URBAN MICRO-MOBILITY AND DATA FOR PLANNING AND POLICYMAKING IIASA iTEM4 Fourth International Transport Energy Modeling workshop October 30, 2018 Regina Clewlow, Ph.D. CEO & Co-Founder Populus www.populus.ai
MOBILITY SERVICES HAVE RAPIDLY EVOLVED IN CITIES 2000 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 www.populus.ai
THE CHALLENGE Priv ivate mobilit ility s serv rvic ices are being launched in cities at an unprecedented pace. Pu Public ag agenc ncies have limited information about how mobility services are changing how people move. Cities es struggling to integrate new alternatives with existing transportation investments are now demanding access to data.
OUR SOLUTION Populus is a trusted, third-party data reporting platform that helps cities access private mobility data securely and cost-effectively. Data Public reporting data compliance Our Urban analytics to proprietary shape data-driven data policy decisions Software for Private cities to integrate mobility private and data public mobility services
CITIES NOW HAVE THE OPPORTUNITY TO HARNESS BIG DATA ON SHARED MOBILITY SERVICES TO PLAN FOR THE FUTURE OF TRANSPORTATION Deter ermine wher ere Uber er/Lyft ser ervices es a are c e complem ementar ary v vs. competit itiv ive with t transit it. As Assess eq equitable ac access to priv ivate d dockle less m mobilit ility s serv rvic ices (i.e. e. scooter ers a and b bikes es) Measure p e progress t towar ards transportation d demand manag agem ement (TDM) g goal als. Populus Mobility Manager - a platform for cities to access shared mobility data for monitoring operators and planning www.populus.ai
SAMPLE ANALYSIS: TRIP DISTANCE BY TECHNOLOGY Dockless s s scooters s and b bikes a s are gene nera rally lly u used f for s r shorter t r trip ip distan ances. Docked b bikes used f for s r slig ightly ly longer er d distan ances - likel ely d due e to the l loc ocations of of d doc ocks. (Dockles ess) elec ectric b bikes es are b e being used f for or m much l lon onger trips ps. www.populus.ai
SAMPLE ANALYSIS: TRIPS BY TRAFFIC ANALYSIS ZONE Micromoblity d dat ata c can an b be e harnes essed ed t to b better er u understand trip p patter erns t to plan an f for: ● Da Data-driv riven public lic tra rans nsit it planning ng. ● Impro rovin ing a activ ive tra ransportatio ion i infra rastru ructur ure (bike/ e/scooter er r racks, l lanes es). ● Understand nding ng e equity imp mpacts ts. www.populus.ai
POPULUS GROUNDTRUTH: DATA OVERVIEW MOBILITY BEHAVIOR ATTITUDES DEMOGRAPHICS VEHICLES SERVICES CHANGE ● ● ● ● ● Technology Household License rates Uber/Lyft use Substitution of ● ● ● Environmental structure # household Carsharing use Uber/Lyft for ● ● ● Transportation Age vehicles Bikesharing driving and ● ● ● Housing Income Make, model, use vehicle ● ● preferences Race year of most Scootersharing ownership ● ● ● Neighborhood Education used vehicle use Reasons for ● ● ● preferences Employment Reasons for Travel mobile changes in ● ● Political Housing type forgoing app use behavior ● ● ● ideology Rent/ own vehicle Delivery Reasons for ownership services changes in ● ● Reasons for Brand choice vehicle vehicle and customer ownership purchase satisfaction ● Future vehicle purchase plans
By Age ge RIDEHAILING ADOPTION By Hous ousehol hold Inc ncom ome
RIDEHAILING TRIPS Freq equen ency Trip p Distanc nces
RIDEHAIL POOLED TRIPS Freque uenc ncy of of P Pool ooled Rides Pr Price-Saving ngs Requi uired t to o Sha hare a R Ride
INTERCEPT SURVEY: LAST RIDEHAILING TRIP Alter ernate e Mode Trip p Pur urpos pose
REASONS RIDEHAILING USED OVER OTHER MODES Ins nstead of of Driving ng One neself Ins nstead of of Trans nsit
WITH BETTER DATA, No data PRIVATE MOBILITY SERVICES AND CITIES CAN PARTNER TO DELIVER A SAFE, Undesired Limited EQUITABLE, AND EFFICIENT outcomes policies TRANSPORTATION FUTURE
THANK YOU REGINA CLEWLOW, PH.D. CEO & CO-FOUNDER www.populus.ai
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