Data driven methods for effective micromobility parking. (June 2021)
- Record Type:
- Journal Article
- Title:
- Data driven methods for effective micromobility parking. (June 2021)
- Main Title:
- Data driven methods for effective micromobility parking
- Authors:
- Sandoval, Ricardo
Van Geffen, Caleb
Wilbur, Michael
Hall, Brandon
Dubey, Abhishek
Barbour, William
Work, Daniel B. - Abstract:
- Highlights: Clustering historical trip data is used to identify high-demand parking locations for shared urban mobility devices. A case study in Nashville, Tennessee, USA, shows that 20 parking locations is sufficient to capture 1 in 4 trips. Built environment factors such as sidewalk width are used to prioritize parking locations. Prioritized parking addresses 300% more narrow-sidewalk trips by sacrificing 13% total trips served. Abstract: In this work, we propose a data-driven method to use proven clustering algorithms for establishing shared electric scooter (SES) parking locations and assessing their anticipated utilization. We first address the problem of finding locations for a given number of parking facilities, based pur0ely on demand, that maximize the number of trips that would likely be parked at these facilities. We then formulate an enhanced version of the SES parking facility problem in which exogenous environmental factors are considered, such as sidewalk width. Parking SESs on narrow sidewalks raises accessibility concerns for other users of this infrastructure and capturing these trips in dedicated parking facilities is a valid priority to trade off with pure demand maximization. These methods are demonstrated in two case studies, which use a large SES dataset from Nashville, Tennessee, USA. We provide empirical results on how many facilities are needed to serve demand of SESs and necessary capacity allocation of the facilities. When the methodologyHighlights: Clustering historical trip data is used to identify high-demand parking locations for shared urban mobility devices. A case study in Nashville, Tennessee, USA, shows that 20 parking locations is sufficient to capture 1 in 4 trips. Built environment factors such as sidewalk width are used to prioritize parking locations. Prioritized parking addresses 300% more narrow-sidewalk trips by sacrificing 13% total trips served. Abstract: In this work, we propose a data-driven method to use proven clustering algorithms for establishing shared electric scooter (SES) parking locations and assessing their anticipated utilization. We first address the problem of finding locations for a given number of parking facilities, based pur0ely on demand, that maximize the number of trips that would likely be parked at these facilities. We then formulate an enhanced version of the SES parking facility problem in which exogenous environmental factors are considered, such as sidewalk width. Parking SESs on narrow sidewalks raises accessibility concerns for other users of this infrastructure and capturing these trips in dedicated parking facilities is a valid priority to trade off with pure demand maximization. These methods are demonstrated in two case studies, which use a large SES dataset from Nashville, Tennessee, USA. We provide empirical results on how many facilities are needed to serve demand of SESs and necessary capacity allocation of the facilities. When the methodology considers sidewalk width in facility placement, the refined parking locations can address 300% more problematic trips parked along narrow sidewalks, with only a nominal sacrifice, around 13%, in the overall number of trips served. … (more)
- Is Part Of:
- Transportation research interdisciplinary perspectives. Volume 10(2021)
- Journal:
- Transportation research interdisciplinary perspectives
- Issue:
- Volume 10(2021)
- Issue Display:
- Volume 10, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 10
- Issue:
- 2021
- Issue Sort Value:
- 2021-0010-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-06
- Subjects:
- micromobility -- Clustering -- Dockless scooters -- Urban planning
Transportation -- Periodicals
388.05 - Journal URLs:
- https://www.sciencedirect.com/journal/transportation-research-interdisciplinary-perspectives/issues ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.trip.2021.100368 ↗
- Languages:
- English
- ISSNs:
- 2590-1982
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17330.xml