TNC and Taxi Data Methodology
Last September we announced a partnership with Uber and Lyft to share pick-up and drop-off data with cities to help inform curb management initiatives. Since that announcement, we have been collaborating with pilot cities to create a framework for sharing aggregated and anonymized pick-up and drop-off activity data using SharedStreets.
In this post, we’re sharing more about how it works. Our goal for this project is to continue to empower cities to better manage curb space with the highest resolution aggregated data on for-hire vehicle pick-up and drop-off, while protecting user privacy.
These metrics reflect our proposed methodology and have changed since the pilot began to fit city needs and requests. We will update this post with all changes to the methodology and we welcome any comments, questions and feedback you have. E-mail us here.
How it Works:
Step 1. Setting Model Weeks
The goal of this analysis was to give a picture of the relative demand for curb space. Therefore, we worked with cities to select several representative weeks over a year period to account for seasonality and minimize irregular trip activity. This allows for a more consistent combination of data from multiple sources. All data are processed from Monday through Sunday Midnight GMT.
Currently, Washington DC, Pittsburgh, Toronto, Los Angeles and Minneapolis are working with PUDO data through SharedStreets. The next round of cities is currently being determined.
Step 2. Setting Metrics
Two metrics are currently provided to support both the analysis of macro segments along a street and micro sub-segment areas of use along a street.
‘Macro’ Segment Analysis:
The ‘macro’ segment analysis was developed to triage locations across the city using a relative ranking of curb demand. This metric categorizes sections of streets (block-faces) into ranked a performance metric.
Our proposed metric classifies each block-face by percentile of regional performance. The percentile bins are adjustable, but as currently implemented it ranks segments over 50th percentile for start/end activity compared with all other segments in the survey area.
Time period: hour of week
Metric: Percentile usage > 50th
Questions this answers:
- What are the top 10 busiest blocks for pick-up or drop-off in our city at X time?
- Where is the busiest block-face near the baseball stadium during game time?
- Where are the most frequently used blocks in this business improvement district?
‘Micro’ Sub-segment Analysis:
The micro analysis converts data to average trips per sub-segment per hour (curb productivity rate) for queried period. Start and ends are counted separately. No absolute counts are shown, and only sub-segments that exceed 10 events for the query range will be viewable.
Standard sub-segment size: 10m
Standard time period: hour of week
Metric: Curb Productivity (Trips/sub-segment/hour)
Questions this answers:
- What times and where along this block do pick-ups and drop-offs occur?
- Where along a block are people getting dropped off/picked up? Why?
- Where does the volume of trips warrant time of day changes to the infrastructure?
- This area seems busy for drop-offs and is also a bicycle corridor. Is there a place on this block I can dedicate space for people getting dropped off to decrease bike/ride-hail conflict? Is there another block that would work nearby as well?
3. Data governance
Data aggregation and privacy
The metrics defined here assume collection and aggregation of data from Uber, Lyft and taxi services where available. All metrics show a combined view of data providers. Providers share aggregated data with SharedStreets References in SharedStreets data formats for curb demand, this ensures that trip level data does not leave providers control. SharedStreets takes in provider-aggregated data, combines provider data sets, and only stores the multi-provider aggregation.
Data Sharing
Data is provided to SharedStreets and is shared with external partners (e.g. a city or other city specified stakeholders) via the SharedStreets interface link. External partners access the data through SharedStreets developed analysis tools and are limited to metrics and analysis methods allowed by these tools. All metrics can be exported in GeoJSON format to be used in the analysis platform of the city’s choice. Access to the platform login is regulated through contractual terms governing both platform access and use, as agreed on by the data providers.
Data Security & Data Management
Data is provided to cities using a SharedStreets interface. All data is attached to SharedStreets references and exportable outside of the SharedStreets interface in geoJSON format. Two-step authentication is in place for users of the data.
What’s Next
Methodology suggestions and questions? Please e-mail us here. We worked with all first round pilot cities to develop this methodology but are always happy to take feedback.
