With the promotion of ChatGPT to the public, Large language models indeed showcase
remarkable common sense, reasoning, and planning skills, frequently providing insightful …

In the field of transportation, data analysis is probably the most important and widely used
research tool available. In the data analysis universe, there are two 'schools of thought'; the …

Most literature on short-term traffic flow forecasting focused mainly on normal, or non-
incident, conditions and, hence, limited their applicability when traffic flow forecasting is most …

Urban traffic congestion is one of the most severe problems of everyday life in Metropolitan
areas. In an effort to deal with this problem, intelligent transportation systems (ITS) …

Real-time and accurate short-term traffic flow prediction results can provide real-time and
effective information for traffic information systems. Based on classic car-following models …

Wireless sensor networks (WSNs) offer the potential to significantly improve the efficiency of
existing transportation systems. Currently, collecting traffic data for traffic planning and …

Methods are described for identifying events that would be considered Surprising by people
and identifying how and when to transmit information to a user about situations that they …

In this paper, the number of goods subject to inspection at European Border Inspections
Post are predicted using a hybrid two-step procedure. A hybridization methodology based …

Time series analysis has been used extensively in transport research in various areas, such
as traffic management and transport planning. Time-series data may contain temporal and …

Natural language processing (NLP) is a key component of intelligent transportation systems
(ITS), but it faces many challenges in the transportation domain, such as domain-specific …