Predicting Short-term Bus Ridership with Trip Planner Data: A Machine Learning Approach

To address the increasing passenger demand in the coming years and make public transport less crowded and delayed, insights into predicted passenger flow are needed. A wide range of studies has used and validated that smart card data can be one of the sound bases for predicting short-term passenger demand. However, it also has several...

Bus ridership prediction: Development of a framework

During tenders in public transport, the bus network is reconsidered and adjusted. An accurate prediction of the effect on ridership is required. Due to the tender environment, time and input data are limited. This research focuses on deriving a relation between level-of-service (LOS) and ridership, and implementing this in a model suitable for...