Creation of Individualized Sets of Multimodal Travel Itineraries

Digitalization enables travelers to access an ever-increasing number of mobility services. Creating door-to-door multimodal travel itineraries from individual mobility services is challenging, since the impact of individual preferences on complex multimodal travel itineraries is not transparent to the traveler. To support them in their individual choice of relevant itineraries, travel websites create sets of multimodal travel itineraries using multimodal shortest path approaches. Then, they let travelers specify their individual preferences further to reduce or extend the set of travel itineraries. However, due to the complexity of the underlying search space and the large Pareto front, it is challenging to individualize the created set of travel itineraries systematically. In this paper, we use solution sampling to create request-specific meta-information about the complex solution space of multimodal travel itineraries. We identify intervals of and relationships between travel parameters such as travel time, price, number of transfers and mode choice by applying multimodal shortest path approaches with solution sampling. The derived request-specific meta-information is used to individualize a traveler’s set of multimodal travel itineraries. As an alternative to complete evaluation of the Pareto front, we examine solution sampling in a laboratory setting with data on scheduled and non-scheduled transportation services from German transit networks.