Improving a CollaborativeTravel Planning Application

In this thesis, we present a novel multi-agent travel planning algorithm which finds shared journeys for multiple travellers. The algorithm uses existing planners and works in three phases: finding initial single-agent plans, their optimisation by the best-response approach and matching the plans to the timetable. The algorithm has been evaluated using real-world public transportation data of the United Kingdom in five different scenarios of increasing complexity. The results show linear scalability both with the scenario size and the number of agents, confirming empirically that the proposed algorithm has overcome the scalability issues experienced in the previous work. The algorithm can be used in practice as a part of a travel planning system for real passengers. However, there is a trade-off between the amount of improvement in cost, the percentage of found timetables and the prolongation of journeys. i ACKNOWLEDGEMENTS Acknowledgements At first, I would like to thank my supervisor Michael Rovatsos for his guidance and support. Also, I wish to thank Matt Crosby, Radomír Černoch and Dominik Głodzik for their feedback. Last but not least, I would like to thank Gerhard Wickler for the consultation of the PDDL specifications. ii DECLARATION Declaration I declare that this thesis was composed by myself, that the work contained herein is my own except where explicitly stated otherwise in the text, and that this work has not been submitted for any other degree or professional qualification except as specified. Abstract i Acknowledgements ii Declaration iii Table of contents iv 1 Introduction 1 1.