Felix Becker

• ETH Zurich

To better understand the choice behavior of train route schedulers and to predict their choices for optimizing the annual construction schedule, prospective data for 2020 on train route decisions are analyzed using discrete choice models and machine learning classifiers. The choice alternatives include (i) partial cancellation of the train schedule...

The results of studies investigating the impact of automated vehicles can vary substantially, partly due to different assumptions on key input parameters such as costs and travel behavior. We therefore present a detailed cost analysis that was performed for 17 metropolitan areas in 15 different countries. Furthermore, we show the results of a compr...

This paper introduces mixl, a new R package for the estimation of advanced choice models. The estimation of such models typically relies on simulation methods with a large number of random draws to obtain stable results. mixl uses inherent properties of the log-likelihood problem structure to greatly reduce both the memory usage and runtime of the...

Automated Mobility on Demand (AMoD) is a concept that has recently generated much discussion. In cases where large-scale adoption of an automated taxi service is anticipated, the service’s impacts may become relevant to key transport system metrics, and thus to transport planners and policy-makers as well. In light of this increasingly important qu...

Automated Mobility on Demand (AMoD) is a concept that has recently generated much discussion. In cases where large-scale adoption of an automated taxi service is anticipated, the service’s impacts may become relevant to key transport system metrics, and thus to transport planners and policy-makers as well. In light of this increasingly important qu...

Automated driving technology along with electric propulsion are widely expected to fundamentally change our transport systems. They may not only allow a more productive use of travel time, but will likely trigger completely new business models in the mobility market. A key determinant of the future prospects of both existing and new mobility servic...

Although automation of motorized vehicles has the potential to transform public transport as we know it, prospective users are still skeptical. Trials with shared autonomous vehicles (AVs) offer an opportunity to assess future demand in a more realistic setting. In the context of an autonomous shuttle service trial operating on public road-space in...

Automation of vehicles will substantially change traffic and especially public transport as we know it. Ongoing implementations of test runs with self-driving vehicles offer the opportunity to assess future demand on this matter. Associated with the introduction of a self-driving bus service fully integrated into the local transport schedule on the...

We evaluate performance of four different operational policies to control an automated mobility-on-demand system with sequential vehicle-sharing in one public open-source-accessible, agent-based, high fidelity simulation environment. Detailed network dynamics on a road level of precision are taken into account. The case study is conducted in a simu...

Due to the potential of automated vehicles to offer a multitude of advantages to the travelers and therefore influence their daily routines, it is essential to monitor the public’s opinion on this particular technological development. The goal of a number of surveys in recent years was therefore not only to elicit the general acceptance of the tech...

Fast advances in autonomous driving technology trigger the question of suitable operational models for future autonomous vehicles. A key determinant of such operational models’ viability is the competitiveness of their cost structures. Using a comprehensive analysis of the respective cost structures, this research shows that public transportation (...