Geospatial analysis of residential parking behaviors using a semantic modeling approach. (April 2018)
- Record Type:
- Journal Article
- Title:
- Geospatial analysis of residential parking behaviors using a semantic modeling approach. (April 2018)
- Main Title:
- Geospatial analysis of residential parking behaviors using a semantic modeling approach
- Authors:
- Stewart, Kathleen
Fan, Junchuan
Schwarz, Chris
McGehee, Daniel V. - Abstract:
- Highlights: Transform driving trajectories from geometric base to semantic behaviors. Trajectory mining module uses acceleration behaviors to detect the start of parking. Individuals show consistent parking behaviors over time under same spatial context. Different driving behaviors occur during parking even under same spatial context. Abstract: Pedal misapplications by drivers have received attention as being an underlying factor for the phenomenon known as sudden unintended acceleration (SUA) in vehicles. This research investigates behaviors during a common task for drivers, namely residential parking. Parking has been identified as a maneuver that is often linked with SUA mishaps. Using driving trajectories data from a set of four couples collected as part of a naturalistic driving study, we investigate whether consistent behaviors can be detected when parking at home from a geospatial perspective, i.e., whether deceleration and braking occur in a characteristic way at the end of a driving trajectory, and whether these behaviors vary when the geospatial context of parking changes. An ontology-based approach is used to frame the key behaviors of the naturalistic driving, and big data techniques are applied to extract parking-specific behaviors from driving trajectories. Results show that individuals showed relatively consistent parking behaviors under the same geospatial context and the standard deviation of the deceleration threshold has a larger discrepancy betweenHighlights: Transform driving trajectories from geometric base to semantic behaviors. Trajectory mining module uses acceleration behaviors to detect the start of parking. Individuals show consistent parking behaviors over time under same spatial context. Different driving behaviors occur during parking even under same spatial context. Abstract: Pedal misapplications by drivers have received attention as being an underlying factor for the phenomenon known as sudden unintended acceleration (SUA) in vehicles. This research investigates behaviors during a common task for drivers, namely residential parking. Parking has been identified as a maneuver that is often linked with SUA mishaps. Using driving trajectories data from a set of four couples collected as part of a naturalistic driving study, we investigate whether consistent behaviors can be detected when parking at home from a geospatial perspective, i.e., whether deceleration and braking occur in a characteristic way at the end of a driving trajectory, and whether these behaviors vary when the geospatial context of parking changes. An ontology-based approach is used to frame the key behaviors of the naturalistic driving, and big data techniques are applied to extract parking-specific behaviors from driving trajectories. Results show that individuals showed relatively consistent parking behaviors under the same geospatial context and the standard deviation of the deceleration threshold has a larger discrepancy between couples parking at different residences than within couples where parking occurs at the same place. … (more)
- Is Part Of:
- Travel behaviour and society. Volume 11(2018)
- Journal:
- Travel behaviour and society
- Issue:
- Volume 11(2018)
- Issue Display:
- Volume 11, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 11
- Issue:
- 2018
- Issue Sort Value:
- 2018-0011-2018-0000
- Page Start:
- 9
- Page End:
- 20
- Publication Date:
- 2018-04
- Subjects:
- Naturalistic driving -- Geospatial trajectory -- Parking behavior -- Geospatial ontology -- Semantic data modeling -- Sudden unanticipated acceleration
Transportation -- Periodicals
Population geography -- Periodicals
303.48305 - Journal URLs:
- http://www.sciencedirect.com/science/journal/2214367X ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.tbs.2017.12.004 ↗
- Languages:
- English
- ISSNs:
- 2214-367X
- 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:
- 20973.xml