Large Language Models (LLMs), based on their highly developed ability to comprehend and
generate human-like text, promise to revolutionize all aspects of society. These LLMs …

Building a multimode transportation system could effectively reduce traffic congestion and
improve travel quality. In many cities, use of public transport and green travel modes is …

Thailand's collaboration with China to develop High-Speed Rail (HSR) represents a crucial
step in enhancing transportation infrastructure and promoting regional economic growth …

Using survey data from three dwelling types in Jakarta, we examine how dwelling type,
socioeconomic identity, and commuting distance affect women's travel-mode choices and …

Artificial Intelligence (AI) and machine learning have been increasingly adopted for travel
demand forecasting. The AI-based travel demand forecasting models, though generate …

Customized bus is considered an effective means to alleviate traffic congestion and reduce
traffic-related environmental pollution caused by the increasing number of private cars …

Overfitting poses a significant limitation in mode choice prediction using classification
models, often worsened by the proliferation of features from encoding categorical variables …

Travel survey data has long been one of the fundamental sources for travel mode choice
behavior analysis. It can provide a wealth of travel-related information and detailed …

Demand for sustainable mobility is particularly high in urban areas. Hence, there is a
growing need to predict when people will decide to use different travel modes with an …

Accurate classification of mode choice datasets is crucial for transportation planning and
decision-making processes. However, conventional classification models often struggle to …