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Volume 557 Issue 7706, 24 May 2018

Driving force

Taxis are a common mode of transport in most of the world’s cities, but is the size of the fleet optimal for the number and nature of trips undertaken? In this issue, Mohammad Vazifeh and his colleagues reveal that it is possible to deploy fewer cabs without causing delays to the passengers or requiring them to share taxis. The team used a network-based approach in which the individual vehicles (not the individual rides) are shared across the transport network, and they tested their scheme against the millions of taxi trips taken in New York City over the course of one year. With prior knowledge of the trips taken, they calculated that the same service could have been provided with a fleet 40% smaller than the one actually used; when the scheme is modified to work from real-time information, a saving of around 30% is possible. The result has implications not only for current taxi fleets but also for the potential deployment of self-driving vehicles in the future. The cover picture captures their optimization model in action: it shows one minute of taxi rides in New York City (dots represent destinations, while lines are trajectories). The right side of the image (yellow lines) represents the current situation; the left side of the image (blue lines) shows the reduced fleet that could be obtained using the team’s model.

Cover image: Snoweria Zhang, Irene de la Torre, Fábio Duarte/MIT Senseable City Lab

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