Countries that are still developing experience significant disparities in access to railway services, as these nations also grapple with societal inequality issues that remain unaddressed. In developed countries, railway transportation systems serve as the primary mode of transportation for both passengers and goods. However, in recent years, studies on disparities in developed countries have increased, while literature concerning developing countries remains scarce. Therefore, this study takes place in Thailand, a developing country facing significant population disparities. The objective is to examine factors contributing to these disparities in access to railway transportation systems across cities, using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to identify user disparities. The sample group comprises 1,252 randomly selected railway users from various regions in Thailand, obtained through Stratified Random Sampling. The results reveal seven dimensions of disparities: cultural, spatial, societal, political, knowledge-based, economic, and environmental. The CFA results also highlight cultural disparities as a significant factor in explaining access disparities among railway users. These findings can inform relevant organizations, aiding them in better understanding the actual needs of railway users and aligning railway development plans accordingly. Ultimately, this contributes to policy development aimed at reducing access disparities and fostering a more equitable society. Doi: 10.28991/CEJ-2024-010-03-01 Full Text: PDF

This study focused on pre-flood measures to estimate evacuation times impacted by flood depths and identify alternate routes to reduce loss of life and manage evacuation measures during flood disasters. Evacuation measures, including traffic characteristics, were reviewed according to different flood depths. Several scenarios were constructed for different flooding situations and traffic volumes. Evacuation times in the study area were evaluated and compared for all scenarios with reference to dry conditions. Results of network performance indicators compared to the dry situation showed that average speed dropped to 2 km/h, VHT rose above 200%, and VKT rose above 30%. Cumulative evacuee arrival percentage increased when flood levels were higher than 5 cm. Flood levels of 10–15, 15–20, 20–25, and 25–30 cm represented percentages of remaining evacuees at 9%, 19%, 49%, and 83%, respectively. Time taken to evacuate increased according to flood level. For flood depths of 5–30 cm, travel time increased by 40, 90, 260, and 670 min, respectively, suggesting the need for early evacuation before the flood situation becomes serious.

Ensuring that people from all regions in a country can easily access railway stations is a crucial objective in the development of transportation and mobility systems and is essential for the convenient travel within the country. Furthermore, accurately assessing accessibility in disadvantaged areas is pivotal in designing and implementing development policies for equitable and sustainable transportation systems. Although various methods and tools are available for measuring accessibility, interpreting local-level data remains challenging. This study was conducted in Thailand, a country with severe accessibility disparities but undergoing considerable development. Therefore, the objective of this study was to evaluate accessibility disparities to analyze accessibility capabilities and inequality of railway stations. The objective of the study was to aid the development of inequality and railway services to cover all areas. The geographic information system methodology with network analysis tools was used to visualize and analyze spatial accessibility data and identify regional disparities. The results of this study indicate inequality in accessing railway services, which revealed that densely populated areas have superior access to railway stations compared with districts with a lower population density. Additionally, over 41% of the study area’s population resides more than half an hour away from access to a railway station. This study highlights regional inequality in accessing railway station services. Furthermore, strategies to alleviate this inequality are presented, and the findings will aid government agencies and railway planners in designing critical strategies or formulating policies for improving accessibility to rail transportation systems and reducing inequality in accessing railway services.

Despite the considerable efforts to address traffic crashes, overspeeding in industrial zones remains a primary cause in Thailand. In order to effectively against this challenge (overspeeding), the deep-rooted factors influencing speeding behaviors, particularly drivers’ risky behaviors, must be understood. Thus, this study employs the theory of planned behavior (TPB) and the framework comprising three basic Es (Education, Engineering, and Enforcement) and additional Es (Emergency response), i.e., the 3Es + Es framework, to examine these deep-rooted factors while considering the riders’ sociodemographic data. Additionally, we performed structural equation modeling to investigate the factors influencing speeding behaviors, with key findings revealing that Engineering factors significantly account for overspeeding. Conversely, we revealed that attitude, subjective norm, and perceived behavioral control (which are essential TPB components) significantly influence riders’ intentions to exhibit safe behavior, resulting in reduced speeding. Additionally, our examination of latent factors based on riders’ sociodemographic data revealed that age, marital status, income, riding experience, crash history, and traffic tickets are significant factors that determine speeding habits. Specifically, we observed that single riders and those with less than five years of riding experience were less likely to exhibit safe riding behaviors. Overall, our findings would benefit Thailand’s road-safety authorities, as we specifically proposed appropriate policies and empirical guidelines for Thailand’s industrial zones, which are prone to high crash rates. This could effectively reduce speeding among motorcycle riders and mitigate traffic crashes.

Bangkok, Thailand is prone to flooding after heavy rain. Many road sections become impassable, causing severe traffic congestion and greatly impacting activities. Optimal vehicle management requires the knowledge of flooding impact on road traffic conditions in specific areas. A method is proposed to quantify urban flood situations by expressing traffic conditions in specific ranges using the concept of macroscopic fundamental diagram (MFD). MFD-based judgement allows for a road manager to understand the current traffic situation and take appropriate traffic control measures. MFD analysis identified traffic flow–density and density–velocity relationships by using the shape of the estimated MFD travel time-series plots. Then, results were applied to develop a traffic model with vehicle-flow parameters as a measuring method for road-network performance. The developed model improved road-network traffic-flow performance under different flood conditions. A method is also presented for traffic management evaluation on the assumption that flooding occurs.

This study aimed to identify and compare the risk factors associated with motorcycle crash severity during both daytime and nighttime, for single and multivehicle incidents in Thailand using 2021–2024 data. The research employed the XGBoost (Extreme Gradient Boosting) method for statistical analysis and extensively examined the temporal instability of risk factors. The results highlight the importance of features impacting the injury severity of roadway collisions across various conditions. For single motorcycle crashes, the key risk factors included speeding, early morning incidents, off-road events, and long holidays. In multivehicle crashes, rear-end collisions, interactions with large vehicles, and collisions involving other motorcycles or passenger cars were linked to increased injury severity. The findings indicate that the important factors associated with motorcyclist injury severity in roadway crashes vary depending on the type of crash and time of day. These insights are valuable for policymakers and relevant authorities in developing targeted interventions to enhance road safety and mitigate the incidence of severe and fatal motorcycle crashes.