An evaluation of passenger delay-based refund schemes in urban public transportation

In this thesis, the functioning of passenger delay-based refund schemes in urban public transportation settings is evaluated, such as metros or light-rails. These are used when a passenger encounters a delay on their trip, in order to grant a form of refund to them. To the best of knowledge, no research has been carried out yet on several...

Evaluating and modifying a public transport network to achieve an equitable distribution of accessibility: A comparison of accessibility distribution principles in Amstelland-Meerlanden

The provision of good accessibility is the main function of a well-functioning public transport (PT) system, the quality of which affects the ability of people to access basic needs such as employment, education, and healthcare. It is therefore important that PT accessibility is distributed in an equitable, or fair, manner. This thesis evaluates...

Assessing Moving Block Railway Capacity Based on Fixed Block Infrastructure Occupation

Moving block signalling promises a significant reduction of the infrastructure occupation compared to a fixed block system, such as NS’54/ATB. This is mainly caused by a strong reduction of the approach and running time. However, to assess the capacity gains track occupation data, such as blocking times are needed. ETCS L3 Moving Block is still...

Predicting Truck Cycle Time in Earthworks Using a Machine Learning Approach

Inaccurate truck cycle time (TCT) prediction in earthworks impacts construction projects because more equipment and human resources must be added to complete the project. It also increases fuel consumption and emissions from the machinery. However, the current method gives inaccurate prediction because of subjectivity and human error. <br/>This...

Short-Term Traffic Forecasting on Highways Using Neural Networks: A Congestion Pattern-Based Assessment

As traffic demands are ever increasing and building new infrastructure poses challenges in densely populated areas, it is important to optimally utilise existing infrastructure. Short-term traffic forecasting can help with this task, as its predictions can help to prevent congestion by rerouting vehicles. Recently, neural networks developed for...

Forecasting tourist counts with historical counts and external features

This research explored two types of models, ARIMA and multiple linear regression, for forecasting tourist counts in 7 locations around Amsterdam red light district, for the prediction horizon of up to 30 minutes.

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...