Impact of external factors on bus speed profile: insights from continuous GPS data analysis

Operational speed plays a crucial role in transportation analysis, influencing decisions in planning, infrastructure design, and traffic management. To achieve a comprehensive understanding of operational speed profiles, consideration of static, dynamic, and external factors is essential. In this study, we leverage continuous GPS data from buses, integrating vehicle type characteristics, road features, traffic volumes, and meteorological data. More than 35,000 observations were used in two Ordinary Least Square (OLS) models to address three key questions: (a) how does passenger weight influence the speed profile? (b) how traffic volumes influence the speed profile? (c) how do different weather conditions affect the speed profile? for low-speed or high-speed roads. Results show that higher load on the vehicles, larger traffic volumes on the roads and snowfalls on high-speed roads, significantly reduced the operational speed. In addition, the results demonstrate the importance of considering multiple predictors to accurately estimate speed dynamics. These findings highlight the need of a multivariate approach to account for the nuanced interactions between factors. By incorporating these insights, transportation planners can make informed decisions to enhance the efficiency, safety, and sustainability of transportation systems.