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Forecasting Travel Demand for New Mobility Services Employing Autonomous Vehicles
The impact of new mobility services, such as shared autonomous vehicles, should be evaluated in terms of their sustainability based on future demand as well as their business feasibility based on current demand. However, the effects of shared autonomous vehicles, such as the number of autonomous veh...
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Published in: | Transportation research procedia (Online) 2018, Vol.34, p.139-146 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The impact of new mobility services, such as shared autonomous vehicles, should be evaluated in terms of their sustainability based on future demand as well as their business feasibility based on current demand. However, the effects of shared autonomous vehicles, such as the number of autonomous vehicles required to replace conventional vehicles, have only been examined based on current demand obtained from traffic surveys. The aging of national populations is inevitable and has significant implications for traffic, including age-related declines in individual travel needs and increasing rates of driver’s license relinquishment. In this paper, we propose a method of forecasting travel demands by applying a model that generates predictions for both human mobility and human activity using future population and future percentages of licensed and unlicensed citizens as input. The proposed method predicts mobility-service demand by considering changes in age compositions, age-related declines in individual travel needs, increasing rates of driver’s license relinquishment, and regional factors including the level of service for alternative modes of transportation. In addition, we describe a new mobility service employing autonomous vehicles and use it as an example for projecting the demand for such new services arising from future travel demands. |
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ISSN: | 2352-1465 2352-1465 |
DOI: | 10.1016/j.trpro.2018.11.025 |