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Heuristic-based journey planner for mobility as a service (Maas)
Georgakis, P Almohammad, A Bothos, E Magoutas, B Arnaoutaki, K Mentzas, G
Georgakis, P
Almohammad, A
Bothos, E
Magoutas, B
Arnaoutaki, K
Mentzas, G
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2020-12-04
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Abstract
The continuing growth of urbanisation poses a real threat to the operation of transportation services in large metropolitan areas around the world. As a response, several initiatives that promote public transport and active travelling have emerged in the last few years. Mobility as a Service (MaaS) is one such initiative with the main goal being the provision of a holistic urban mobility solution through a single interface, the MaaS operator. The successful implementation of MaaS requires the support of a technology platform for travellers to fully benefit from the offered transport services. A central component of such a platform is a journey planner with the ability to provide trip options that efficiently integrate the different modes included in a MaaS scheme. This paper presents a heuristic that implements a scenario-based journey planner for users of MaaS. The proposed heuristic provides routes composed of different modes including private cars, public transport, bike-sharing, car-sharing and ride-hailing. The methodological approach for the generation of journeys is explained and its implementation using a microservices architecture is presented. The implemented system was trialled in two European cities and the analysis of user satisfaction results reveal good overall performance.
Citation
Georgakis P., Almohammad A., Bothos E., Magoutas B., Arnaoutaki K., Mentzas G. (2020) Heuristic-Based Journey Planner for Mobility as a Service (MaaS). Sustainability, 12(23), 10140.
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Journal article
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en
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© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/su122310140
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2071-1050
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2071-1050
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This research was funded by the European Union’s Horizon 2020 research and innovation programme grant number No 723176. And the APC was funded by the European Commission.