-related psychological distress strongly predicted COVID-19-related burnout. In this context, as the psychological distress associated with COVID-19 increased, the sense of burnout associated with COVID-19 also increased. However, it was found that burnout associated with COVID-19 significantly and positively predicted depression. SEM results revealed that COVID-19-related psychological distress directly affected COVID-19-related burnout, depression, and social media addiction. In addition, it was determined that an indirect effect of COVID-19-related burnout and social media addiction exists in the relationship between COVID-19-related psychological distress and depression.

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Examining the Associations between COVID-19-Related Psychological Distress, Social Media Addiction, COVID-19-Related Burnout, and Depression among School Principals and Teachers through Structural Equation Modeling

Transient aerodynamic performance of high-speed trains when passing through an infrastructure consisting of tunnel–bridge–tunnel under crosswind

Abstract The description of the aerodynamic cross-wind effect that occurs on a long vehicle, when it crosses the wake of a bridge tower will be analyzed both considering and neglecting the adoption of wind barriers close to tower. Wind tunnel tests are used to measure the aerodynamic loads and the surface pressure distribution on a 1:40 scale model. The presence of wind shielding near the tower produces an unexpected change in the sign of the lateral force and of the overturning moment. A description of the aerodynamic phenomenon is proposed relying on the measured force and pressure data, and on flow visualization.

Cross wind effects on a vehicle crossing the wake of a bridge pylon

Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study

Low-level wind effects on the glide paths of the North Runway of HKIA: A wind tunnel study

Wind tunnel testing of the effect of terrain on the wind characteristics of airport glide paths

Walking is a sustainable mode of transport which has well established health and environmental benefits. Unfortunately, hundreds of thousands of pedestrians lose their lives each year over the world due to involvement in road traffic crashes, and mid-blocks witness a significant portion of pedestrian fatalities. This study examined the direct and indirect effects of various contributing factors on the pedestrian injury severity in vehicle-pedestrian crashes at mid-blocks. Data of vehicle-pedestrian crashes during 2002-2009 were extracted from the NASS-GES, with pre-crash behaviors and injury severity included. The SEM path analysis method was applied to uncover the inter-relationships between the pedestrian injury severity and various explanatory variables. Both the direct and indirect effects of these explanatory variables on the pedestrian injury severity were calculated based on the marginal effects in the multinomial and ordered logit models. The results indicate some variables including number of road lanes and the age of pedestrian have indirect impacts on the injury severity through influencing the pre-crash behaviors. Although most indirect effects are relatively small compared with the direct effects, the results in this study still provide some valuable information to improve the overall understanding of pedestrian injury severity at mid-blocks.

https://www.mdpi.com/1660-4601/17/17/6170/pdf

Examining Injury Severity of Pedestrians in Vehicle-Pedestrian Crashes at Mid-Blocks Using Path Analysis

The COVID-19 epidemic has had a major impact on people's normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic prevention and control. In this paper, a dynamic programming model based on nonlinear integer programming (NIP) is established to study the problem of boarding and alighting planning at various CB stops under the influence of COVID-19. Using Gurobi 9.1.1 solver, the optimal plan for passengers boarding and deboarding CB buses could be obtained. Besides, the mathematical model established in this paper can obtain the minimum value of the total number of contacts between passengers during travel under different CB numbers. It is found that the model solution results eventually form a Pareto frontier. When the number of CB buses increases, the total number of contacts between passengers will decrease This study has positive significance for ensuring the normal travel of passengers during the COVID-19 epidemic, and provides useful references for the studies about the planning of the customized bus.

Haorong Peng

Papers

Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study

Low-level wind effects on the glide paths of the North Runway of HKIA: A wind tunnel study

Wind tunnel testing of the effect of terrain on the wind characteristics of airport glide paths

Examining Injury Severity of Pedestrians in Vehicle-Pedestrian Crashes at Mid-Blocks Using Path Analysis

Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19