Mobilityscope: Interactive optimization to deliver better active transportation K. Shankari, UC Berkeley Sara Barz, City of Oakland Add logos June 14, 2016

Sustainable transportation planning has a data problem Data on people is limited Census: every 10 years; ACS: updates every year Only commutes to work Only primary mode (bike -> bus -> bike) => bus Household Travel Survey: All trips across a wide variety of modes Expensive, so infrequent and small Self-reported Project/Plan Specific Surveys Traffic counts are primary, track vehicles, not people End to end data is missing (last mile problem) Data is siloed - no holistic view across modes Active transportation => person with clipboard No data on perceptions - e.g safety Last SF Bay Area Travel Survey (BATS) was in ... 2000 Tracks travel volume (huge emphasis) and not trips Condense 2&3

How we want to improve transportation planning in the City of Oakland Eugene Chan via Flickr Better Data: Opportunity for the City to intercept travelers with focused questions at the right time and place Better Plans: Ability for the City to create plans and projects that can be efficiently tested and evaluated Competitive Projects: Advatage to craft more competitive grant applications with better data Targeted Projects: Opportunity to target investments in the right of way according to demand by mode user group and to reward specific modes, like walking and biking Creating a Department of Transportation Flickr photo: https://www.flickr.com/photos/eugevon/26469327061/in/faves-29543560@N07/ Better plans, more fundable projects Better qualitative and quantitative data Targeted projects Competitive Projects Flickr photo: https://www.flickr.com/photos/bike/1336615373/in/faves-29543560@N07/ Traffic Counts & ACS data Telegraph protected bike lane ATP demands data on users as well as user growth projections

Potential: Agile transportation system Waterfall -> agile Waterfall originally from Civil Engineering Still in Civil Engineering – 5 year plans, implement, population does what it does, re-measurement super later Very hard to estimate cause and effect Close the loop, can now enable cause and effect Collect passive data using smartphones, augment with qualitative data from users on safe/suck + targeted surveys Compare against goals Controller makes change, see if it works, if so, do more, if not, try something else closing the loop engages residents, creates community & enhance satisfaction. moves sustainable communities forward. Build cities based on what people actually do rather than a model of what they should do Active transportation - time scales are short by planning standards. Small targeted changes can have big impact.

What makes this Mobilityscope system different? User centric versus City centric Making it possible for planners to use all this cool

Evaluation No comparable open data at scale! That’s why we are building this! Trip data: Existing data collection Comparison with regional model Spot checks on specific corridors User initiated qualitative data: Feedback on stress hotspots compared to regional stress estimates based on GIS and land use Survey data: Compare response rate to existing postcard based mechanism Design Survey data Prioritization Evaluation Trip data Qualitative data Very hard to evaluate. Three data sources, used in various parts of the agile transportation cycle. Largely compare against existing methods although existing methods have known limitations as described earlier.

End to end system

Deployment plan

K. Shankari | shankari@eecs.berkeley.edu Sara Barz | sbarz@oaklandnet.com | @skbarz