Wenzhe Sun

Bus bunching is a well-known phenomenon on many bus routes where an initial delay to one service can disturb the whole schedule due to resulting differences in dwell times of subsequent buses at stops. This paper deals with the passenger behaviour when there is more than one bus serving the stop, focusing on their choices and possible switching actions from the queue of the bus they are waiting to board. A parameter γ is introduced to denote the percentage of passengers boarding the front bus of

This paper employs regression with ARIMA errors (RegARIMA) to quantify the impacts of multiple non-pharmaceutical interventions, daily new cases, seasonal and calendar effects, and other factors on activity trends across the timeline of the ongoing COVID-19 pandemic in Japan. The discussion focuses on two controversial policy sets imposed by the Japanese government that aim to contain the pandemic and to stimulate the recovery of the economy. The containing effect was achieved by stay-at-home re

The mobility of sizable trucks is often limited by their large size. They thus may have additional requirements on road types, road widths, and the turning radius at the intersection when traveling. Therefore, this study explores the unique needs and preferences of large truck drivers’ route choice with a focus on trip and road network characteristics. GPS trajectory data from the central Kansai area of Japan with numerous ports and freight terminals are used. Trajectories are considered having

Bus bunching resulting from initially small headway irregularities is a widely-known and studied problem. A variety of headway-prediction approaches, as well as corrective strategies, have been developed to identify and correct headway irregularity in real time. Instead of predicting an exact value for future headways, this study explores a probabilistic predictive methodology to forecast whether or not a bus will be bunched during its dwelling at a downstream stop, using a logistic regression m

This chapter discusses the various means of obtaining demand estimates for public transport planning. It starts by discussing the relevant models for obtaining a general knowledge on the network-level demand before the service starts operation. This is followed by consideration of demand estimation for existing services, focusing on the potential emerging from massive passive public transport (PT) data. Distinctive detailed levels of demand information (stop flows, leg-Origin Destination (OD) fl

Bus bunching is a well-known phenomenon on many bus routes where an initial delay to one service can disturb the whole schedule due to resulting differences in dwell times of subsequent buses at stops. This paper deals with the passenger behaviour when there is more than one bus serving the stop, focusing on their choices and possible switching actions from the queue of the bus they are waiting to board. A parameter γ is introduced to denote the percentage of passengers boarding the front bus of