Victoria Dahmen

• Research Associate at Technical University of Munich

The last decade has seen a growing interest in semi-passive travel diaries. These diaries are characterized, in contrast to fully-passive ones, by the active validation and correction by the participants of automatically-generated trips. Albeit promising and with important benefits in terms of cost, scalability, and trip-recall quality, these diari...

Mode choice modeling is imperative for predicting and understanding travel behavior. For this purpose, machine learning (ML) models have increasingly been applied to stated preference and traditional self-recorded revealed preference data with promising results, particularly for extreme gradient boosting (XGBoost) and random forest (RF) models. Bec...

In this paper, we present a novel efficient multicriteria route model for bicycles. Efficiency is particularly relevant for handling large-scale routing requests, as is essential for centralized routing services and traffic assignment problems. The multicriteria aspect is crucial in the context of bicycles, since their route choice is heavily influ...

A manuscript summarising our "Mobilität.Leben" study that we conducted from May 2022 to December 2023 to observe the natural travel behavior experiments in Germany of the 9-Euro-Ticket and the Deutschlandticket using a six-wave panel survey and semi-passive travel diaries with waypoint tracking.

This study explores the relationship between travel stress, infrastructure quality, and cycling mode share. Utilizing multimodal trajectory data, survey responses on travel stress, and detailed road network information with geological and bicycle facility data, the study analyzes correlations between actual and perceived infrastructure quality, tra...

The Mobilität.Leben study investigated travel behavior effects of a natural experiment in Germany. In response to the 2022 cost-of-living crisis, two policy measures to reduce travel costs for the population in June, July, and August 2022 were introduced: a fuel excise tax cut and almost fare-free public transport with the so-called 9-Euro-Ticket....

Mode choice modeling is imperative for both predicting and understanding travel behavior. For this purpose, machine learning (ML) models have increasingly been applied to stated preference and traditional self-recorded revealed preference data with promising results, particularly for XGBoost and Random Forest (RF) models. Due to the rise in the use...