This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.

The present study analyzed the extant literature about the phenomenon of human trafficking in Indonesia. The Scope Analysis examined scholarly journals and publications from 2012 to 2020. We obtained databases from internationally recognized journals such as Scopus and Web of Science. We restricted the time frame based on the available evidence at that moment. The methodology employed in this study involved the identification, collection, and organization of peer evaluations that were published with pertinent details or by delineating the fundamental concepts that constitute the domain of a research investigation concerning chronology, location (nation or setting), source (literature review), and provenance. The findings of the analysis indicated the existence of articles that delved into the circumstances and current state of persons who fell victim to human trafficking, specifically from Indonesia to different regions throughout the globe. The analysis approach was utilized in this study, following the methodological parameters outlined by Arksey and O’Malley in 2005. Moreover, it is anticipated that the Scoping Analysis will generate policy recommendations for policymakers, practitioners, and researchers seeking to combat and address the illicit trafficking of individuals in Indonesia.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

This study examines the spatial distribution and structure of traffic offences in the Northern Great Plain region. The research is unique in that it examines a specific area through the lens of geography. The research shows and demonstrates that the research area of crime and transport geography is much broader than previous researches has shown. At the beginning of the study, the authors clarified the conceptual framework, as the terms “violation” and “offence” are often confused even in technical materials. The research shows which routes are the most frequently used by road hauliers in the regions under study and what type of checks have been carried out on these routes by the Transport Authorities of the Government Offices. The type of administrative penalty detected and the nationality breakdown of the infringements are described. The study typifies the infringements involving administrative fines by nationality category.

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.