Bhaven Naik

Distracted driving remains a major concern on highways, with it contributing to severe and fatal crashes, particularly on high-speed routes, prompting numerous states to implement targeted initiatives aimed at combating traffic violations that significantly contribute to fatal and injury-inducing crashes. Among these initiatives is the highway safety corridor program, a collaborative endeavor between the state departments of transportation and law enforcement agencies. Highway safety corridors employ a combination of engineering interventions and heightened law enforcement presence to address risky driver behavior and mitigate the occurrence of crashes. Despite the longstanding existence of safety corridors, research on their effectiveness remains relatively limited, with existing studies indicating only moderate success rates. This study is dedicated to evaluating the effectiveness of ten highway safety corridors in Ohio, where the state recently launched its inaugural highway safety corridor program targeting distracted driving. Utilizing 2023 crash data, this Empirical Bayes’ before-and-after study seeks to gauge the impact of these safety corridors on enhancing roadway transportation safety. Upon assessing all crash types within Ohio’s distracted driving safety corridors that provided sufficient data for a before–after study, it was determined that the adoption of safety corridors generally led to a reduction in crashes ranging from 2% to 49%. The significance and magnitude of crash reduction may vary if specific crash types or severity levels are considered.

With the availability of different data sources on freeways and arterials, travel-related information along with traffic conditions can be collec |

Identifying speed variability patterns is an essential task for transportation modeling, especially within increasing traffic demand and limited |

Road managers require convenient, inexpensive methods to quickly assess pavement conditions over large areas. New imaging technologies potentially offer a substantial improvement over current methods. In this study, two hand-portable methods based on widely available consumer-grade technology were tested across a range of pavement conditions. To place the proposed methods in a familiar context, data were compared with the mean texture depth (MTD) calculated by the widely used volumetric method. MTD provided the clearest distinction between experimental roughness classes. Spatial pattern analysis (fractal dimension) of digital images discriminated between light, moderate and severe deterioration but failed to make fine distinctions between degrees of moderate wear. Three-dimensional models constructed by stereoscopic infrared scanning distinguished between all but the smoothest texture classes. It appears that both the proposed methods have potential for accurate, quick and convenient assessment of pavement macrotexture at little expense, although some judgement must be used in their application.

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.