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Travel mode choice (TMC) prediction, improving health parameters, and promoting sustainable transportation systems are crucial for urban planners and policymakers. Past studies show the influence of health on activities, while several studies use multitasking activities and physical activity intensity to study the association between time use and activity travel participation (TU and ATP) and health outcomes. Limited studies have been conducted on the use of transport modes as intermediate variables to study the influence of TU and ATP on health parameters. Therefore, the current study aims to evaluate urban dependency on different transport modes used for daily activities and its influence on health parameters to promote a greener and healthier society and a sustainable transportation system. Pearson's Chi-squared test was used for transport mode classification, and multinominal logit models were used for regression using R programming. A total of five models were developed for motorized, non-motorized, public transport, physical, and social health to study the correlation between transport modes and health parameters. The statistical analysis results show that socio-demographic and economic variables have a strong association with TMC in which younger, male, workers and high-income households are more dependent on motorized transport. It was found that a unit rise in high-income causes a 4.5% positive increase in motorized transport, whereas it negatively influences non-motorized and public transport by 4.2% and 2.2%, respectively. These insights might be useful for formulating realistic plans to encourage individuals to use active transport that will promote sustainable transportation systems and a healthier society. [ABSTRACT FROM AUTHOR]

Injury as a result of road traffic accidents (RTA) is one of the leading causes of death and disability-adjusted life years. Strategies to handle this major public health problem, which has significant consequences for the Saudi economy and families, have been underway for many years but with very little success. This study's main aim is to determine respondents' perceptions of traffic safety and the factors that lead to road traffic accidents. It is a cross-sectional study conducted on randomly selected university students, faculty drivers, and visitors using King Saud University's parking facility. Data were collected from 381 drivers using a pretested questionnaire, which comprises questions intended to attain the study's objectives. The critical factors affecting traffic safety are public information followed by road maintenance, Garage, vehicle inspection, Road design and equipment, Training of drivers, Sanctions and Police enforcement, Protective devices and vehicle design, and post-accidental care. Road traffic accidents were found to be 39.0% with respondents aged less than 20 years, followed by ages between 20-35 years, which was 34.8%, and only 2.4% above 50 years. The most frequent occurrence of road traffic accidents was angle collision (39.0%) and back collision (18.9%), followed by hitting a fixed object (17.7%). Distraction habits during driving include cell phone usage (56.7%), followed by smoking (24.4%), and eating and drinking (18.9%) while driving. The most common traffic violations were increased speed limit (48.1) and loss of driving license (11.8%). The most common injuries were head (39.0%) and limbs (22.0%). A significant association between drivers' age during the accident and distraction habits has been found (p < 0.000). The study demonstrated that drinking/eating, cell phone use, and violation of traffic rules are significant reasons for RTA. The findings of this study will contribute to a more comprehensive knowledge of road traffic accidents for the formation of effective strategies and evidence-based policies for the prevention of accidents. [ABSTRACT FROM AUTHOR]

This paper presents a simulation-driven method for assessing the safety and efficiency of traffic at roundabouts incorporating connected and automated vehicle (CAV) technology. Utilizing the newly proposed CAV-based factors specified by the Highway Capacity Manual (HCM) provided a practical framework for analyzing capacity dynamics across various traffic scenarios. Using microscopic traffic simulation on a roundabout model replicating real-world geometry and traffic attributes facilitated the identification of crucial behavioral parameters. This simulation spanned from smooth traffic scenarios to operational saturation, aiding in the study of mixed traffic scenarios during the transition to increasing CAV presence. Additionally, the study assessed the safety and traffic impact of a dedicated CAV lane using surrogate safety metrics. Aimsun software aided in model parameter calibration, which, combined with the Surrogate Safety Assessment Model (SSAM), supported safety analysis. Despite observed enhancements in roundabout performance with CAV integration, the benefits of a designated CAV lane highlighted the potential to reduce conflicts among vehicles. In conclusion, the paper emphasizes the overall performance enhancement achieved with CAVs at roundabouts while also providing insights for evaluating the potential of CAV technologies in future mobility management strategies. [ABSTRACT FROM AUTHOR]

The correlation between mobility and subjective well-being (SWB) has received much attention lately. Previous researchers have studied the effect of health parameters or SWB on transport mode; however, there is a lack of study on the influence of travel mode choice (TMC) for daily activities on SWB. Besides, the prediction of TMC is critical for transport planning. Therefore, the current study aims to study the TMC and its influence on overall SWB. Data from 732 individuals and 191 households are collected using random sampling techniques, which represents 0.029% of the total population. Statistical Package for Social Sciences (SPSS) was used for descriptive statistics, whereas R software was used for the multilevel linear regression analysis. The model estimation results show a significant correlation among the variables (p < 0.05, R2 > 0.20). Besides, those who are exposed to public transport and tend to use nonmotorized transport modes engage in more physical activities than those who use a private vehicle, which has a negative impact on SWB. The outcome of current research helps policymakers build policies to achieve a sustainable transportation system. [ABSTRACT FROM AUTHOR]