Shared Mobility in Smart Cities: insights from Ride-Hailing in Austin, TX

April 5, 2018
16:00  -  16:45
Room 204

The city of Austin, TX is at the forefront of energy efficient and shared mobility services
such as ride-hailing, bike-sharing, car-sharing and electric last-mile micro-transit. RideAustin, a
local non-profit ride-hailing service operating since June 2016, has completed millions of trips and
has shared travel data for research purposes. Information on pick-up and drop-off locations,
timestamps, distance, duration, and fare for each passenger ride as well as vehicle make, model,
and year are made available. This study analyzes ten months of origin-destination data to
understand impacts on transportation and energy, and develops a novel methodology for
estimating ‘dead-heading’ and commuting trips. A comprehensive statistical analysis is conducted
for 5,000 unique drivers, 260,000 unique passengers, and 1.5 million rides.

In this study drivers are clustered based on the numbers of hours driving per week into
occasional, regular, and full-time categories. We find that regular drivers – 40% of drivers –
typically complete 3.5 shifts per week and 6 rides per shift, with an annualized estimated VMT of
12,800 miles, whereas full-time drivers – just over 10% of drivers – drive 5.5 shifts per week and
9 rides per shift on average, with an annualized estimated VMT of 29,000 miles. Total mileage
driven consist of ride miles with passenger on-board, ‘dead-heading’ miles in between rides, and
commuting distance at the beginning and end of each driver’s shift. The fraction of miles driven
with a passenger on board is 51%, while 31% is ‘dead-heading’, and the remaining 18% is
commuting.

Geospatial data fusion is performed to infer land use characteristics of the major ride-hailing trip
generators and attractors. Commercial locations (including retail, restaurants and bars) are found
to be the most common trip origins and destinations, followed by single-family housing,
apartments, offices and the airport. Peak ridership occurs in the evening, between 6pm and
midnight, which seems to indicate recreational trip purposes. Shift VMT distributions shows that
approximately 90% of shifts are under 150 miles, while about 70% of drivers have never
exceeded 250 miles per shift. High annual mileage of regular and full-time drivers underlines the
potential benefits resulting from the adoption of energy efficient electric vehicles for ride-hailing
services. In the future, managed charging of electric ride-hailing fleets could provide grid services,
thereby co-optimizing energy and mobility outcomes.

Session Category :  ACADEMIC  TRANSPORTATION