Agent-based transport models such as MATSim have been developed and used for the past few decades to simulate transportation systems in different cities and are capable of accurately reproducing travel patterns at different levels of aggregation. Given their disaggregate representation of both travel demand and supply as well as the high level of spatial and temporal detail, agent-based transport models also have the potential to allow ...

Discrete choice experiments (DCE) are widely used in transport planning to elicit peoples' preferences for different alternatives and attributes. They rely on stated and/or revealed preference (SP/RP) data. Over the past years, web-based DCEs became popular in many disciplines. Yet, there is little literature on how to actually implement them. This paper provides a framework to implement DCEs in two ways, using the online survey platform ...

This study introduces an autonomous ride-pooling service to six communities with varying population sizes and trip densities in the Munich Metropolitan Region. We analyze a) a laissez-faire scenario without additional policies, defining the modal shift through an incremental mode choice model and b) a draconian scenario in which each within-city car trip is replaced by ride-pooling. Results indicate a logarithmic increase in system ...

A genetic algorithm to design efficient large-scale public transport networks is extended. It goes beyond existing approaches by incorporating a dynamic demand response towards both changes in the network and external disruptions. The algorithm is based on an agent-based (MATSim) simulation and tested for the city of Zurich. Compared to the existing public transport system, it proposes a sparser network with substantially higher frequencies. ...