Abstract
As cities face the escalating demands of urban mobility, sustainability, and accessibility, multimodal transportation systems are gaining recognition as a solution to these complex challenges. It examines how different modes of transport (cars, public transport, bicycles, walking, and micromobility) can be integrated into seamless transport networks which improve the user experience as well as the efficiency of transport operations. The chapter outlines the challenges facing multimodal systems, including complex iteration requirements, coordination between the numerous different transportation providers, differing regulatory environments, and the need for users to adapt to integrated systems. It goes on to highlight best practices, keeping users at the centre of the agenda when introducing new integrated ticketing solutions and developing robust infrastructure to support such systems in place. It concludes with policy recommendations, stressing the need for regulatory alignment, sustainable funding frameworks, and incentives for sustainable practices.
Original language | English |
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Title of host publication | Machine Learning and Robotics in Urban Planning and Management |
Editors | Kamalesh Ravesanger, Christian Kaunert, Bhupinder Singh, Sahil Lal, Manmeet Kaur Arora |
Publisher | IGI Global |
Pages | 49-66 |
Number of pages | 18 |
ISBN (Electronic) | 9798369394120 |
ISBN (Print) | 9798369394106, 9798369394113 |
DOIs | |
Publication status | Published - 2025 |