Analytical modeling of bus travel time parameters on urban route segments under the conditions of dedicated lane implementation

Abstract. Problem. Modern urban public transport systems face the challenge of ensuring schedule adherence and improving the efficiency of bus operations, particularly under conditions of variable traffic and complex infrastructure. A key issue remains the insufficient accuracy of forecasting bus travel time on individual route segments, even with the implementation of dedicated lanes. This necessitates the development of analytical tools that take into account the impact of both external and organizational factors on bus speed patterns. Goal. The objective of this study is to develop a set of analytical models for determining the temporal parameters of bus movement on segments of urban routes, considering the features of dedicated public transport lanes and characteristic traffic patterns. Methodology. The study is based on field observations of bus movement on the route, using the mobile application GalileoGPS Speedometer. A detailed analysis of changes in speed was conducted, leading to the identification of typical operating conditions on route segments. The conditions were classified into 6 levels of movement convenience, reflecting the interaction between the bus and the surrounding traffic environment. Based on the data collected, analytical dependencies were formulated to describe the travel time under varying conditions. Results. The developed analytical models account for speed variability and movement convenience levels, enabling precise modeling of bus travel times on different route segments. The models consider both delays and schedule advancements. Six typical interaction scenarios between buses and the traffic environment were identified, allowing for accurate predictions of speed changes and arrival times at stops. Originality. The scientific novelty of the study lies in the systematic and analytical description of bus movement regimes with a focus on dedicated lane operation. A new approach is proposed for classifying bus movement convenience levels based on objective environmental parameters, enhancing the accuracy of arrival time prediction and enabling the development of adaptive schedules. Practical value. The proposed models can be integrated into intelligent transportation systems to improve timetable accuracy, facilitate the creation of adaptive schedules, and optimize route planning. Their implementation enhances the reliability and stability of public transport operations, which is particularly relevant for large cities with high mobility demands.