Principles and Practice of Structural Equation Modeling (2nd ed.)

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Distracted driving has been considered one of the main reasons for traffic crashes in recent times, especially among young drivers The objectives of this study were to identify the distracting activities in which young drivers engage, assess the most distracting ones based on their experiences, and investigate the factors that might increase crash risk The data were collected through a self-report questionnaire Most participants reported frequent cell phone use while driving Other reported activities include adjusting audio devices, chatting with passengers, smoking, eating, and drinking A structural equation model was constructed to identify the latent variables that have a significant influence on crash risk The analysis showed that in-vehicle distractions had a high effect on the crash likelihood The results also indicated that dangerous driving behavior had a direct effect on the crash risk probability, as well as on the rash driving latent variables The results provide insight into distracted driving behavior among young drivers and can be useful in developing enforcement and educational strategies to reduce this type of behavior

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Investigating in-vehicle distracting activities and crash risks for young drivers using structural equation modeling.

Measuring users’ satisfaction of the road network using structural equation modeling

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 study investigated factors affecting the severity of red-light-running (RLR) -related crashes by means of crash records from the State of Florida (US). Previous studies have attempted to incorp...

Severity analysis of red-light-running-related crashes using structural equation modeling

Each year, thousands of wildlife–vehicle crashes (WVCs) occur in North America with negative effects on wildlife welfare, human health, and the economy. Although previous studies have investigated ...

Iman Gharraie

Papers

Severity analysis of red-light-running-related crashes using structural equation modeling

Severity Analysis of Wildlife–Vehicle Crashes using Generalized Structural Equation Modeling: