hubcab

Michael Szell mszell@mit.edu

Paolo SantiGiovanni RestaStanislav SobolevskyCarlo RattiSteven Strogatz (Cornell)

Benedikt GroßJoey LeeEric BaczukCarlo RattiAndi Weiß (47Nord)Stefan Landsbeck (47Nord)

Research Visualization & Explorer

hubcabTaxi-sharing in New York City: A network-based approach

Large GPS data sets on taxi movements

NYC

Singapore

13,500 cabs

26,000 cabs

Shanghai, San Francisco, Vienna, ...

Step 1: Analyze dataNY 170,000,000 trips / year

Pickups Dropoffs

Urban taxi systems

Pickups Dropoffs 7 days in 20 sec

Trips could be combined

Previous attempts at improvement

• Ride sharing

• Smart hailing

Can we come up with a new system?

• More efficient

• Less emissions

• Affordable alternative

Step 2: A new dispatch algorithm

Combine 2 trips

Step 2: A new dispatch algorithm

Combine k trips “Taxi Limousine”

Manhattan street network

4000 intersections9000 street segments

Extracted fromOpenStreetMap

Match GPS-coords of pickup/dropoff points with street intersections

Dynamic pickup and delivery problems

T1

T2

T3

T4

Like traveling salesman with time constraints

Small systems solvable with linear programming

Large systems not

Yang, Jaillet and Mahmassani, Transp Sci 38 (2004)Berbeglia, Cordeau and Laporte, Eur J Op Res 202 (2010)

Marin, An Op Res 143 (2006)

Shareability networks

k = 2T1

T2

T3

T4

T2T1

T3

T4

Shareability networks

k = 2T1

T2

T3

T4

T2T1

T3

T4

Solution: maximum matching

Generalizable to k>2but unfeasible for k>3

Chandra and Halldorsson, J Alg 39 (2001)

Satisfaction criterion

Maximum time delay Δ

Δ = 30 sec Δ = 60 sec

more tolerance = denser network = more sharing opportunities

Krings et al, EPJ Data Sci 1 (2012)

Oracle vs. Online

Oracle: omniscient, best possible

T1

T2

Online: realistic, constrained by time window δ

δ

Set δ = 1min

Step 2: A new dispatch algorithm

• Send destination request (via app)

• Wait δ min

• Receive sharing options

• Trip may be prolonged up to Δ min

How it works:

Consequences:

• Less traffic = less pollution etc

• Split costs for customers

Step 3: Simulation results: MOST trips can be combined!

Only δ = 1 min initial waiting time needed!

Online tool for interactive exploration

http://hubcab.org

(in development)

Zoom into the data

Pickups Dropoffs

Michael Szell mszell@mit.edu

Benedikt GroßJoey LeeEric BaczukCarlo RattiAndi Weiß (47Nord)Stefan Landsbeck (47Nord)

Research Visualization & Explorer

hubcabTaxi-sharing in New York City: A network-based approach

Paolo SantiGiovanni RestaStanislav SobolevskyCarlo RattiSteven Strogatz (Cornell)