A methodology to determine suitable locations for regional shared mobility hubs
Gonçalo Homem Correia (Transport and Planning)
Rob van Nes (Transport and Planning)
JA Annema (TU Delft - Transport and Logistics)
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Abstract
As a solution to the high greenhouse gas emissions and declining quality of life caused by private vehicles, the shared mobility hub is introduced. The shared mobility hub is a place where multiple modalities come together, including public transport and shared private mobility. As the shared mobility hub is a relatively new solution, limited research is available on the topic, especially on finding potentially suitable locations for allocating them. In this research, this knowledge gap is addressed by developing and testing a generic methodology to determine suitable locations for a specific type: the regional shared mobility hub. The regional shared mobility hub is located outside a city center being able to act as an intermodal point of transfer. The developed methodology is a combination of two existing methods: the GIS Multi-Criteria Analysis (MCA) and Multi-Actor Multi-Criteria Analysis (MAMCA) available in the literature. The method is able to score and weight different criteria which determine regional shared mobility hub suitability, taking the end-user (traveler), operator, and government perspectives into account in the weighting. Results are presented in multiple heat maps based on scenarios with varying stakeholder weight importance. The methodology developed consists of five criteria that measure location suitability (potential demand at a certain location, hub implementation costs, generalized travel costs from and to the hub, link to surroundings, and societal impact) measured by nine attributes. In this method, the choice is made for the Analytic Hierarchy Process (AHP) to determine the criteria weights. The developed methodology is applied to the region of Rotterdam (The Netherlands) to analyse if the methodology produces useful results for policy implementation. From multiple analyses, it appears that the methodology is suitable for tackling the location suitability determination problem, as it produces intuitive results.
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