Trip Purpose Based on Naturalistic Driving Data
| dc.contributor.author | Costa, Rufina | en |
| dc.date.accessioned | 2024-07-10T12:15:20Z | en |
| dc.date.available | 2024-07-10T12:15:20Z | en |
| dc.date.issued | 2024-07-09 | en |
| dc.description.abstract | Understanding trip purpose is important as it provides valuable information for driver behavior research, traffic management, and urban transportation planning. The primary challenge in analyzing trip purpose is upholding the constraints on personally identifiable information (PII) and ensuring confidentiality. Privacy protocols are particularly stringent for the Second Strategic Highway Research Program 2 (SHRP 2) regarding data at trip origins and destinations. Researchers have access to specific origin and destination data only within a secured enclave. Researchers receive only truncated trip data when it is exported, limiting their ability to identify specific origins and destinations that could indicate home or work-related trips. In this study, we successfully identified and labeled home and work-related trips without retaining any geographical information. This approach allows the use of the derived information in further analyses without depending on any PII, thus preserving individual privacy and complying with data protection regulations. The study utilized geospatial data, including latitude and longitude, as well as trip duration, Google API labels, driver demographic information, and trip date and time. To identify residential trips, we considered only those trips that the Google API labeled as residential destinations and that had an interim of at least 8 hours before the next trip. Geofencing was then employed across all destinations by each participant. The destination that was most frequently visited was identified as the resident’s home location. Work-related trips were identified for participants who reported full-time employment and had trips with a 2-hour or longer stay at destinations not classified as residential according to the Google API. Work-related trips were defined as those involving 16 consecutive visits to the same destination per month, covering at least 70% of the study time for the participant. Further analysis was conducted to link trips together, enabling the identification of round trips that either involved a single purpose or multiple destinations. Additionally, trips related to home and work that involved safety-critical events were specifically identified. Finally, trips that occurred 100 miles away from home were also analyzed, with a focus on examining the patterns based on the day of the week when each trip took place. The study used a novel method to identify home and work-related trips and successfully identified 1,546,798 home trip destinations from 2,937 drivers and 48,813 trips defined as work trips from 109 participants. These are now available for researchers as part of the SHRP 2 export, enhancing the scope for further academic and practical analyses. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | https://hdl.handle.net/10919/120626 | en |
| dc.language.iso | en | en |
| dc.publisher | National Surface Transportation Safety Center for Excellence | en |
| dc.relation.ispartofseries | NSTSCE; 24-UD-147 | en |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| dc.subject | naturalistic driving study | en |
| dc.subject | SHRP 2 | en |
| dc.subject | PII | en |
| dc.subject | transportation | en |
| dc.subject | location data | en |
| dc.title | Trip Purpose Based on Naturalistic Driving Data | en |
| dc.type | Technical report | en |
| dc.type.dcmitype | Text | en |